DELIVERABLE
Project Acronym: ASSESS CT
Grant Agreement number: 643818
Project Title: Assessing SNOMED CT for Large Scale eHealth
Deployments in the EU
WP1 D1.3 Current and Future Use of SNOMED CT
(Interim Report)
Appendixes
Authors:
Giorgio Cangioli
HL7 Foundation
Catherine Chronaki
HL7 Foundation
Rémy Choquet
BNDMR, APHP
Daniel Karlsson
Linköping University
Riika Vuokko
Terveyden ja
Hyvinvoinnin Laitos
Terveyden ja
Hyvinvoinnin Laitos
Virpi Kalliokuusi
Päivi Hämäläinen
Reza Fathollah
Nejad
Ronald Cornet
Terveyden ja
Hyvinvoinnin Laitos
Hochschule
Niederrhein
AMC
François Macary
Phast
Pim Volkert
Nictiz
Laura Sato
HSCIC
Stefan Schulz
Marie Christine
Jaulent
Estefânia Araújo
Medizinische
Universität Graz
Institut National de la
Sante et de la
Recherche Medicale
Clinical
Terminologies Centre
in Portugal - SPMS
Project co-funded by the European Commission within H2020-PHC-2014-2015/H2020_PHC-2014-single-stage
Dissemination Level
PU
Public
X
PP
Restricted to other programme participants (including the Commission Services
RE
Restricted to a group specified by the consortium (including the Commission Services
CO Confidential, only for members of the consortium (including the Commission Services)
ASSESS CT – D1.3
Revision History, Status, Abstract, Keywords, Statement of Originality
Revision History
Revision
Date
Author
0.1
03/Nov/2015
C. Chronaki
HL7 Foundation
First Outline
0.2
17/Feb/2016
C. Chronaki; G. Cangioli
HL7 Foundation
Revised Outline
0.3
25/Feb/2016
L. Sato; G. Cangioli,
C. Chronaki
HSCIC HL7
Foundation
UK Implementation case Pathology reports
(Lab Results)
0.4
28/Feb/2016
M.C. Jaulent; Estefânia
Araújo
INSERM; SPMS
Updates from the French and Portuguese
Focus Groups.
0.5
01/Mar/2016
F. Macary; G. Cangioli
Phast
HL7 Foundation
French implementation case (Lab Results)
0.6
03/Mar/2016
R. Vuokko
THL
Finnish implementation case (Lab Results)
0.7
11/Mar/2016
C. Chronaki; G. Cangioli,
0.8
15/Mar/2016
R. Choquet ; G. Cangioli ;
D. Karlsson ; P. Volkert
HL7 Foundation;
APHP; Linköping
University; Nictiz
Updated Case Study Sections
0.9
25/Mar/2016
R. Cornet, R. Nejad,
C. Chronaki; G. Cangioli
AMC; Hochschule
Niederrhein; HL7
Foundation
Release for review
0.10
29/Mar/2016
S. Schulz
Medial University
of Graz
General Revision
1.0
11/Apr/2016
S. Schulz; G. Cangioli
Medial University
of Graz
HL7 Foundation
Final Version (Interim Release)
Date of delivery
Contractual:
Status
final
Organisation
Description
Updated Section 1 and 5. Added
Questionnaires results.
Revision of Section 4 and 5
31.03.2016
Actual:
11.04.2016
/draft
Abstract
The current interim report consolidates the evidence on the current and future use
(for dissemination) of SNOMED CT. It (a) presents updated case studies identified in the focus groups,
literature review, and the workshops, while elaborating on a small number of case
studies involving relevant experts; it provides updated information about (b) country
focus groups; (c) questionnaire and (d) revision workshop; moreover it describes the
results of (e) the survey realized with non-European countries (f) and a literature
review. This report also completes the picture presented in D1.1 and D1.2 on the
use of terminologies in Europe and worldwide. This interim report will be completed
and integrated into the final deliverable D1.4 with (a) an updated review of the
assessment of SNOMED CT against Annex II of the European Standardization
Regulations, and (b) results from an EU / US meeting in May 2016, and (c) any
update concerning the assessment of case studies and the country overview
questionnaires.
Having identified specific areas or topics where there are gaps in knowledge or a
strong need to explore evidence, this report will interplay / feed into D4.3 to provide
recommendations on further actions. In the context of PHC34 cooperation early
versions of this deliverable will provide input to the eStandards project and in
particular D3.3 (first iteration of the eStandards roadmap).
Keywords
Current use, terminologies, case studies
Standardization Regulation, IHTSDO policies
of
terminology
use,
European
Statement of originality
This deliverable contains original unpublished work except where clearly indicated otherwise.
Acknowledgement of previously published material and of the work of others has been made through
appropriate citation, quotation or both.
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Table of Contents
1
Foreword...................................................................................................................... 6
2
Glossary....................................................................................................................... 7
3
Appendix 1 - Case Study Assessment Template ...................................................... 8
3.1
Case study description ........................................................................................... 8
3.2
Implementation Case XYZ.1 ................................................................................... 8
3.2.1
The Context ....................................................................................................................................... 8
3.2.2
Drivers for adoption ............................................................................................................................ 8
3.2.3
Adoption and operational strategies ................................................................................................. 15
3.2.4
Other remarks .................................................................................................................................. 16
4
Appendix 2 - Case Study Reports ............................................................................ 17
4.1
Case studies selection process ............................................................................ 17
4.2
Cross-border Exchange of Patient Summaries: Problem Lists .............................. 19
4.2.1
Case Study Description.................................................................................................................... 19
4.2.2
The European Cross-borders exchange of PS (epSOS/EXPAND) .................................................. 20
4.3
National/Regional Exchange of Patient Summaries: Problem Lists ...................... 28
4.3.1
Italy: the Fascicolo Sanitario Elettronico .......................................................................................... 28
4.3.2
The Dutch Diagnosis Thesaurus project .......................................................................................... 31
4.3.3
Sweden: the National Program for Data collection. .......................................................................... 34
4.4
ERNs Rare disease Registry ................................................................................ 38
4.4.1
European Context ............................................................................................................................ 38
4.4.2
Registries for rare diseases ............................................................................................................. 39
4.4.3
Case study ....................................................................................................................................... 42
4.4.4
Selecting (or detecting) RD patients from care setting (EHR) to include into registries or
cohorts: the French national registry for rare diseases perspective ................................................. 43
4.5
National/Regional Exchange of Lab Procedures/ Results ..................................... 52
4.5.1
The Laboratory Reports in the French “Dossier Médical Personnel (DMP)” .................................... 52
4.5.2
National/Regional Exchange of Laboratory Procedures and Results in Finland .............................. 57
4.6
National/Regional Exchange of Lab Pathology Procedures/Results ..................... 65
4.6.1
Case Study Description.................................................................................................................... 65
4.6.2
The NHS Diagnostics Data Service ................................................................................................. 65
5
Appendix 3: Overview of European Countries (Questionnaire) ............................. 74
5.1
About your country ............................................................................................... 74
5.1.1
Which statement describes your country best (IHTSDO membership and SNOMED CT
adoption)? ........................................................................................................................................ 74
5.1.2
Which of the following statements apply to your country (usage of terminologies at the
national level)? ................................................................................................................................. 77
5.1.3
Is/are there national competence center(s) for terminologies in your country? ................................ 78
5.1.4
Are there international terminologies used nationally for health and social data? ............................ 80
5.1.5
Are there relevant domains for which you feel that - in your country - Nationally adopted
terminologies are missing? .............................................................................................................. 83
5.1.6
Are there nationally defined terminologies used at the national level for health and social
data? ................................................................................................................................................ 85
5.1.7
How the nationally adopted terminologies are are managed (administration; authoring ;…)? ......... 88
5.1.8
How the nationally adopted terminologies are made available for usage? ....................................... 90
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5.1.9
Tools and technologies that have been applied in your country for facilitating the usage of
nationally adopted terminologies by end users ................................................................................ 91
5.1.10
Methodologies applied in your country for facilitating the usage of nationally adopted
terminologies by end users .............................................................................................................. 93
5.2
About SNOMED CT adoption and usage.............................................................. 96
5.2.1
Which approach has been followed in your country for introducing SNOMED CT as a
terminology for health and/or social care data? ............................................................................... 96
5.2.2
For which use cases/purposes is currently used SNOMED CT in your country? ............................. 98
5.2.3
In which care settings is SNOMED CT used? .................................................................................. 99
5.2.4
For the indicated use cases how SNOMED CT is actually used? .................................................. 101
5.2.5
For the indicated use cases what of SNOMED CT do you actually use? ....................................... 103
5.2.6
Did (or will) the introduction of SNOMED CT in your country affect existing terminologies ............ 104
5.2.7
Could you briefly describe what has been (or what will be according to your current
evaluation) the impact of the introduction of SNOMED CT in the existing IT architecture
(including software)? ...................................................................................................................... 105
5.2.8
Could you briefly describe what has been the main challenges (or what will be according to
your current evaluation) of the transactional scenario (i.e. moving toward the adoption of
SNOMED CT)? .............................................................................................................................. 108
5.2.9
Could you briefly describe how those challenges have been managed (or are planned to be
managed)? ..................................................................................................................................... 110
5.2.10
Could you summarize the main steps accomplished for the adoption of SNOMED CT ................. 112
5.2.11
What has been the content selection approach applied (or planned to be applied) for
introducing in your country SNOMED CT? ..................................................................................... 114
5.2.12
Who was (is planned to be) responsible for selecting the contents? .............................................. 116
5.2.13
For supporting the indicated use cases, which selection approach has been applied in your
country? ......................................................................................................................................... 117
5.2.14
Can you quantify (and qualify) the selected SNOMED CT Refset(s)? ........................................... 118
5.2.15
What is the approach followed for translating terms and collect possible synonyms? ................... 119
5.2.16
Who is responsible for translating designations and collect possible synonymous? ...................... 121
5.2.17
What are the main on-going activities? .......................................................................................... 121
5.2.18
Could you briefly describe your future plans? ................................................................................ 122
5.3
About non-IHTSDO member countries ............................................................... 124
5.3.1
What are according to you the main reasons for which your country is not currently an
IHTSDO member? ......................................................................................................................... 124
5.3.2
Are you aware about any current or past plan, discussion or evaluation regarding the
adoption of SNOMED CT in your country? .................................................................................... 125
5.3.3
Are you aware about any IHTSDO affiliate in your country? .......................................................... 127
6
Appendix 4 - Overview of non-European Countries (Questionnaire) .................. 128
6.1
About your country ............................................................................................. 128
6.1.1
Which statement describes your country best (IHTSDO membership and SNOMED CT
adoption)? ...................................................................................................................................... 129
6.1.2
Which of the following statements apply to your country (usage of terminologies at the
national level)? ............................................................................................................................... 130
6.1.3
Is/are there national competence center(s) for terminologies in your country? .............................. 131
6.1.4
Are there international terminologies used nationally for health and social data? .......................... 132
6.1.5
Are there relevant domains for which you feel that - in your country - Nationally adopted
terminologies are missing? ............................................................................................................ 133
6.1.6
How are the nationally adopted terminologies are managed (administration; authoring ;…)
and distributed? ............................................................................................................................. 134
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6.1.7
Tools and technologies that have been applied in your country for facilitating the usage of
nationally adopted terminologies by end users? ............................................................................ 135
6.1.8
Methodologies applied in your country for facilitating the usage of nationally adopted
terminologies by end users ? ......................................................................................................... 136
6.2
About SNOMED CT adoption and usage............................................................ 138
6.2.1
Which approach has been followed in your country for introducing SNOMED CT as a
terminology for health and/or social care data? ............................................................................. 138
6.2.2
For which use cases/purposes is currently used SNOMED CT in your country? ........................... 139
6.2.3
For the indicated use cases how SNOMED CT is actually used? .................................................. 139
6.2.4
For the indicated use cases what of SNOMED CT do you actually use? ....................................... 140
6.2.5
Did (or will) the introduction of SNOMED CT in your country affect existing terminologies? .......... 142
6.2.6
Could you briefly describe what has been (or what will be according to your current
evaluation) the impact of the introduction of SNOMED CT in the existing IT architecture
(including software)? ...................................................................................................................... 142
6.2.7
Could you briefly describe what has been the main challenges (or what will be according to
your current evaluation) of the transactional scenario (i.e. moving toward the adoption of
SNOMED CT)? .............................................................................................................................. 143
6.2.8
Could you briefly describe how those challenges have been managed (or are planned to be
managed)? ..................................................................................................................................... 144
6.2.9
Could you summarize the main steps accomplished for the adoption of SNOMED CT ................. 144
6.2.10
What has been the content selection approach applied (or planned to be applied) for
introducing in your country SNOMED CT? ..................................................................................... 145
6.2.11
Can you quantify (and qualify) the selected SNOMED CT Refset(s) ............................................. 146
6.2.12
What are the main on-going activities? .......................................................................................... 147
6.2.13
Could you briefly describe your future plans? ................................................................................ 147
Appendix 5 - Report on 2nd revision workshop ..................................................... 149
7
7.1
Highlights from the country focus groups and questionnaires ............................. 149
7.2
Implementing SNOMED CT in General Practice in the UK ................................. 153
7.3
Selecting use case scenarios and case studies for reference terminologies in the
health sector ................................................................................................................... 153
7.4
8
Final discussion .................................................................................................. 154
Appendix 6 - Literature Review on the Use of SNOMED CT ................................. 156
8.1
Introduction ........................................................................................................ 156
8.2
Results ............................................................................................................... 156
8.2.1
SNOMED CT Focus and Usage Category ..................................................................................... 157
8.2.2
Medical Domains and countries ..................................................................................................... 164
8.3
Search Queries .................................................................................................. 166
8.4
Full list of eligible publications: ........................................................................... 167
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1
Foreword
This document gathers all the appendixes of the ASSESS CT deliverable D1.3 (interim
report) for better documenting the results of the survey and assessment activities described
in that document (D1.3).
Please refer to the main deliverable document WP1 D1.3 “Current and Future Use of
SNOMED CT (Interim Report)” for context information (e.g. scope, methodologies; executive
summary).
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2
(ICD) AM
(ICD) CA
(ICD) CM
AMT
API
ASIP
ATC
C-CDA
CCI
CDA
CIBB
CIMI
CoA
CoT
Glossary
ICD - Australian Modification
ICD - Canada
ICD - Clinical Modification
Australian Medicines Terminology
Application
Programming
Interface
Agence
des
Systèmes
d’Information Partagés (de Santé)
Anatomical Therapeutic Chemical
(Classification System)
Consolidated CDA
Canadian Classification of Health
Interventions
Clinical Document Architecture
Clinical
Information
Building
Blocks [Netherlands]
Clinical Information Modeling
Initiative
ICN
ICNP
Country of Affiliation
Country of Treatment
MOF
MOH
MS
NCP
NCRS
NHS (UK)
NHS
NLMC
DCM
DHD
DICOM
Detailed Clinical Models
Dutch Hospital Data [Netherlands]
Digital
Imaging
and
COmmunications in Medicine
DMP
Dossier Médical Personnel (Now
renamed “ Dossier Médical
Partagé”) [France]
DOW
Description of Work
DRG
Diagnosis-Related Group
eCRTS
epSOS
Central
Reference
Terminology Server
EDQM
European Directorate for the
Quality of Medicines
eHGI
eHealth Governance Initiative
EHR
Electronic Health Record
epSOS
European Patients Smart Open
Services
ERN
European Reference Network
EU
European Union
FG
Focus Group
F-MDS-RD French national Minimum DataSet
for Rare Diseases [France]
FSE
Fascicolo Sanitario Elettronico
[Italy]
GP
General Practitioner
GUI
Graphical User Interface
HGVS
Human Genome Variation Society
HCP
Health Care Professional
HIS
HL7
HPO
ICD
Hospital Information System
Health Level 7
Human Phenotype Ontology
International Classification
of
Diseases
International Classification
of
Diseases for Oncology
International Classification
of
Functioning, Disability and Health
ICD-O
ICF
ICPC
ICT
ICRS
IHE
IHTSDO
LIS
LORD
MLDS
NPDi
NRC
OMIM
OWL
PBCL
PHR
PMSI
PS
R&D
RD
RF2
ROR
SCT
SDO
UCUM
UK
US
WGM
WHO
WHO-FIC
WP
XD-LAB
Page 7 of 176
International Council of Nurses
International Classification for
Nursing Practice
International Classification
of
Primary Care
Information and Communications
Technology
Individual Case Safety Report.
Integrating
the
Healthcare
Enterprise
International Health Terminology
Standards
Development
Organisation
Laboratory Information Systems
Linking Open data for Rare
Diseases
(IHTSDO) Membership License &
Distribution Service
Ministry of Finance
Ministry of Health
Member State
National Contact Point
NHS Care Records Service
National Health Service (UK)
National Health System
National Laboratory Medicine
Catalogue [UK]
National Program
for Data
collection
National Release Center
Online Mendelian Inheritance in
Man
Ontology Web Language
Pathology Bounded Code List
[UK]
Personal Health Record
Programme
Médicalisé
des
Systemes d'Information
Patient Summary
Research & Development
Rare Diseases
Release Format 2 (IHTSDO)
Regional Oncologic Registries
SNOMED CT
Standard
Development
Organisation
Unified Code for Units of Measure
United Kingdom
United States
Working Group Meeting
World Health Organization
WHO Family of International
Classifications
Work Package
Sharing Laboratory Reports [IHE
Profile]
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3
Appendix 1 - Case Study Assessment Template
Hereafter the template used for guiding the case study assessment. Compiling notes and
instruction are indicated in blue italic.
3.1
Case study description
Provide a description of the use case including what it in scope and out of scope; the
domains covered; …
3.2
Implementation Case XYZ.1
{For each Implementation case}
3.2.1
The Context
Type of Project: operation / pilot / feasibility study
Current status: completed / active / in progress / planned / under evaluation
Provide a description of the context of this implementation case. For example how the
general use case is specialized or it is interpreted in this implementation.
Please provide all the information that you deem are useful to better understand the
terminologies choices (e.g. different concepts might be selected if different interpretation of
what a Problem list should be are given).
3.2.2
Drivers for adoption
The deliverable D4.1 “Portfolio of (best) practices” has identified a set of possible Drivers for
investments in semantic interoperability; please indicate for each of them if and how the
identified driver applies to the described implementation case.
Better quality and safety of care to individual patients
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Driver
Is Applicable?
How it applies?
More
complete
coded
documentation.
Yes/No/Partially The increasing complexity of patient care requires the
content in the EHR to be unambiguous and
understandable to multiple care providers and
interpretable by computers, to be comprehensive and
to provide relevant and rich detail. Fine grained
terminology can therefore support more complete and
accurate coded clinical documentation, provided that
the user interfaces for selecting relevant terms are
friendly and avoid overloading the clinician with too
many choices or a complex system of navigating term
hierarchies. The ability for computers to interpret
coded EHR data is an important driver, since
clinicians have much experience of interpreting
handwritten and typed information that is in free text,
received from other care providers: terminology
systems bring little, if any, benefit for human
readability purposes. Computable uses of EHR data
include filtering and navigation of a large or complex
patient record, the generation of summary screens,
and the decision support and care pathway drivers
mentioned below. MS feedback has drawn attention
to the lack of rich enough terminology support for
nurse documentation, clinical processes, rare and
genetic diseases.
Better overview of
each
patient’s
information.
Yes/No/Partially Well-structured and coded information can enable
EHR systems to automatically generate patient
summaries and disease monitoring dashboards.
Without these tools it can be time consuming and
error prone for a clinician unfamiliar with a patient to
obtain the necessary overview. An EHR system could
also highlight to a clinician any previous occurrence of
an observation or finding they are just entering, or
another finding of relevance - for example to query
the EHR for previously recorded information about
pain or the use of analgesics, and generate a purpose
specific overview.
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Driver
Is Applicable?
Better records to
enable
decision
support.
Yes/No/Partially This seems to be one of the strongest direct patient
care drivers for enhancing the proportion of structured
and coded information in EHRs. Decision support has
a well-established evidence base for improving
patient safety and optimizing clinical outcomes, and
this need will increase as medicine becomes more
complex, the volume of clinical guidelines grows, and
healthcare professionals come under increasing time
and resource pressures. However its extent of use is
somewhat limited by the limited domains of the EHR
data over which algorithms can reason and provide
accurate advice to clinicians. A focus on enhancing
decision support not only acts as a potential driver for
the adoption or enhanced use of terminology
systems, it provides a basis for prioritization, since the
codes most important to adopt are those for which we
currently have decision support needs and
capabilities.
Support
the
adoption of point of
care evidence based
clinical guidelines
Yes/No/Partially Through care pathway systems that can interrogate
the EHR content for a given patient in order to
generate
alerts,
provide
prompts,
make
recommendations on the nature and timing of future
care activities and orchestrate multi-actor workflows.
(Note that electronic care pathways often make use of
decision support components, but may include
additional functions and make richer use of the coded
content of an EHR.)
Improved
safety
Yes/No/Partially It is an expected outcome from all of the above
drivers,
but
relies
primarily
upon
making
computational use of the coded data. It is important to
recognize that the patient safety value of scaling up
the level of semantically interoperable health data
relies upon the querying and retrieval of complete and
relevant information about an individual patient, to
present it directly to the clinician or indirectly via a
computed alert or recommendation. The level of
granularity of the terms and data structures used to
capture, store and exchange the EHR data must be
sufficient to support correct safety alerts, without too
many false positives or false negatives: for example
ATC codes seem not to be fine grained enough to
support prescribing safety algorithms. Unless natural
language processing (NLP) technologies are also
used, information that has not been coded will be
invisible to such computational processing, just as will
information in an unconnected EHR in another care
setting. Even with NLP one cannot rely upon all safety
critical events to be detected, nor to avoid a certain
rate of false positives. The safety of patient safety
alerts therefore hinges upon the completeness and
accuracy of the structured and coded EHR they can
access and analyze.
patient
How it applies?
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Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Yes/No/Partially Patient
care
increasingly
involves
multiple
professionals working in different care settings,
forming a kind of “just in time” virtual team for each
patient. Paper based communications between such
actors are a well-recognized point of failure leading to
suboptimal and sometimes unsafe care. Electronic
communications (such as electronic discharge
summaries) can be transferred faster, but the
bottleneck of staff time to compose such
documentation remains. However, smart rules for the
semi-automatic
generation
of
summary
communications can reduce that workload burden
and improve the quality and timeliness of shared care
communications.
Underpinning multiprofessional
collaboration.
Offering all relevant actors direct access to each
other's records is another approach. However without
the filtering and navigational support referred to
above, can easily leader overload, missing key facts
and therefore fail to improve continuity of care. Some
health systems and initiatives employ care
coordinators (case managers) to orchestrate care, but
this is expensive. Computable and semantically
interoperable EHR data can be leveraged to flag up
critical facts relevant to a particular multi-actor care
pathway, and can flag up issues in the management
of one condition that has bearing on another.
However, the realization of computable benefit from
shared EHRs relies upon the existence of
correspondingly computable care pathways, reminder
systems, alerts etc. as discussed above.
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Driver
Is Applicable?
How it applies?
Yes/No/Partially Studies have shown that patients value access to
structured and coded data within their EHRs,
sometimes simply to read their records but
increasingly wishing to take advantage of applications
and tools that can re-present their data more usefully
to aid understanding, generate charts and tables,
highlight trends, support education about their health
conditions, and enable patients to play active roles in
self-care.
At present few personal health record (PHR) systems
use the same international terminology systems as
might be used by healthcare professionals, and so the
reverse flow of PHR data into EHRs will not easily
permit that data to be co-processed alongside EHR
data. Recognizing, though, that health professionals
are not all comfortable with including patient
generated or provided data into their EHR, this
reverse flow might not be a strong decisioninfluencing driver. However, a national semantic
interoperability strategy may include incentives for the
PHR marketplace to align with that strategy.
Sharing EHRs with
patients.
Cost reduction (in the healthcare system)
Driver
Is Applicable?
How it applies?
Yes/No/Partially Healthcare activities are sometimes documented
multiple times, for example in a health record, a clinic
letter or discharge summary, a reimbursement claim,
Reduce
duplicate
a disease registry entry etc. For some of these the
data
capture
documentation might initially be paper and later
through
better
entered into a computer system, which is not only
interoperability
time consuming but misses out on any real time
benefit that system could provide the author (such as
validation checks, reminders, warnings).
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Driver
Is Applicable?
How it applies?
Yes/No/Partially The use of codes for reimbursement is generally
aimed at optimizing reimbursement, not at cost
reduction. The cost reduction element lies in reducing
the duplicate effort to code for clinical care in the EHR
and to code for reimbursement, quality monitoring and
public health purposes, using different terminology
systems. Reimbursement codes are generally more
Capture
reporting
coarse-grained than clinical documentation codes, so
and reimbursement
reimbursement can be derived from clinical coding,
codes at source, in a
but not the other direction. If such mappings are used,
more efficient way.
changes to a reimbursement framework can be
introduced at lower cost and with little or no disruption
to the majority of healthcare staff. However, it should
be noted that reimbursement systems usually contain
rules that have historically been linked to terminology
systems like ICD, and so these too would need to be
redefined.
Yes/No/Partially Most health systems presently use a mixture of
terminology systems, for reimbursements, hospital
activity monitoring, births and deaths, disease
registries, screening programs etc. Many of these
systems are maintained by each country, including
cross-mappings between them and to international
terminology systems such as ICD. Several countries
Consolidate
from
have expressed the interest in reducing this burden of
multiple
existing
developing and maintaining cross-mappings by using
terminologies.
SNOMED CT as a core reference terminology (i.e. as
a common mapping target or semantic broker), and
this being one of the reasons for opting for it. It is also
being considered as a terminology to replace some of
the national terminology system, thereby reducing
even further the cost of maintaining local
terminologies.
Optimising reimbursement
Driver
Is Applicable?
How it applies?
Optimising
reimbursement
Yes/No/Partially To use fine grained clinical data from the EHR as the
basis for generating more accurate activity and
outcomes data, to map into reimbursement claims.
(This may, on the one side, reduce the likelihood of
“up-coding”, where a more expensive interpretation of
a patient’s care is claimed for than is actually the
case. On the other side, it may improve the
completeness of claims since the requirement for
duplicate coding for claims as well as for clinical
documentation can result in missed claims.)
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Analysis (secondary) uses
Driver
Is Applicable?
How it applies?
Analysis
(secondary) uses
Yes/No/Partially Analytic uses of health data can be powerful drivers
for adopting a coherent semantic interoperability
approach, including focusing the uses of terminology.
In some examples such as population health
screening and disease registries, subject-level data
needs to be incorporated. In others it is the analysis
results that are needed, which might be derived
through pooling data extracts for central analysis or
by distributing the queries though a federated
network. However, they all require data from multiple
sources across the health ecosystem to be combined
and co-processed, and therefore to be semantically
interoperable.
On the one hand, health data can only be combined if
it is originally captured in a semantically consistent
way, or can be mapped to a common representation
for the analysis. In general, analysis use cases will
not deliver benefits until a high degree of coding
quality has been reached. This requires a significant
preparatory effort, i.e. a revolution in documentation
culture. This means that the capability to fulfil these
purposes in a better way through a new or alternative
terminology choice will depend upon the widespread
use of that terminology in the source data. On the
other hand, the data items needed for these purposes
can serve as the focus for prioritizing that terminology
adoption and accompanying efforts to improve data
quality in the capture of those data items.
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Cross-border information and knowledge sharing
Driver
Is Applicable?
How it applies?
Yes/No/Partially The principal driver for investments in semantic
interoperability at a European level, supported by EC
funding, has been the cross-border healthcare rights
of citizens. This has triggered projects, specifications,
standards and profiles that handle the cross-border
communication
of
patient
summaries
and
prescriptions, primarily to support unplanned care
There is now a momentum to extend these
specifications and services to support cross-border
planned care. Smaller scale clinical data sets might
also be useful to exchange across countries, such as
laboratory and radiology results, medical device
Cross-border
information
and
readings. In all of these cases semantically
knowledge sharing
interoperable data is required, and clearly requires
consistent use of information models, clinical models
and terminology value lists. At present some countries
are planning to map locally captured and stored EHR
data (in whatever structures and terms presently in
use) to the European interchange specifications.
Migrating the underlying EHR systems and
repositories to natively capture, store and process
patient summary data items in the formats of the
European patient summary guidelines would not
make sense if all other patient data are handled in the
existing ways.
Others Drivers
Please indicate if there are other drivers to be considered
Driver
3.2.3
How it applies?
Adoption and operational strategies
Please describe what have been the semantic interoperability strategies that this
implementation case relies on. Including for example:
1. which support services and infrastructure is will be provided and funded centrally
2. Organizational changes needed to enable the adoption.
3. Approach followed for implementation and terminology e.g. national program versus
narrow scoped pilot projects; full terminology adoption versus project scoped subsets;
and so on...
Describe what have been the selection process applied and which terminologies / value sets
has been selected at the end.
Please indicate which operational strategies have been chosen, including
1. The role played by the terminology (e.g. as a reference terminology; as a user interface
terminology.)
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2.
3.
4.
5.
6.
The Approach to subsets and language translation
The Approach to post-co-ordination
The clinical model development
Terminology version management and distribution
What has been done about legacy terminologies? (if any)
3.2.4
Other remarks
Please describe:





What are/have been - if any - the benefits and the challenges of using this solution.
Is the value set derived from a guideline? How EU collaboration could help in this
process…
What are /have been the development and maintenance costs (of this choice) if
known.
What are/have been - if any - the lessons learned; and if applicable, what did you do
differently and why …
What are - if any - the suggestions and/or the plan for the future (in term of process,
content choice…)
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4
Appendix 2 - Case Study Reports
This section provides detailed information about the (a) the selection criteria applied and (b)
the results of the case study assessment. For a general description of this task please refer
to the D1.3 body document.
4.1
Case studies selection process
As first step a list of possible candidate cases, based also on the Workshops, surveys and
other projects1 inputs, have been prepared:
1.
2.
3.
4.
5.
6.
7.
European Reference Network (ERN) registry for rare diseases.
National/Regional exchange of Laboratory test results - Lab procedures
National/Regional exchange of Laboratory orders - Lab procedures
Cross Borders exchange of Patient Summary - Problem List
National/Regional exchange of Patient Summary - Problem List
EU Registries : ERA-EDTA registry (Patients on Renal Replacement Therapy in Europe)
Cross Borders exchange of Patient Summary: Allergies (agents, reaction (manifestation
of), type of intolerance)
8. Cross Borders exchange of Patient Summary: Medication List
9. Cross Borders exchange of Patient Summary: (Surgical) Procedures
10. Cross Borders exchange of Patient Summary: Autonomy / invalidity
11. Cross Borders exchange of Patient Summary: Medical (implanted) device
12. Cross Borders exchange of Patient Summary: Social History (smoke, alcohol intake, diet
...)
13. Local decision support system - Medication and allergies
14. Clinical research, especially the querying of EHRs for clinical trial protocol feasibility
15. Indications (Disease, symptoms, procedure, concurrent conditions ) for Product
registration
16. Indications (Disease, symptoms, procedure, concurrent conditions ) for Case Safety
Reports (ICSRs)
A preliminary evaluation of the selected criteria against the above reported list has been
done. A summary is reported in the following table
Criteria for selection
Cases covering this criteria
Some cases should be in routine
use in healthcare
1. National/Regional exchange of Laboratory test results - Lab procedures
2. National/Regional exchange of Laboratory orders - Lab procedures
Doubts have been expressed on the fact that the Patient Summary could or
could not be considered a routine use.
Cases should cover both primary
and secondary (e.g. health
registries) cases
Primary : most of the identified cases
Cases should cover a range of
health specialties
The candidate cases cover different specialties. This criterion is substantially
covered when the other criteria are met.
1
Secondary: European Reference Network (ERN) for rare disease or EU
Registries : ERA-EDTA registry (Patients on Renal Replacement Therapy in
Europe)
E.g. Trillium Bridge; eStandards
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Criteria for selection
Cases covering this criteria
Cases should cover both “closed”
(i.e. well identifiable with defined
coded concepts) and “openended”
(i.e.
that
requires
compositional syntaxes and/or
free
text
for
being
fully
expressed),
e.g.
laboratory
medicine vs. anamnesis
Possible closed cases: 1. National/Regional exchange of Laboratory test
results - Lab procedures; 2. National/Regional exchange of Laboratory
orders - Lab procedures; 3. Cross Borders exchange of Patient Summary:
(Surgical) Procedures
Cases should cover different
levels of granularity, i.e. from
holistic to sub-specialized use
cases,
The Patient Summary related cases are the best representatives of generic
cases.
Cases should cover both common
and rare cases
The European Reference Network (ERN) registry for rare disease is the best
case for representing rare conditions.
Possible open-ended cases: 1. Cross Borders exchange of Patient Summary
- Problem List; 2. National/Regional exchange of Patient Summary - Problem
List
Specialized cases: ERN and ERA-EDTA are.
Patient Summary, Laboratory and Allergies cover the common cases.
Cases should cover different
jurisdictional
contexts
(e.g.
European
(cross-borders),
National, Regional...)
1. Cross Borders exchange of Patient Summary - Problem List
Cases
should
be
ranked
considering the potential impact
on EU eHealth policies (e.g.
highest
ranks
for
Patient
Summary,
ePrescription,
PARENT related cases….)
All the Patient Summary and the Registry related cases have impact on the
EU eHealth policies: X-border Patient Summary Use Case for CEF; the
European Reference Network (ERN) for rare disease is another example.
2. National/Regional exchange of Patient Summary - Problem List
A special focus should be however given to the patient summary problem list
and procedure cases considering that they have been explicitly mentioned
as a short term action in the Recommendation for the International Patient
Summary, coming from the Trillium Bridge Project [deliverable 5.2]: “Assess
the use of SNOMED CT to express clinical problems and procedures in the
International Patient Summary [R#1-R#5]
As result of this preliminary evaluation four case studies have been selected for assessment;
hereafter the top five ranked case studies:





Case 1 - Cross Border exchange of Patient Summary - Problem List
Case 2 - National exchange of Patient Summary - Problem List
Case 3 - National / Cross Border Registries for Rare Diseases [European Reference
Network (ERN)];
Case 4 - National / Regional exchange of Laboratory results - Laboratory procedures.
Case 5 - Cross Border exchange of Patient Summary - Procedures
The following table summarize how the 5 top-ranked cases fulfills the selected criteria
Criteria for selection
Some cases should be in
routine use in healthcare
Nat./Reg.
Lab
results
X-border
PS:
Problem
List

National
PS:
Problem
List
ERN rare
disease


X-border
PS:
Procedure
Case
study set
is ok?

Cases should cover both
primary and secondary (e.g.
health registries) cases
primary
primary
primary
secondary
primary

Cases should cover a range
of health specialties
Lab
Emergency
, Primary
Care
Primary
Care
Rare
diseases
Emergency
, Primary
Care

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Nat./Reg.
Lab
results
X-border
PS:
Problem
List
National
PS:
Problem
List
Cases should cover both
“closed” (i.e. well identifiable
with defined coded
concepts) and “open-ended”
(i.e. that requires
compositional syntaxes
and/or free text for being
fully expressed), e.g.
laboratory medicine vs.
anamnesis
Closed
Openended
Openended
Cases should cover different
levels of granularity, i.e. from
holistic to sub-specialized
use cases,
generic /
specialized
generic
generic
Common
Common
National/R
egional
Low
Criteria for selection
Cases should cover both
common and rare cases
Cases should cover different
jurisdictional contexts (e.g.
European (cross-borders),
National, Regional...)
Cases should be ranked
considering the potential
impact on EU eHealth
policies (e.g. highest ranks
for Patient Summary,
ePrescription, PARENT
related cases….)
X-border
PS:
Procedure
Case
study set
is ok?
Closed

specialized
generic

Common
Rare
common

CrossBorders
National/R
egional
EU wide;
National
CrossBorders

Very High
Low
Very High
Very High

ERN rare
disease
Even if medication related cases are been evaluated of extreme interest, those cases should
be re-evaluated after that the results of the OpenMedicine project have been published.
Indications (Disease, symptoms, procedure, concurrent conditions) for Product registration
and Case Safety Reports (ICSRs) have been retained for future consideration.
Note: during the assessment phase a new case study has been added for covering the NHS
Diagnostic Data Service implementation case initially thought to be part of the Lab Result
case. The reasons of this choice are described in the previous section.
4.2
4.2.1
Cross-border Exchange
Problem Lists
of
Patient
Summaries:
Case Study Description
This case study is based on the exchange of a Patient Summary between the country of
affiliation (CoA) of the Patient, where the clinician information of that patient are available,
and the country of treatment (CoT) use cases. The CoA is the “This is the country which
holds information about a patient, where the patient can be univocally identified and his or
her data may be accessed.” [epSOS glossary]. The country of treatment is the “country
where cross-border healthcare is provided when the patient is seeking care abroad. This
country is different from CoA.” At this level this use cases does not specify how the exchange
of such information can be accomplished.
With Patient Summary is usually indicated an excerpts of Electronic Health Records commonly a document - most frequently used for emergency or continuity of care. Several
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different approaches can be however found for such a kind of record with concrete different
scopes: emergency data; encounter report (including discharge summary); continuity of care
record; specialized clinical summaries, and so on…2. For the purpose of this definition we will
consider a high level definition as that done by the JIC3 “the minimum set of information
needed to assure healthcare coordination and the continuity of care”.
The case study is focused on the problem list domain, being in general considered one of the
essential sections of this minimum data set.4.
There are several different viewpoints about the content of a problem list: e.g. any conditions
to be noted (including for example pregnancy, allergies and procedures); illnesses and
diagnosis; and so on. For the scope of this description no assumptions are taken on this
subject, however is expected that for each implementation case reported the actual meaning
of the Patient Summary and the scope of the Problem List “domain” will be specified for
determining on which basis the selection process has been realized, and benefits and
challenges experienced.
4.2.2
The
European
(epSOS/EXPAND)
Cross-borders
exchange
of
PS
The Context
Type of Project: pilot (will become operative with the future Connecting the European Facility
program)
Current status: completed
epSOS is a large scale pilot co-funded by the European commission (EC) for 66
months (1st July 2008 - 30 June 2013) with 47 Beneficiaries from 21 EU
member countries and 3 non-EU members, consisting of national ministries of
health, competence centers, an industry consortium, and the Project
Management Team with the goal to design, build and evaluate a service
infrastructure that demonstrates cross-border interoperability between electronic health
record systems in Europe.
The primary purpose of the electronic Patient Summary in epSOS Large Scale Project is to
provide the Health Care Professional (HCP) with a dataset of key health information at the
point of care in order to be able to deliver safe patient care during unscheduled care as well
as planned care, having its maximal impact in unscheduled care. The PS is not the entire
medical record but the essential patient information needed so that assistance can be
provided5.
The epSOS Patient Summary is a “reduced set of patient’s data which would provide a
health professional with essential information needed primarily in case of unexpected or
unscheduled care (emergency, accident..): that means that the main purpose of the PS is the
unscheduled patient care, even if the planned care case (citizen movement, crossorganizational care path..) is not excluded6.
2
See for example the US Continuity of Care Document; the British Summary Care Record; The Italian Patient Summary
(Profilo Sanitario Sintetico); the European Patient Summary, and so on.
3
Joint Initiative Council for Global Health Informatics Standardization “A JIC Foundation and Scope Report for Patient
Summary
Standards
Set”
http://www.jointinitiativecouncil.org/news/JIC_Patient_Summary_Standard_SetFoundation%20_Scope_Report_20151008_v3_5.pdf
4
See for example the Trillium Bridge Key Recommendation as endorsed by JIC and HL7 International Council.
5
Final definition of functional service requirements - Patient Summary, D 3.2.2, version 0.6 29/10/2012
6
Final definition of functional service requirements - Patient Summary, D 3.2.2, version 0.6 29/10/2012, page 13.
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The Patient Summary contains the patients’ general information, the medical summary and
the medication summary; detailed or specialized information about the medical history;
clinical conditions or medication prescribed or dispensed is however out of scope (detailed
and complete data are usually contained in the Electronic Health Record).7
The epSOS patient summary is represented using the HL7 CDA R2 standard and may
include the following sections: Medication Summary, Allergies and Other Adverse Reactions,
Immunizations, History of Past Illness, Coded List of Surgeries, Active Problems, History
of Present Illness, Medical Devices Coded, Procedures and Interventions, Health
Maintenance Care Plan, Functional Status, Coded Social History, Pregnancy History, Coded
Vital Signs, Coded Results. The “list of current problem” (Active Problems) is part of essential
health information that is required from a clinical point of view to be sent to deliver safe
patient care. The List of Resolved, Closed or Inactive problems is instead part of the optional
information to be shared.
Resolved, Closed or Inactive problems are defined as the “problems or diagnosis not
included under the definition of ‘Current problems or diagnosis’. Example: hepatic cyst (the
patient has been treated with a hepatic cystectomy that solved the problem and therefore it´s
a closed problem)”
Current problems or diagnosis’ are the “Problems/diagnosis that fit under these conditions:
conditions that may have a chronic or relapsing course (e.g.: exacerbations of asthma,
irritable bowel syndrome), conditions for which the patient receives repeat medications (e.g.:
diabetes mellitus, hypertension) and conditions that are persistent and serious
contraindications for classes of medication (e.g.: dyspepsia, migraine and asthma)”
epSOS consider mainly two use cases for the Patient Summary service:


USE CASE 1: an occasional visitor in country of treatment, for example someone on
holiday or attending a business meeting. The distinguishing characteristic is that this type
of visit is irregular, infrequent, and may not be repeated. This is a type of incidental
encounter where the Health Care professional may have no previous record of the
person seeking care.
USE CASE 2: the person is a regular visitor to country of treatment, for example
someone who lives in one country but works in another country. The distinguishing
characteristic is that this type of visit is regular, frequent, and the person seeking care
may be accustomed to using services in the country where he or she works as a matter
of personal convenience. This is a type of occasional situation where the Health Care
professional may have some information available from previous encounters; therefore
the patient could have a medical record locally stored in country of treatment, and maybe
a PS in country of treatment plus in country of affiliation. If this is the case, both PSs
should be available for the HCP to be consulted.
These use cases are realized based on a network of National Contact Point Nodes (NCP)
interacting with a central terminology server for the purpose of accomplishing codes’
transcoding and terms’ translation to the exchanged documents. For the liability reasons the
original coded concepts and original and target designations are expected to be recorded in
the exchanged document after each transformation applied.
7
Guidelines on Minimum/Nonexhaustive Patient Summary Dataset for Electronic Exchange in accordance with the CrossBorder Directive 2011/24/EU http://ec.europa.eu/health/ehealth/docs/guidelines_patient_summary_en.pdf
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Drivers for adoption
Better quality and safety of care to individual patients
Driver
Is Applicable?
How it applies?
More
complete
coded
documentation.
Yes
The availability of national structured and coded
information is a prerequisite in epSOS for allowing the
cross-borders exchange and the translation of the
clinical contents.
The adoption of common reference clinical models
and terminology subsets goes in the direction of
reducing data element mapping ambiguities and limits
the unavoidable information losses due to
terminologies mapping.
Better overview of
each
patient’s
information.
Yes
Well-structured and coded information can enable
EHR systems to automatically generate patient
summaries that could be more easily remapped into
the common cross-border format.
Better records to
enable
decision
support.
No
The use of the Patient Summary coded data for
feeding decision support systems has not been a
piloted scenario in epSOS.
Support
the
adoption of point of
care evidence based
clinical guidelines
No
Not in scope
Improved
safety
Yes
This is one of the main drivers of the X-border Patient
Summary use case. Shortages have been however
experienced due to: (a) the non-availability of quality
structured and coded data at the national level ; (b)
the loss of information due to the mapping from local
terminologies (e.g. ICD9-CM) and the epSOS value
set based on ICD-10.
patient
Enriched EHR data exchange for continuity of care
Driver
Underpinning multiprofessional
collaboration.
Is Applicable?
How it applies?
Partially
Care coordination is not the main scope of epSOS;
however the capability of sharing essential patient
information in a cross-jurisdictional care process may
be intended as the simple form of multi-professional
collaboration.
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Driver
Is Applicable?
How it applies?
Partially
The patient access to the European Patient Summary
is one of the key scenarios considered in epSOS.
Is not however part of this scenario the import of such
information into a Personal Health Record, neither the
inclusion of Patient originated data in the Patient
Summary.
Sharing EHRs with
patients.
Note: the Trillium Bridge project, based on the epSOS
implementation, demonstrated the patient mediated
exchange scenario of the patient summary, that
potentially enable the import of Patient Summary data
into a PHR.
Cost reduction (in the healthcare system)
Driver
Is Applicable ?
How it applies ?
Reduce
duplicate
data capture through
better
interoperability
Partially
The reuse of exchanged data for avoiding duplicated
data capturing was not in the scope of epSOS,
however the availability of structured and coded data
may enable in the future such usage.
Capture
reporting
and reimbursement
codes at source, in a
more efficient way.
No
Yes
Consolidate
from
multiple
existing
terminologies.
Even if epSOS do not aim to impact on nationally
chosen terminologies, had as goal that of defining an
EU common ground to be used as reference for
facilitating the cross-countries data exchange.
For the problem list
represented by ICD 10.
this
common ground
is
Optimising reimbursement
Driver
Is Applicable ?
Optimising
reimbursement
No
How it applies ?
Analysis (secondary) uses
Driver
Is Applicable ?
How it applies ?
Analysis
(secondary) uses
No
Not in scope of epSOS
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Cross-border information and knowledge sharing
Driver
Is Applicable ?
How it applies ?
Cross-border
information
and
knowledge sharing
Yes
This is the main driver of epSOS, please refer to D4.1
- “Cross-border information and knowledge sharing “
driver for detailed assertions.
Adoption and operational strategies
Introduction
Note: the information included in this section is focused on the epSOS Patient Summary
implementation case and doesn’t presume to cover the global European strategy on
semantic interoperability.
The epSOS project tried to face some of the semantic interoperability challenges for the
cross-borders health data exchange adopting a focused scoped project approach: a limited
set of well specified use cases (the Patient Summary is one of them) were selected and the
related interoperability challenges (including organizational, legal and semantic aspects)
addressed.
One of the precepts of the epSOS strategy was that of avoiding imposing any kind of choice
at the National Level trying to reach a large countries consensus on the cross-borders
exchange rules. Another relevant aspect to be considered is that epSOS was a pilot project:
the Participating Nations‘ capability of actually implementing the agreed solutions has been
in fact a key factor in most of the choices (including for the semantic part).
For supporting the semantic infrastructure a central terminology service has been set up for
managing code systems, value set, translations and terminologies maps.
A general governance and management model was agreed, that has been substantially
replicated for the EXPAND project that had the goal of maintaining the epSOS assets before
the CEF. Summarizing, experts groups involving clinicians, pharmacist, modelers and
terminology experts in representation of countries where established (the Clinical and
Semantic Key Task (KT 1.4.10) in epSOS-II and the Semantic Maintenance Shop in
EXPAND). Those groups were in fact responsible for the submission to the epSOS Project
Steering Board (composed by representatives of the Ministries of Health of the Participating
Nations) for approval of consensus-based choices concerning information (conceptual,
logical and implementable) models and terminologies (code system selection, value sets
definition).
Even if sometime ignored it is worth to note the tight mutual interdependency between
terminologies and information models that should be taken in account in the general process.
Lacks in term of countries / expertise involvement, continuity of support, maturity of the
process has been experienced in the governance and management of the semantic assets,
this appear to be even more critical after the end of the EXPAND project.
Why SNOMED CT was not chosen as unique code system
An initial methodologic discussion was held in epSOS8 regarding the opportunity of selecting
a single code system representing all the needed information or a selection of code systems
should be preferred for supporting specific types of information. The only code system having
the needed potentiality for the first option was recognized to be SNOMED CT. The
discussion turned very fast out to be a political, organizational, procedural and economical
discussion, several participating nations were not in fact in the position to legally continue to
8
Extracted from the epSOS report: “The experience of selecting the code systems for the development of the epSOS Master
Value Catalogue (MVC)”
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use the content selected based on SNOMED CT after the project. No agreement was found
with IHTSDO for allowing participating nation could continue using their content after project
end. Furthermore, it was not adopted at the national level requiring for most of them to apply
mappings. It was thus agreed that SNOMED CT was not selected to represent the content
for all the information in all the documents, but that for each information type a suitable code
system should be identified according to agreed criteria.
The general Code system selection criteria
The code systems selection criteria9 applied in epSOS has been ordered here per priority:
Internationally Used: An international code system such as those released by ISO or WHO,
for example, has the advantage that it was elaborated by experts having vast experiences
with terminology implementation and application. The internationally used code systems
have implementation guidelines that are used at a national level, as well as maintenance
guidelines. The code system used in the epSOS Value Sets Catalogue must be
internationally recognized. The suitability should be evaluated by experts in the field, both
medical and non-medical.
In Use: The second most important criterion in selecting the code system is its use in the
MS. A survey is done among the experts working on the epSOS Value Sets Master
Catalogue in order to have an accurate representation of the code systems used in each
country.
Existence of translation in Different Languages: The existence of translation via version
in different languages is another key element to be evaluated, since it will dramatically
reduce the activity of translating the epSOS Value Sets Catalogue terms into the local
(national) language. If a code system exists in the local (national) version, it is likely that
existing translations have been already validated / certified and kept aligned when newer
versions are released.
Has a Maintenance Process: A code system that has an official maintenance process is
highly desirable. The release of new versions should be taken into account during deciding
process. The maintenance process should include specifications for distribution and support.
Existence of Transcoding Systems / Services: The existence of officially defined or at
least of consolidated systems / services to perform transcoding from one code system to
another one is a desirable element in order to reduce costs and risks. However it is known
that this is an important issue that most Standard Organization Bodies are struggling with,
and therefore much bigger than the epSOS perimeter. Nevertheless, whenever official
attempts exist to map one code system to another it is considered very useful as this
provides guidance for mapping.
Cost of licenses, implementation and maintenance: Although for research purposes most
of the code system licenses are provided for free, the cost might prove to be prohibitive. In
addition to the cost of the licenses, the cost of the implementation and maintenance need to
be considered.
The code system must be easily implementable: The code system must be easily
implementable based on a sound methodology which takes into account both the syntactic
and vocabulary aspects.
The general criteria for concepts selection
Based on these principles, additional criteria were identified for the concept selection:
Relevancy to scope documents: concepts must have clear relation to the specific domain
that they are representing and they should be used in its context.
9
From epSOS deliverable D3.5.2.
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Information sufficient for clinical decision: Health terminology is very complex and it
covers a large area of knowledge requiring lot of effort to organize part of this terminology for
specific purpose. It is hard to decide what level of detail should be used, especially when use
cases cannot be precisely specified. But having fundamental use case of HCP taking care
about citizen of foreign country (possibly in emergency situation) one should always think of
what information is really necessary to obtain about given conditions. Sometimes it is
necessary to know just presence or absence (e.g. patient was immunized against tetanus), in
other cases more specifying attributes are necessary (e.g. type of pace maker, date of last
examination, clinical course). These various levels of information and granularity were
addressed in the choosing the syntax and the value set that accompany the respective value
sets syntax . Each coded element was studied as a group, within the health care
professionals in the semantic group, resulting in the epSOS MVC (or the epSOS Reference
Terminology).
Information systems behind: the main purpose of epSOS was to enable the
communication between real information systems (e.g. NCP, national systems). The content
and representation had therefore to follow constraints given by their implementations semantic services and communication standards. Moreover, current local systems
introduced additional constraints to be taken in account.
Frequency of use: Even within one domain, delimited by scope documents, the number of
possible concepts may exceed realization possibilities.
Severity (Consequences): In contrary to previous criterion, or together with it, severity of
the information carried by concept has to be considered. If absence of a particular even very
sparse fact can lead to serious harm of patient’s health conditions it should be incorporated
even if some less important will have to be omitted.
Content evaluation and acceptance: The process of choosing concepts is quite demanding
and time consuming. However, it has to be executed properly and evaluation must not be
missing. The evaluation should run in parallel with ontology creation, because the extent of
the task is major. Evaluation should cover various levels from basic in working group
selecting concepts, to project representatives of HCP and medical specialists in all countries
involved. Syntactical and orthographical rules of each language have to be held.
Reconcilability: Special emphasis should be put on reconcilability of concept’s meaning
through chosen term. Generally, self-explanatory terms should be preferred. On international
level, higher priority should be given to terms incorporating Latin or Greek elements.
Non-ambiguity: Terms evocating ambiguity should be avoided. The meaning of the concept
should be as clearly understandable from the term as possible and what’s more for
professionals from all medical specialties.
Clinical acceptability: Similarly as by concept selection, following clinicians’ preferences is
crucial. Qualification and acceptance in practice plays a major role.
Consistency and systematic order: Decisions on which terms to choose, have to be
consistent within the framework of the whole terminological system. If it is decided to follow
some morphological or syntactical rules for a specific category of concepts, they have to be
applied to all terms from this category and all exceptions should be well justified.
The selection of terminology for the problem list
Based on the above mentioned criteria discussed three candidate code systems were
identified for the problem list: ICD-9, ICD-10 and SNOMED CT.
ICPC was used by Patient Record systems in some countries, but not largely used. Too
heavy translation and transcoded would have been needed. Hence it was excluded.
SNOMED CT was quickly rejected based on the licensing reasons discussed above.
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Considering that the large majority of the countries used ICD-10 (even if with different
versions and with or without national extensions) ICD-10 was selected considering the latest
version available at that time.
The awaiting mapping burden for the countries that still were using ICD-9 was a big
argument for minimizing the value set/data set as much as possible but of course without the
risk of introducing use cases couldn’t be supported. Discussions on the data reduction went
on if a limitation should be made to including only all 3-char codes from the ICD-10 or also to
include all 4-char codes. After a vote in the Semantic team the decision was made on making
an initial validation based on only the 3-char codes. The value set was created based on this
decision and validated in each participating country where clinicians were consulted to see if
their use cases were supported by the 3-char value set. In general it was accepted but some
single important 4-char codes missing were identified and added e.g. concept: 150.0
Congestive heart failure. It was also agreed to revise the decision when more experience
from the practical use could be gathered.
Based on the feedbacks collected during the pilot period about the need of increasing
granularity, it was finally decided to extend the used value set to the full ICD 10 code system
(‘category’) with the exclusion of those belonging to chapter XX. The code system version
has been updated to the 2015 version.
Operational strategies
Role
The terminologies in epSOS acted mainly as reference terminology, even if - in concrete - they were
also used as interface terminologies by the epSOS display tool.
Approach to subsets and language translation
See above
Approach to post-co-ordination
Not applicable.
The clinical model development
The first step has been the definition of a Data Set for the Patient Summary, developed by
subject matter experts (Clinicians and Pharmacist); this data set has been documented in
epSOS deliverable D3.2.210. This data set has inspired the EU Patient Summary Guideline.
Based on this agreed data set a HL7 CDA R2 based implementation has been developed,
and document, section and entry level templates defined. This implementation drove the
identification of the value sets that was included in the epSOS Master Value Catalogue.
Terminology version management and distribution
The management and distribution of terminologies was in charge of the semantic
maintenance teams. However, considering the epSOS pilot scope and therefore the wish of
minimizing changes in the used assets, there was not pro-active management of the new
code systems versions. Updates for the epSOS value sets were considered in fact only in
case of change proposals triggered by identified errors or omissions impacting on patient
safety.
Terminology distribution was realized by means of an epSOS Central Reference
Terminology Server (eCRTS) that could be accessed by a web GUI or using agreed API. The
eCRTS serves the two environments: the operation (http://ecrts.conet-services.de) and the
pre-production (http://ecrtsppt.conet-services.de)
10
Final definition of functional service requirements - Patient Summary, D 3.2.2, version 0.6 29/10/2012
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A more mature process should consider the realization of a European value set authority
responsible for the technical management of Value Sets: monitoring of the code systems
releases; value set updates; terminology distribution ;…).
Legacy terminologies
Not applicable in the cross-borders context.
Other remarks
Benefits:


Allowed the cross-country exchange of information about illnesses and diagnoses in
a multilinguistic context
Used by a (relative) majority of countries
Remarks:
 Some countries complained about the limited granularity of the value set (this
triggered the adoption of the full ICD-10)
 Concept mapping from locally used terminology often implies loss of information (no
equivalent concepts, missing maps,..)
Lessons learned:
 The usage of a terminology as mapping-broker could be a short / medium term
solution, but harmonization should be a long - term one. Harmonization includes
harmonization activities among SDOs enabling the development of affordable maps
and / or harmonization among the terminology choices made at the national level. A
similar consideration should be made also for information models.
 Terminology and information models cannot be seen as distinct aspects.
 There is a need of consolidating and creating committed entities (e.g. a value set
authority) for supporting the governance and the day-by-day management processes.
 It is vain to focus on cross-border data exchange formats (and related terminologies)
if the quality of data available at the national level is low. It has to be analyzed what
are the data captured by EHR system in use. Especially their capability of capturing
structured and coded information (as expected by epSOS)? Sensible progress has to
be done in this field.
4.3
4.3.1
National/Regional Exchange of Patient Summaries:
Problem Lists
Italy: the Fascicolo Sanitario Elettronico
The Context
Type of Project: operation
Current status: in progress (national Level) / Active (few regions)
The FSE (Fascicolo Sanitario Elettronico) is the Italian Electronic Health Record System
realized as a system of interoperable Regional EHR-systems for the purposes of prevention,
diagnosis, treatment and rehabilitation. It is supposed to allow the sharing among authorized
Health Professionals of a set of data and documents, enabling also the Patient Access to
that information. The FSE is a longitudinal EHR-S that covers the entire life of the patient and
it is continuously fed by the health professionals belonging to the National Health and Social
Services (NHSS) and the Regional Health and Social Services (RHSS), who take part in the
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patient’s care. The establishment of FSE has been regulated by law11 and a National and
Regional operational plan are under definition. Several regions (Lombardy, Tuscany, Emilia
Romagna…) have however consolidated regional EHR-S, allowing already the exchange of
Patient Summary, which will be the basis for the future Fascicolo Sanitario Elettronico. In an
initial phase a minimum set of data and document has been establish, among them the
Patient Summary is one of the document supposed to be shared through the FSE.
The scope of the Italian Patient Summary is to “help the continuity of care, allowing a quick
overview of a patient when a contact with the National Health System occurs: emergency;
hospital admission; visits; diagnostic services; continuity of care for groups of GPs…”. This
document is supposed to be generated as output of a clinical act of the GP responsible for
that patient, deriving the included information from his/her EHR-S.
The Italian Patient Summary is realized using a nationally12 defined template based on the
HL7 CDA R2 standard.
On the contrary of the epSOS specification the Italian Patient Summary includes only one
problem list section including closed and open problems (as it happens for the US C-CDA).
The concept of “problem” to be recorded in the problem list is quite wide and it includes
diseases, illnesses and conditions (e.g. missing organs; while pregnancy is not expected to
be recorded there).
Drivers for adoption
Better quality and safety of care to individual patients
Driver
Is Applicable ?
How it applies ?
More
complete
coded
documentation.
Yes
Even if it can be improved, the choice allows
implementing the exchange of coded information
about problems for the Patient Summary scope.
Better overview of
each
patient’s
information.
Yes
This was mainly the driver for the adoption of the
Patient Summary.
Better records to
enable
decision
support.
No (future)
Possible future extension, in that case a revision of
the choices made shall be considered.
Support
the
adoption of point of
care evidence based
clinical guidelines
No (future)
Possible future extension, in that case a revision of
the choices made shall be considered.
Improved
safety
Yes
Mainly for unscheduled care
patient
Enriched EHR data exchange for continuity of care
Driver
Is Applicable ?
How it applies ?
Underpinning multiprofessional
collaboration.
Yes
It is a baseline solution for allowing the sharing of
patient data among care providers.
Sharing EHRs with
Partially
Even if the FSE is designed for allowing the patient
11
12
See for example http://www.agid.gov.it/sites/default/files/linee_guida/fse_linee_guida_31032014_dpcm_dt.pdf
Regional specific CDA based templates are still in use at the regional level.
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Driver
Is Applicable ?
patients.
How it applies ?
access to his/her EHR, including the Patient
Summary. The patient summary is mainly conceived
for the HPs consultation.
Cost reduction (in the healthcare system)
Driver
Is Applicable ?
Reduce duplicate data capture through better interoperability
Yes
Capture reporting and reimbursement codes at source, in a
more efficient way.
No
Consolidate from multiple existing terminologies.
No
How it applies ?
Optimising reimbursement
Driver
Is Applicable ?
Optimising reimbursement
No
How it applies ?
Analysis (secondary) uses
Driver
Is Applicable ?
Analysis (secondary) uses
No
How it applies ?
Cross-border information and knowledge sharing
Driver
Is Applicable ?
How it applies ?
Cross-border
information
and
knowledge sharing
Yes
Italy - through Lombardy - has been involved since
the beginning in the epSOS project. That project has
been a reference for the development of the Italian
PS.
Adoption and operational strategies
As described above the Italian Health System is organized on a regional basis, according to
national policies and laws (e.g. defining the essential levels of care that each region shall
provide to citizens). The main governance role played by the central organizations (e.g. the
Minister of Health, the Minister of Finance) was such that most of the nationally defined
terminologies applied to the Healthcare were defined for statistical, monitoring and
reimbursement purposes (e.g. ICD-9-CM for DRG calculation and reimbursement purposes,
ICD-10 for some registries;..).
When the first structured document were therefore defined for the earliest national eHealth
pilot projects (e.g. “rete MMG” (GPs Network project) after 2005) the only terminology
officially recognized, distributed by the Ministry of Health, with official translations, and
transversally used among all the regions in the problem domain, was ICD-9-CM.
The official translation of ICD-9-CM is distributed by the ministry of health web site as excel
and pdf file.
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This code system is used for example not only for the patient summary, but also in other
contexts where coded data about diagnosis have to be provided (e.g. reason for prescribing),
with the exception of pharmacovigilance where MedDRA is used. When the patient summary
document was proposed, the adoption of ICPC was promoted, but since it was used only
within limited groups of GPs it was not considered at that time.
ICD-9-CM coding is usually made directly by the GP picking up the code from their EHR-S
GUI, mainly with a classification approach rather than for actually providing the clinical
description13. The “true” semantic is however conveyed in the Patient Summary, and in the
GP EHR-systems, by means of textual descriptions. Some GP EHR-Systems provides also
customized “extensions” to the ICD-9-CM code system for covering perceived missing
concepts, these are not however exchanged in the Patient Summary but usually used by the
GP or within groups of GPs that share the same EHR-system.
No issue with pre-existing terminologies or organizational changes was required by the
adoption of ICD-9-CM.
Other remarks
The main benefit of this solution has been that of enabling the usage of coded information,
across also multiple settings and for different scopes, minimizing the organizational impact
reusing existing assets.
Potential challenges are the fitness for purpose (granularity) and the reuse of data for
reasoning, even if, more than the specific code system to be used the main challenge seems
be to be the GPs disposition on providing structured and coded; there is not however any
official assessments giving evidence of that.
There is some initial though about moving from ICD-9-CM to an Italian version of ICD-10
(mappings from ICD-9 CM to ICD-10 have been used and tested during some pilots for DRG
calculation based on ICD 10 ) and around SNOMED CT (not limited to the problem list).
Lesson learned.



The terminology choice is driven by the terminology availability in that case driven by
administrative / monitoring purposes.
The absence of a national competence center and of a policy on semantic interoperability
has as direct consequence the adoption of the solution with minimal impact.
It would be interesting to investigate what is the impact of the terminologies chosen, and
of tools made available for using them, in the way clinicians use and perceive
terminologies (e.g. if a terminology is a classification is most likely that it will be used for
that scope and not for recording clinical statements..).
4.3.2
The Dutch Diagnosis Thesaurus project
This implementation case describes the Dutch Diagnosis Thesaurus project that provides an
interface terminology implemented in all hospital EHR’s for capturing problems (diagnosis)
and mapping capabilities with relevant international terminologies.
This project provides a terminology input for the realization of the Clinical Information
Building Blocks (CIBB) that should be the basic elements of patient information in the
Netherlands. These CIBBs should, support all care processes, and not only care processes
in the strict sense, but also secondary processes like Quality Registers, Reimbursement, etc.
These CIBBs are structured following the HL7 Detailed Clinical Models (DCM) methodology,
although not to every detail that is required in DCM.
13
It would be interesting to better analyze how much of this behavior depends on the type of terminology used, either on the
GPs attitude (or non-attitude) on using codes or others.
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The Context
Type of Project: Operation
Current status: Both completed and in progress
Dutch Hospital Data, an association of the Dutch Hospitals generated a problem list based
on existing list with problem (diagnosis). Per specialism, the existing lists were cleaned,
extended and mapped to ICD-10, DRG’s and SNOMED CT. The thesaurus is implemented
in all hospital EHR’s
Complex mappings could not be used as the EHR vendors are not capable of handling them.
Primary focus was/is on ICD-10 and DRG’s. In total the list comprises of more than 20 000
problems/diagnosis.
As of March 2016, 20% of the terms are validated SNOMED CT concepts. Ongoing work is
aimed to 99% coverage by Q3 2016..
The first version of the Diagnosis Thesaurus was released in July 2015 to help hospitals to
fulfill the regulation that they should ICD-10 codes
Drivers for adoption
Better quality and safety of care to individual patients
Driver
Is Applicable ?
How it applies ?
More
complete
coded
documentation.
Yes and no
It is more complete than ever, but it is still not
complete enough for the clinicians. Completing the
thesaurus with more relevant and granular content is
work in progress.
Better overview of
each
patient’s
information.
No
It only applies for reimbursement information. When
fully clinical relevant, the thesaurus will surely support
better clinical overview of the patient.
Better records to
enable
decision
support.
Now: Partially, See comments above
Soon: Yes
Support
the
adoption of point of
care evidence based
clinical guidelines
Now: Partially, See comments above
Soon: Yes
Improved
safety
Now: Partially, See comments above.
Soon: Yes
patient
Enriched EHR data exchange for continuity of care
Driver
Is Applicable ?
How it applies ?
Underpinning multiprofessional
collaboration.
Now: Partially, See previous comments
Soon: Yes
Sharing EHRs with
patients.
Now: Partially, See previous comments. In addition the SNOMED CT
Soon: Yes
NRC works with the national patient association to
have patient-friendly terms available in SNOMED CT
which than can be mapped to the diagnosis thesaurus
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Cost reduction (in the healthcare system)
Driver
Is Applicable ?
How it applies ?
Reduce
duplicate
data capture through
better
interoperability
Now:
No, See comments above
Soon: Yes
Capture
reporting
and reimbursement
codes at source, in a
more efficient way.
Yes
Consolidate
from
multiple
existing
terminologies.
Now: Partially, See comments above. Additionally, ICD-10 is mapped
Soon: Yes
to SNOMED CT .
DRG and ICD codes are captures at point of care
Optimising reimbursement
Driver
Is Applicable ?
How it applies ?
Optimising
reimbursement
Yes, but
The link between the (DRG) code and actual
diagnosis is more often than not strictly implemented.
Analysis (secondary) uses
Driver
Is Applicable ?
How it applies ?
Analysis
(secondary) uses
Now: Partially, The thesaurus does not cover all clinical relevant
Soon: Yes
terms yet. That is work in progress.
Cross-border information and knowledge sharing
Driver
Is Applicable ?
How it applies ?
Cross-border
information
and
knowledge sharing
Now: Partially, The Diagnoses thesaurus is definitely the source for
Soon: Yes
cross border exchange of problems and diagnoses. It
is the best there is and will become even more clinical
relevant.
Adoption and operational strategies
The Diagnosis Thesaurus is owned and maintained by the Dutch Hospital Data (DHD). DHD
is owned by two organizations: the Federation of University Medical Centers and the
Federation of General Hospitals.
It is free for use by member hospitals, thus covering 100% of the hospitals. Private clinics
have to pay a small fee to use the Diagnosis Thesaurus.
As the 1st driver for adoption was the use of DRG and ICD-10 codes, typically the Diagnosis
Thesaurus is implemented under supervision of the financial departments of the hospitals.
The DHD is in close contact with the SNOMED CT NRC and WHO-FIC for respectively
SNOMED CT and ICD-10 mappings. On a weekly basis change requests are processed by
the three parties.
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The thesaurus can be considered as an interface terminology. It includes both dereference
terms as synonyms and abbreviations.
The selection for terms is being done in close cooperation with the national representatives
of the medical societies. The final lists are mapped and incorporated in the national
SNOMED CT extension for the Netherlands.
In one case, Clinical Genetics, a large legacy terminology is fully incorporated in the
thesaurus (3500 concepts). It is not clear how this set will be represented in the Netherlands
SNOMED CT extension.
As the EHR vendors indicated that they cannot handle complex mappings or data capture
pre-coordination is used in many cases. Laterality is post-coordinated.
The Diagnosis Thesaurus is now the reference list with diagnosis for the Dutch hospitals and
used as reference in ongoing clinical model developments. For that and other reasons the
NRC is working hard to cover the diagnosis in the thesaurus with SNOMED CT concepts.
In the Netherlands we do not have a patient summary. We do have so-called Clinical
Building Blocks, a variant on Detailed Clinical Models. In the CBB’s the diagnosis thesaurus
is used as source for diagnoses/problems.
Other remarks
The great benefit is that we now have one interface terminology for the diagnosis for all
hospitals.in the Netherlands Although the first focus was on reimbursement/ICD-10 use we
think that the clinical relevance will increase substantially once covered by SNOMED CT
completely. The main challenge now is to make the thesaurus clinical relevant enough for the
physicians.
As we do not have a translated version of SNOMED CT parties like the DHD are obliged to
use the so called ‘Cherry picking’ method to assemble the subset per specialism. Translation
, relevant parts of , SNOMED CT is recommended if one wants to have a clinical consistent
set.
A guideline was used for the harmonization of the term (for example, the use of capital letters
and hyphens).
Plans for the future are to also include the non-DRG specialisms into the Diagnosis
thesaurus.
4.3.3
Sweden: the National Program for Data collection.
This case study description concerns the use of standard terminologies or classifications for
meeting the need to represent problems or diagnoses when reporting to Swedish national
quality registries.
The Context
Type of Project: operation
Current status: active / in progress
In Sweden there are approximately 100 quality registries collecting clinical data from
healthcare organizations. The completeness14 of reporting to the registries varies but for at
least some registries the completeness is above 90 %. For healthcare practitioners and
healthcare organizations this poses a major challenge in contributing the registries in a
resource-effective manner. While specialized care units may contribute to one registry only,
many units need to deal with the contribution to multiple, possibly overlapping, registries.
This leads to a situation where healthcare practitioners must register the same information
about the patient twice or more; once in the health record and once per quality registry.
14
Completeness is measured in relation to the diagnosis and procedure coding in the National patient registry.
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Further, the nature of variables varies both within and between registries. Some may well be
collected through reuse of data already in healthcare information systems, while often
variables require manual assessment and/or aggregation. Variables which are more easily
reused from existing sources include coded variables, i.e. variables where the allowed values
are constrained by some terminology subset.
A national project, the National Program for Data collection (NPDi), has set the goal to
decrease the amount of information that has to be registered multiple times by, among other
things, trying to get the registries to agree on information standards, including terminology
standards. The terminologies applied in this work include SNOMED CT as well as national
classifications, some of which are national versions of international classifications. In order to
reuse information as much as possible, the terminologies used in the information standards
should be the same as those used by healthcare delivery organizations. This in Sweden
means the national classifications or the laboratory medicine terminology NPU. When the
national classifications do not meet the needs, SNOMED CT is considered.
Part of the solution developed is to create a structured interface layer between the electronic
health record and the quality registers. This way health care providers can upload their
coded data which then may be reused across different quality registers. Also, the solution
includes setting of standards for coded contents of the health records.
Specifically, for reporting problems or diagnoses to the quality registries the Swedish version
of the ICD-10 has been the primary source. SNOMED CT has some benefits over ICD-10 for
representing problems and diagnoses, for example as SNOMED CT typically has a higher
granularity, and as ICD-10 is developed to be used as a classification and not a clinical
terminology. Still, as SNOMED CT is not widely implemented in Swedish healthcare, ICD-10
is the primary choice of problems and diagnoses terminology.
The “implementation” here refers to the total use of standardized terminologies for use in
reporting to quality registries, although there are many different registries.
Drivers for adoption
The drivers for adoption of terminologies for problems or diagnoses reporting can often not
be distinguished from the drivers for implementing standard terminologies for reporting in
general, as seen in the descriptions below.
Better quality and safety of care to individual patients
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Driver
Is Applicable?
How it applies?
More
complete
coded
documentation.
Partially
While not directly involved in setting standards for
documentation, by providing interfaces between the
care documentation and quality registers, an incentive
for adding structure to the health record is created.
While reporting to quality registers is facilitated if the
structures of the health record are designed in relation
to the quality registry interface standards, the project
aims do not include changing the way care providers
document the care given. Care documentation is and
will be primarily aimed at supporting delivery of high
quality care to the individual patient.
Better overview of
each
patient’s
information.
Partially
The aim of the implementation is to facilitate
secondary use of health data. However, for each
patient report, the contents of the report as well as
consent must be confirmed and signed by the
reporter. Thus, the complete set of information needs
to be available to the one providing consent and the
reporter.
Better records to
enable
decision
support.
Partially
Enabling decision support has been one of the drivers
in implementing quality registers before this project
started, even when reporting to quality register where
done on paper. For a long time and still today, quality
registers are among the few areas of structure in an
otherwise mainly free-text based, narrative health
record, thus being a natural starting point for decision
support.
Support
the
adoption of point of
care evidence based
clinical guidelines
No
Often, the quality registries aim both at collecting
quality data and at influencing care providers to be
more compliant with guidelines. As above, this has
not been a specific driver for implementation.
Possibly, the consequences might be the opposite.
Providing a uniform interface between the EHR and
the quality registries might limit the possibilities of
using registries as a vehicle for delivering guidelines.
Improved
safety
Partially
The implementation may indirectly improve patient
safety, through more complete quality registries and
better basis for healthcare quality analysis.
patient
Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Underpinning multiprofessional
collaboration.
Partially
By using standardized terminologies across health
domains and for different quality registries,
information provided by professions other than the
reporters may be reused.
Sharing EHRs with
patients.
Partially
Structured health information may facilitate presenting
information to the patient.
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Cost reduction (in the healthcare system)
Driver
Is Applicable?
How it applies?
Reduce
duplicate
data capture through
better
interoperability
Yes
This is the most important driver for implementation.
Although large costs are associated with duplicate
data capture, reduction of duplicate capture does not
only relate to cost reduction but also to relieving
health care staff from the burden of documenting the
same facts twice or more, and thus improving the
work situation for care professionals.
Capture
reporting
and reimbursement
codes at source, in a
more efficient way.
No
Consolidate
from
multiple
existing
terminologies.
No
Optimising reimbursement
Driver
Is Applicable?
Optimising
reimbursement
No
How it applies?
Analysis (secondary) uses
Driver
Is Applicable?
How it applies?
Analysis
(secondary) uses
Yes
The aim of the implementation is to support the quality
registries in facilitating reuse of information from the
electronic health record. By facilitating reporting to the
national registries, reducing the burden of reporting,
more information might be collected leading to
increased quality of analysis. Further, local users may
use structured data to perform local follow up.
Cross-border information and knowledge sharing
Driver
Is Applicable?
Cross-border
information
and
knowledge sharing
No
How it applies?
Adoption and operational strategies
A national project (NPDi) has been set up to both provide the necessary specifications, to set
up the national infrastructure, and to keep a dialog with healthcare organizations reporting to
registries as well as the different registries, all while coordinating with other national projects,
specifically within eHealth. The project includes a number of resources, for example an
informatics resource center and a national service (i.e. an IT service) for reporting to
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registries. Also, an infrastructure for long-term maintenance of the products developed
(mappings, bindings, information models, reference sets) is being developed.
A number of pilot projects working on how to facilitate reporting to quality registries through
use of eHealth standards have been performed during the 00ies up until today.
As the primary goal of the implementation is to reduce burden of duplicate data capture, the
primary criterion for selecting terminologies has been existing, wide-spread healthcare use.
When terminologies are in use already in health information systems, those are selected.
However, a large part of the variables in the quality registries are not currently captured in a
standardized manner and the standards had to be set by the project.
The terminologies used in the implementation were to a large extent bound to existing terms
used in the quality registries. Thus, the terminologies were used as reference terminologies
rather than interface terminologies.
Other remarks
A major benefit of the project and the approach has been the centralization of the hand-off of
information from care providers to the national quality registries. Care providers do not have
to make specific arrangements (protocols, formats, etc.) with each of the more than 100
national quality registries. Care providers are responsible for providing interpretable data and
aggregation, calculation, etc. happens on the national level.
Also, not only the health record needs an improved structure in order to allow facilitation of
quality registry reporting. The registries themselves have had to reconsider their information
structures and their use of coded information. For example, previously the registries did not
have to consider the joint impact of multiple registries reporting on the local health record
infrastructure.
4.4
4.4.1
ERNs Rare disease Registry
European Context
Rare diseases are a clinically heterogeneous group of about more than 6000 disorders and
in less than 1/2000 individuals in the EU. They are commonly diagnosed during childhood,
often inherited, and can have deleterious long-term effects. Although any one condition is
rare, their cumulative public health burden is substantial, with 6-8% of people having a rare
disease at some point during life.
Because of the rarity, no single institution, and in many cases no single country has sufficient
numbers of patients to do generalizable clinical and translational research. Geographic
spread of patients has been a major impediment to recruitment into clinical trials.
The EC has recommended that Member States should Consider supporting at all appropriate
levels, including the Community level, on the one hand, specific disease information
networks and, on the other hand, for epidemiological purposes, registries and databases,
whilst being aware of an independent governance. (Council Recommendation on an action in
the field of rare diseases (2009/C 151/02).
Patient registries and databases constitute key instruments to develop clinical research in the
field of rare diseases, to improve patient care and healthcare planning. They are the only
way to pool data in order to achieve a sufficient sample size for epidemiological and/or
clinical research. They are vital to assess the feasibility of clinical trials, to facilitate the
planning of appropriate clinical trials and to support the enrolment of patients as well as for
the post-marketing surveillance of orphan medicinal products. The creation of a registry can
be a powerful tool to create and structure networks of experts, whether they being European
Reference Networks of Centers of Expertise or national expert networks for RD. In either
case, the experts and centers of expertise involved are a primary source of data for
registries. Most rare diseases do not have a specific International Classification of Diseases
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code (ICD), which hampers research that uses existing care centered information systems
for re-use. To foster that problem, the European Commission issued recommendations to
improve codification of rare diseases in health information systems15.
A strategic objective of the European Commission is the creation of a European Platform
on Rare Diseases Registration providing common services and tools for the existing (and
future) rare diseases registries in the European Union and to facilitate the generation of
public health indicators through the codification of rare diseases as stated in the recent
European Joint Action for Rare Diseases (RD-ACTION16, 2015-2018).
4.4.2
Registries for rare diseases
General considerations
Registries are key ICT tools to generate knowledge about rare disease patients. Given the
low prevalence of most rare diseases or conditions, it is much likely that data from a large
number of hospitals will be required to generate sound knowledge depending on the purpose
of the registry.
A patient registry is an organized system that uses observational study methods to
collect uniform data (clinical and other) to evaluate specified outcomes for a
population defined by a particular disease, condition, or exposure, and serves one
or more predetermined scientific, clinical, or policy purposes. A registry database is
a file (or files) derived from the registry (Gliklich RE, Dreyer NA, eds. Registries for
Evaluating Patient Outcomes: A User’s Guide. 2nd ed. (AHRQ, September 2010)). It
is usual to distinguish between population-based registries, which refer to a
geographically defined population and aim to register all cases in that population,
and non-population-based registries based on clinical centres or other criteria
(members of a patient organization, participants registered via an ERN or other
disease-specific registry etc.) where the population coverage may not be
comprehensive. These types of registry have different uses but both are useful
provided they serve identified target aims. Both types of registry are the targets of
these recommendations. Multiple RD registries (>600) already exist in Europe
(Disease Registries in Europe, Orphanet Report Series, Rare Diseases Collection,
January 2013). The key principles proposed apply also to these existing datasets as
they adapt to the changing environment for registries in a European and
international context. The current recommendations for the basic principles
underlying RD registration should take as a starting point generally accepted
guidelines for registry development not revisited here (such as “Registries for
evaluation of patient outcomes: a user’s guide”, 2nd edition, AHRQ). - From
EUCERD CORE RECOMMENDATIONS ON RARE DISEASE PATIENT REGISTRATION
AND DATA COLLECTION
We can propose a classification of registry use as following:
15
16
http://ec.europa.eu/health/rare_diseases/docs/recommendation_coding_cegrd_en.pdf
http://www.rd-action.eu
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
Knowledge dissemination: distribution of information to patients and their clinicians on new
therapies, best practices, and safety issues

Patients’ recruitment: providing patient-population information for designing trial protocols
that optimize size and length of trials

Clinical epidemiology: population descriptive statistics, natural history of disorders, medical
practice variation

Clinical effectiveness: evaluation of the effects of preventive, diagnostic, and curative
interventions delivered in real-world settings

Safety monitoring: orphan drugs are generally not tested in large phase 3 studies, which
makes the need for post marketing safety surveillance via registries even more important
than with conventional drugs

Quality and outcomes improvement: enhancing patients’ outcomes by standardizing
practice and reducing practice variation

Genotype/phenotype association studies: the registry provides phenotypic data which can
be linked to genetic and other exposure data

Linkage to bio-specimens and bio-repositories: to detect phenotypic correlates of cell and
tissue biology
Unfortunately, given the low structuration of EHR data and the heterogeneity of ICT
solutions, data re-entry is the most common way of implementing such registries at large
scale. The high number of rare diseases and the heterogeneity of knowledge that might be
available make it difficult to build a generic approach or tool at EU level. Besides, given the
relatively low therapies (care) available for those diseases, healthcare professionals have
historically build local, national or European registries that might integrate generic care
management and research functionalities together with other requirements as cited above.
Albeit their adoption is still growing, electronic health records systems can offer rich and
sound longitudinal view upon patient disorder especially for long term conditions such as rare
diseases. The need to enable collection of data for RD patients at national or European level
is greatly growing. Whether this data collection is set within a population based registry or a
cohort instrument, interoperability between health information systems and these tools is
crucial. Rare disease patients have different follow up requirements within care. While many
still don’t have a genetic diagnostic, most have lifetime conditions that require specific
expertise and follow up. Given the small number of patient per disease, building a coherent
catalog of rare disease patients for research screening takes time as some rare disease
patients may be seen only once by the RD expert. The data pooling may then be stable
overtime and adapt itself to many local IT servicing situations.
Intended improved medical outcomes for RD for better data structuration for
EHR and for registries
Rare disease patients’ characterization is heterogeneous and may vary from a disease to the
other, a patient to the other. Capturing the right “diagnosis” or patient “state” cannot be easily
done with a single diagnostic terminology system as proposed in many re-use projects
(mainly ICD or LOINC based). The range of required information to group patients with the
same phenotype or genotype generally exceeds classical terminology systems used in
hospitals’ EHRs.
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To help in characterizing data structuration requirements for RD registry data collections, we
will divide the RD medical needs within the following framework: 1. Diagnosis, 2. Care
management and 3. Unplanned care.
1. Diagnosis
Being in position to get the right rare disease diagnosis for a given patient it still difficult.
Many patients are suffering from diagnosis delay (sometimes years). This issue is twofold. 1st
- it is due to the patient wandering within the care system before meeting with the right
physician within the correct rare disease expert center (in EU, many RD plans are actually
building specific national expert centers for RD patients given the specificity of medical
knowledge required to pose the RD diagnosis). 2nd - it might be due to genetic diagnosis not
being available, or even with the genetic test, the phenotype does not express or exactly
match with the genetic test, or the observed phenotype of genotype is still unknown.
Because rare diseases share the same clinical phenotype with more common diseases, it
could be difficult for the clinician to detect the rare disease. It could also be needed to get a
molecular diagnosis done or some other specific observations (images, other tests).
The requirement to structure data collected within the care setting for research depends on
the disease itself and the knowledge physicians (experts and non-experts) have about the
observations required to give a diagnosis.

If a genetic test is available, then the issue will be to detect more rapidly potential RD
for a given patient. Structured clinical phenotype could help in implementing a local
alert system for RDs...

If no genetic test is available, then the sharing of the observed phenotype with the
genotype of the patient might be required. It could be done for a specific database of
non-diagnosed cases for instance.

To understand the natural history of the disease, even if a genetic test is available,
the structuration of clinical data might be required so it could be easily shared within a
registry.
2. Care management
Care management in rare diseases can be compared to chronic disease care management
in the sense that they mostly are lifetime diseases. Depending on the severity of the
diseases and their phenotypic expression, RD care management could be relatively
complex. Few rare diseases have targeted drug therapies and when they have some drug
therapies (maybe not targeted) there is a crucial need to collect data to monitor the treatment
of the patient through certain period of time as orphan drugs are not tested in phase 3
studies because of the limited number of cases.
To measure clinical effectiveness of care given to rare disease patients, the structuration of
clinical data is also required so it could feed diseases specific registries.
Also, given the rarity of the experts, harmonizing care practices could also be needed and
therefore having means to share structured data is also a key enabler here.
3. Unplanned care
In many RD situations, guidelines and/or expert sharing is required. Orphanet17 is playing a
central role in sharing these guidelines but it might not be enough. Emergency guidelines18
for specific rare conditions may be crucial and many countries have various ways (more or
less successful) in dealing with it (RD physical card, etc.). Knowing the condition of the RD
patient within an unplanned care framework is crucial for delivering proper unplanned care.
The introduction of a coding system to document the patient condition would be a relatively
17
18
http://www.orpha.net
http://www.orpha.net/consor/cgi-bin/Disease_Emergency.php?lng=EN
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fast way to enhance this critical patient situation. Implementing such alert functions has to do
with local EHR implementation so it is out of scope of this case study.
Synthesis
These medical/scientific needs are summarized within figure 1 and pictured within the
European and local data management framework for rare diseases: depending on the actual
knowledge upon a patient condition or a treatment, research might be needed, hence that
research could be supported by an observational registry eventually supported by an
European registry through the future EU central RD registry from the EU Joint Research
Centre at Ispra, Italy.
Figure 1 - Care and research processes for rare diseases from national to European
19
infrastructure.
4.4.3
Case study
To enable the re-use of care data generated by expert centers for rare disease, the use of
standards within registries was recommended by the EUCERD joint action on rare
diseases20. The use of common data sets (or minimum data sets) is also recommended in
order to foster better interoperability between data collections of the same sub-domain or
cross-domains within the rare disease community.
Using a more robust terminology that could help in capturing patient phenotype through care
management systems such as EHRs is our first main use case in this deliverable. We will
19
20
Authors: Remy Choquet & Zoi Kolisti from the European taskforce for health data interoperability for rare diseases ERNs
http://www.eucerd.eu/wp-content/uploads/2013/06/EUCERD_Recommendations_RDRegistryDataCollection_adopted.pdf
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divide it into two sub use cases we will instantiate through a generic workflow management
of clinical data to be re-used within external longitudinal registries for rare diseases.
1. Detecting specific patients based on phenotype or genotype
2. Since registries might also be used for care follow-up within the rare disease
communities, the documentation of cases could also be done within these
integrated tools. The structuration of them using controlled terminologies and the
integration of data from EHR will be covered in a second use case.
4.4.4
Selecting (or detecting) RD patients from care setting (EHR)
to include into registries or cohorts: the French national
registry for rare diseases perspective
The Context
Type of Project: operation (upgrading to interoperability with EHR)
Current status: active / in progress
Identifying patients based on disease or phenotype characterization from clinical information
systems is an on-going research focus; whether to accelerate the selection of patients for
clinical research, to trigger alerts in a local setting or to facilitate epidemiological studies. To
facilitate RD patient identification within the hospital health information systems, the
European commission published a recommendation21 in 2015 to integrate a specific
codification system within HIS.
It is foreseen that due to the heterogeneity of the diseases manifestations and therefore care
management, the identification of these patients remains difficult, especially because of the
lack of representation of rare diseases within national coding systems such as ICD-9 or ICD10. Although the growing adoption of SNOMED-CT in the US22 and the UK, the identification
of all (and potentially the very rare ones) is still difficult to perform, especially when the
condition cannot be identified as a specific disease in a disease terminology system (rare
genetic conditions such as chromosomal anomalies). This variability in patient disorders
expression and the description precision required to describe a patient state for research
cannot be captured with a monolithic terminological system and should also cope with
variability in terminologies used in health information systems for patient phenotype or
genotype description requirements.
A recent trend observed is to build deep phenotyping algorithms through various data mining
methods in order to characterize patient phenotype. This methodology seems promising and
may be used at local level. It is although a complex method that could be set by data
scientists and local medical experts with a great knowledge of their local hospital
organization. Unfortunately, this method does not scale well at national level given the
plurality of health information system and local organization of care in hospitals. Besides, the
level of expertise required to describe a RD case combined to the low prevalence of patients
for each disease when the disease is known.
Various initiatives are now being introduced to facilitate the use of EHR data for patient
selection or for re-use of clinical data for research or public health. As an example, the IMI
EHR4CR European project23 set an EU framework to accelerate selection of patients for
clinical research. It enables the creation of selection of patient sharing some predefined comorbidities (ICD-9 or ICD-10) or lab results (LOINC) with compatible hospitals. At the
moment, no further patient rare disease; phenotype or genotype description is available.
21
http://ec.europa.eu/health/rare_diseases/docs/recommendation_coding_cegrd_en.pdf
http://ceur-ws.org/Vol-1327/icbo2014_paper_52.pdf
23
http://www.ehr4cr.eu
22
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Despite the lack of patient description, the cost-benefit of the EHR4CR platform is higher
compared to classic patient selection methods.
The integration of a minimum data set together with the right patient state characterization
terminologies was proposed in CEMARA at national level in France in 2007. From a
terminological perspective, the patient disorder is characterized using ORPHA codes and a
local phenotype terminology was used to describe specific dysmorphias for geneticists.
Some limitations were perceived in using only Orphanet though to classify RD patients.
ORPHA codes are organized using specific classifications per system or mechanism per rare
disease sub group, which could be considered as value-sets.
Rare disease patients’ characterization is heterogeneous and may vary from a disease to the
other, a patient to the other. Many patients still don’t have a diagnostic. Capturing the right
“diagnosis” or patient “state” cannot be easily done with a single diagnostic terminology
system as proposed in many re-use projects (ICD or LOINC based). The range of required
information to group patients with the same phenotype or genotype exceeds classical
terminology systems used in hospitals.
A specific multi-coding scheme that can adapt to many situations was proposed: i) the
patient diagnosis is carried through a genetic test, the phenotype is well known, a single
diagnosis is available, ii) the patient diagnosis is carried through a genetic test but the
phenotype does not exactly match, extra clinical phenotype can be specified, iii) a clinical
phenotype is described but no further genetic information is yet known. To cover these
situations, multiple terminologies are required:
1. ORPHA or SNOMED CT (once ORPHA codes are available within SNOMED CT) codes to
document the disease of the RD patient
2. HPO or SNOMED CT codes to document the phenotype of the patient (co-morbidities,
symptoms)
3. OMIM or HGVS or MUTNOMEN codes to document the genotype of the patient
In that particular use case, if a source EHR system is using SNOMED CT to document their
patient cases, then, given the recent memorandum of understanding between IHTSDO and
ORPHANET, the identification or RD patients for re-use will be higher compared to ICD and
less subject to biases due to reimbursement use of the ICD resource.
There are several attempts at EU level to implement a better documenting system to detect
RD patient within the care setting. The RD-ACTION EU joint action has set a specific WP5 to
help in achieving this task. As an example, the UK and the Belgium has chosen SNOMED
CT to complete this task, Germany, France and Italy have chosen ORPHA codes.
This implementation case is dealing with selecting RD patient from care setting from EHR
care management based data, whether the data is pre-structured or not. We will provide 2
implementation strategies:

Integrating or re-using pre-existing controlled terminologies to select RD patients

Perform text-mining upon discharge letters to select RD patients
Drivers for adoption
Adopting controlled vocabularies to enforce documentation of patient medical file can have
several benefits. Although the case implementation study is related to identifying RD patient
within the care setting by the integration of specific rare disease terminologies, in doing so,
we also promote several other uses within care setting we will precise in the following tables.
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Better quality and safety of care to individual patients
Driver
Is Applicable?
How it applies?
More
complete
coded
documentation.
Yes
Given the rarity of the experts in the rare disease field,
exchange of trustable and understandable information
about a rare disease patient is required in some
health settings. Besides, the complexity of rare
diseases is a key driver to better structure information
about the patient (phenotype, genotype) when the
structure data is relevant to initiate computer based
data interpretation (re-use for research, alerting within
care management, epidemiology).
Patient are followed through their lifetime for many
rare diseases, their care coordination being complex
in many situations hence many healthcare
professionals have initiated the structuration of
medical files specific for some rare diseases. The
multiple encounters for some rare diseases also calls
for better structuring data within its care journey.
Within the rare hemorrhagic field for instance,
knowing the actual treatment course when the patient
is seen in an unplanned care setting may be vital.
Better overview of
each
patient’s
information.
Yes
Well-structured and coded information can enable
EHR systems to automatically generate patient
summaries and disease monitoring dashboards.
Without these tools it can be time consuming and
error prone for a clinician unfamiliar with a patient to
obtain the necessary overview. An EHR system could
also highlight to a clinician any previous occurrence of
an observation or finding they are just entering, or
another finding of relevance - for example to query the
EHR for previously recorded information about pain or
the use of analgesics, and generate a purpose
specific overview.
Better records to
enable
decision
support.
Yes
To enable automatic alerts or decision support tools
within a hospital setting, structured data and
terminological services may be required. Detecting a
rare disease patient to reduce time to diagnosis could
be implemented. This could be made possible using
phenotype comparison between the patient and
others patients within the EHR or by using semantic
resources such as cross linked phenotype to disease
resources (HPO to Orphanet).
For some rare diseases, specific alerts could be
implemented to avoid wrong drug prescription.
Support
the
adoption of point of
care evidence based
clinical guidelines
Yes
Given the rarity and the complexity of the rare
diseases, evidence based clinical guidelines are
generated on a routinely basis by health care
professionals to be shared amongst experts through
the scientific literature.
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Improved
safety
patient
Yes
As stated, reducing time to diagnose and collecting
proofs for some patient treatment are key drivers
within the rare disease field. To improve patient
safety, coded data (given the low number of patient) is
crucial. Rare diseases being often very much
specialized, common terminologies may not cover the
required codes to identify RD patients and to state
specific phenotypes. It is therefore important to be
able to use specialized, yet, cured terminological
systems for RD field.
Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Underpinning multiprofessional
collaboration.
Partially
Patient
care
increasingly
involves
multiple
professionals working in different care settings,
forming a kind of “just in time” virtual team for each
patient. RD registries might be used as medical
records hubs between networks of professionals due
to the lack of communication tools between hospitals.
There might be many situations upon which cross
hospital cooperation for RD patient care is required
and multi-professional collaboration. As in France and
in future ERNs, care networks for group of rare
diseases might be established and the patient might
be followed by several health professionals in link with
the patient expert of the rare disease.
Sharing EHRs with
patients.
Yes
Rare disease patients are generally pro-active in
terms of participation to research protocols or
research databases. They have been sensitized to
privacy concerns and are willing to share their data if
transparency is provided. Since their care data could
be valuable to be shared.
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Cost reduction (in the healthcare system)
Driver
Is Applicable?
How it applies?
Reduce
Yes
duplicate
data
capture through
better
interoperability
Healthcare activities are documented multiple times,
for example in a health record, a clinic letter or
discharge summary, a reimbursement claim, a
disease registry entry etc. For some of these the
documentation might initially be paper and later
entered into a computer system, which is not only
time consuming but misses out on any real time
benefit that system could provide the author (such
as validation checks, reminders, warnings).
Capture
Yes
reporting
and
reimbursement
codes at source,
in
a
more
efficient way.
Rare diseases are often complex, generating higher
costs to diagnose or take in charge patients. Extra
funding to hospitals may be covered by public or
private insurance system, eventually through DRG
systems but not for all rare diseases given the lack
of ICD codes for RD conditions. More granular
documentation of cases could help in generating
effective costing for taking RD patients in charge.
Consolidate
Maybe
from
multiple
existing
terminologies.
Given the large landscape of rare diseases
phenotypes and or genotypes, several terminology
systems are often needed and often lacking of
required terms to characterize RD patients.
Analysis (secondary) uses
Driver
Is Applicable?
How it applies?
Analysis
(secondary)
uses
Yes
Drivers are here presented in the first section of this
document.
Cross-border information and knowledge sharing
Driver
Is Applicable?
Cross-border
Yes
information and
knowledge
sharing
How it applies?
Also described in this document.
Adoption and operational strategies
Integration of a new coding system to enable RD patient selection in France
The implementation strategy of the national data base for rare diseases (representing a
national registry for all rare diseases) through the CEMARA model was to implement a
central application to code rare disease patient whenever they were seen by expert centers
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in France. This implementation is made within the framework of the 2nd national plan for rare
diseases.
Implementation of a national minimum data collection for all rare diseases in France
The 2nd French National Rare Disease Plan highlighted the necessity for better care
coordination and epidemiology for rare diseases. A clinical data standard for normalization
and exchange of rare disease patient data was proposed. The original methodology used to
build the French national minimum dataset (F-MDS-RD) common to the 131 expert rare
disease centers was published24.
To encourage a consensus at a national level for homogeneous data collection at the point of
care for rare disease patients, 4 national expert groups were identified. The scientific
literature for rare disease common data elements (DE) was reviewed in order to build the first
version of the F-MDS-RD. The French rare disease expert centers validated the DEs. The
resulting F-MDS-RD was reviewed and approved by the National Plan Strategic Committee.
It was then represented in an HL7 electronic format to maximize interoperability with EHRs.
The F-MDS-RD is composed of 58 data elements in 6 categories: patient, family history,
encounter, condition, medication, and questionnaire. It is HL7 compatible and can use
various ontologies for diagnosis or sign encoding. The F-MDS-RD was aligned with other
CDE initiatives for rare diseases thus facilitating potential interconnections between RD
registries.
This minimum data set to be collected was approved by the French Ministry of Health and
promoted nationally by regulation. It embeds some medical and non-medical terminologies
and was proposed in a FHIR compatible format to maximize interoperability with EHRs.
Implementation of a national terminology service
Along with a consensual data collection set of items, medical terminologies were proposed.
One major barrier to the implementation of new coding systems is the lack of consolidation of
such information scattered in different classifications such as Orphanet, OMIM or HPO both
from a technical point of view and end user point of view.
To help clinicians with this task, a specific coding application LORD (Linking Open data for
Rare Diseases - http://enlord.bndmr.fr) was built with a backend semantic database acting as
a terminology server and a web application to help clinician finding codes. The application
offers an integrated view of 6000 rare diseases (disorders) entities linked to more than 14
500 signs and 3 270 genes. The application provides a browsing feature to navigate through
the relationships between diseases, signs and genes, and some Application Programming
Interfaces to help its integration in health information systems in routine (see unterhalb).
24
http://www.ncbi.nlm.nih.gov/pubmed/25038198
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Figure 2 - The LORD overall biomedical data architecture of the terminology service developed
The integrated data can be browsed in an openly available web application for all expert
centers. When users are navigating through diseases graphs, they can filter the displayed
concepts.
For
example,
while
looking
at
Cystinosis
information
(http://enlord.bndmr.fr/#disorders/213/97966), the user can filter on rare eye diseases (if the
user is an Ophthalmologist) and then navigate through symptoms that are related to his
medical expertise: Unclassified maculopathy, metabolic disease with corneal opacity or
metabolic disease with pigmentary retinisis. The user then can have access to textual
information from OMIM and HPO for a given disease and epidemiological information from
Orphanet. As relations between data sources can be one to many (1 Orphanet disease for n
OMIM entries) then we have developed an OMIM entry selector to help user navigation and
data retrieval. From the web service standpoint, all data of all OMIM entries are gathered in
the same JSON object for an individual Orphanet disease.
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Figure 3 - The disease interface of the LORD application.
25
While Orphanet nomenclature (Orpha Codes) was used in CEMARA and recommended by
the EU in 2014, the nomenclature is large and we were recently reported that it is not easy to
manage and therefore guarantee a homogeneous codification across the national expert
centers. A dedicated expert group was then appointed by the French ministry of health in
October 2014 to evaluate the fit of the proposed resource based on the CEMARA experience
and medical experts’ needs. The conclusions of the group were delivered to the French
ministry of health. The main recommendations consisted in phasing the rollout of Orpha
Codes together with expert centers that will define the appropriate granularity and lists of
codes, the coding instructions and propose an exploitation plan for their data in the BNDMR.
It was also foreseen by experts in RD centers that double-coding (together with ICD) is a
blocking task to implement any other terminology within their care setting and that
terminologies that are describing genetic based diseases are evolving rapidly nowadays.
Since the rare disease should be only coded once, the burden of double-coding is reduced.
Also, to reduce that burden, the national college of medical information physicians is
proposing to propose transcodes from ORPHA to ICD at a national level.
Integration of the data collection within the care setting of RD expert’s centers
In order to reduce the burden of data multiple entries in information systems (hospital based,
national registries, disease specific registries, bio-banks, etc.) the national strategy adopted
was to incorporate the data collection within the hospital EHRs as specific data collection
targeted for all rare disease patients seen within expert centers. To accomplish that
integration, the ASIP Santé (National Agency for e-health) is conducting a national study first
25
The filtering view gives access to filters based on medical specialties. The graphical tree navigation enables navigation
through diseases, symptoms and group of diseases. The external thesaurus links allow the user to be redirected to source
sites pages of diagnosis. The disease content view represents disease definition data from Orphanet, signs from HPO and
clinical synopsis and genetic data from OMIM.
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to evaluate the best implementation way. The strategy is then to enhance the national
interoperability framework setup for care management purpose for the national medical file
system (DMP). This strategy should provide EHR vendors and clinical genetic vendors to
adapt their data collections tools.
Implementation of a’ i2b2-like’ national service to query the national repository
Once the data is collected, it is anonymized and integrated at national level. Various services
are then proposed such as:



Multi-centric studies for epidemiology purpose
RD Patient selection for registries or cohorts or clinical trials
National studies for care pathway analysis and equity or access to care facilities
Within the frame of this case study, RD patient selection can be made on various data
incorporated within the national minimum dataset for rare disease. For example, for medical
data:





Patient rare disease diagnosis (using ORPHA codes)
Diagnosis assertion
Patient phenotype (depending on the willing of the RD care network) (using HPO or
ICD co-morbidities)
Patient genotype (depending on the willing of the RD care network) (using HGVS or
a specific chromosomal anomaly descriptor)
Patient RD diagnosis family history (when family members could be diagnosed)
Those data are then made accessible through a query interface to authorized users. A count
upon feature selection per reference center is proposed to the user. The user then can
contact the reference center to setup the research protocol and enroll patients and eventually
re-use data from EHR.
Post-coordinated selection of RD patients from discharge records
The integration of specific codes to detect rare disease patients is not always possible and
can be seen as an expensive task at large scale. Another possible solution could be to mine
care generated data such as discharge records from EHRs. The main encountered problem
here would be to rely on the precision/recall of text mining techniques using terminologies
(ORPHA) to recognize eventual rare disease terms. That strategy, although generating less
work for the physician, could provide good results to find RD patients; unfortunately it is most
likely that it could not be implemented at a national or European scale since it would grant
access to all medical files of all patients at national level, resulting in major security and
confidentiality issues. From this perspective, coding and structuring data at source enables
selective and secure sharing of data at wide scale. Last but not least, discharge letters fit well
within a care process, but may lack from important data for epidemiology or further research.
Other remarks
As at today, the French experience (through the collection of data in a specific web
application: CEMARA) to facilitate the identification or RD patient within the general care
network and tools through the use of controlled terminologies enables have enable the
publication of 119 publications done by RD center researcher and the start of 82 research
specific projects.
The integration of interoperability within the project in order to achieve data collection at point
of care is promising. It is although a very long process that requires the adherence of all
actors and stakeholders to the project (ministries, hospital management, physicians, and IT
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specialists). The estimated cost if integrating a specific dataset and controlled terminologies
within EHRs is estimated between 2 and 3 million euros as a setup budget, it includes
interoperability framework setup, the free cost of terminologies chosen, local studies, central
technical tools, vendor data collection adaptation and deployment, interoperability
deployment and project management. The maintenance costs are estimated at 0.5 million
euro per annum including local updates in hospitals.
To enable such rollout, the regulatory stick together the usefulness fitness is also required. It
is important to remember that the rollout in more than 40 hospitals together with the data
collection process could be completed within few years.
4.5
4.5.1
National/Regional
Results
Exchange
of
Lab
Procedures/
The Laboratory Reports in the French “Dossier Médical
Personnel (DMP)”
The Context
Type of Project: operation
Current status: active (the exchange of lab results via DMP is already active; there are
however terminology related activities still on-going)
France has adopted a national interoperability framework since 2009, this framework was
aiming to share health information for improving the coordination of care, and this has been
implemented through the national EHR/PHR: the Dossier Médical Personnel.
The «Dossier Médical Personnel26 (DMP) » is an electronic health record accessible via
Internet that enables health professionals, who support the patient, to share useful health
information to coordinate patient care. DMP can be created during a medical consultation or
upon admission to a healthcare facility. The DMP can be accessed by the patient and by
authorized health professionals.
The DMP is a national document registry/repository based system that allows sharing
different types of medical information, like: medical history, laboratory test results, imaging
reports, treatments data. The system is operational since mid-2011, there are currently 574
020 patient records created27, with some millions of CDA documents stored, and about 150
health IT products have their DMP interface approved and are deployed in care settings.
The uptake is very slow, as well as the adoption by care providers; as of mid-2016 the
National Health Insurance body will be in charge of the project and this will likely speed up
the overall process.
The DMP is based for the large majority on IHE integration profiles with French adaptations
either for the exchange services (XDS/XUA…), either for the content (e.g. IHE LAB (now
PALM), PCC...).
A conformity assessment scheme has been also set up for assessing the technical
compatibility of IT health systems with the DMP requirements. Started on 2011 and still ongoing, it has stimulated vendors to have their product conformant with those specifications
(150 software products tested and approved).
26
27
Now renamed “partagé”
http://www.dmp.gouv.fr/
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The implementation case here described is focused on the sharing of laboratory test results.
The main use case for the sharing of lab reports is the exchange of data between Laboratory
Information Systems (LIS), the DMP and the local EHR systems. Secondary use cases have
not been yet implemented: however public health should be able to extract atomic data (entry
level information) from the published lab reports for their purpose, for example the solution
will allow the Institut de Veille Sanitaire (InVS) to extract those kinds of data for tracking
infections.
Drivers for adoption
Better quality and safety of care to individual patients
Driver
Is Applicable?
More
complete
coded
documentation.
Better overview of
each
patient’s
information.
Better records to
enable
decision
support.
Support
the
adoption of point of
care evidence based
clinical guidelines
Improved
safety
Yes
Yes
Yes
How it applies?
Textual data are enriched with structured and coded
information (CDA L3) in order to allow the import of
fine grained data into the health providers EHR
systems.
See above
The adoption of a common and well recognized
structure (CDA profiled in conformance with XD-LAB)
and agreed value sets, will allow the import of those
data into the EHR-Ss to enable a better decision
support
Not yet
patient
Yes
The scope of the DMP is to better support and
coordinate patient care therefore improving the patient
safety.
Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Underpinning multiprofessional
collaboration.
Yes
Patient care coordination and multi-professional
sharing of information are ones the main goals of the
DMP
Sharing EHRs with
patients.
Yes
The DMP has bene conceived to be accessed by
Patients
Cost reduction (in the healthcare system)
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Driver
Reduce
duplicate
data capture through
better
interoperability
Capture
reporting
and reimbursement
codes at source, in a
more efficient way.
Consolidate
from
multiple
existing
terminologies.
Is Applicable?
How it applies?
Yes
The adoption of a common and well recognized
structure (CDA profiled in conformance with XDSLAB) and agreed value sets, facilitate the import and
the reuse of the shared data reducing the need of
duplicate data capturing.
No
Maybe in the future. It is however interesting to link
care
coordination
with
better
control
of
reimbursements.
Yes
Legacy vocabularies have been replaced with the
mandated ones. Mapping from the old national
classification (used for the billing of lab tests) to
LOINC have been done to facilitate the integration of
LOINC in the existing LISs.
Optimising reimbursement
Driver
Optimising
reimbursement
Is Applicable?
No
How it applies?
Maybe in the future.
Analysis (secondary) uses
Driver
Analysis
(secondary) uses
Is Applicable?
Yes (in the
future)
How it applies?
Secondary use cases have not been yet
implemented: however public health should be able to
extract atomic data (entry level information) from the
published lab reports for their purpose, for example
the solution will allow the Institut de Vielle sanitaire
(InVS) to get those kinds of data for tracking
infections.
Cross-border information and knowledge sharing
Driver
Cross-border
information
and
knowledge sharing
Is Applicable?
Yes
How it applies?
France has been one of the Participating Nations to
epSOS and it is candidate for the CEF call. The DMP
will be the major healthcare data source for French
citizens going abroad.
One of the stronger drivers for adopting international
Code Systems.
Adoption and operational strategies
On 2014, after having identified the priority areas with the involvement of the main health
actors, the French Minister of Health and the Délégation à la Stratégie des Systèmes
d’Information de Santé (DSSIS) agency, committed ASIP Santé to make a study on
reference terminologies taking in account several dimensions (e.g. governance,
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implementation, use) considering this a priority within the scope of the semantic
interoperability.
This work has been planned in three phases (1) a background analysis including basic
notions, terminology resource requirements, inventory of the reference terminologies
available for the health and social sector. (2) The analysis of the needs and usages of
terminologies realized involving vendors, professionals and other French and international
stakeholders (3) Propositions, that aims to present the scenarios for the governance of
terminologies in France. All three phases have been completed. The results of the two first
phases are available for public comment since May 201528. The 3rd phase was completed on
February 1st, and concluded in favor of the setting up of national governance for semantic
resources for health and social care in France, and in favor of adding two terminologies to
the existing framework for healthcare: SNOMED CT and ICPC-2. The report of this phase 3
is not published yet.
The main aspects identified by the first phase have been the enforcement of the concept of
semantic interoperability as key factor for interoperability; the determination of the bricks for
the semantic interoperability: information models; coded concepts; value set (and vocabulary
bindings); code systems; mappings (associations); availability of standardized terminology
services.
The analysis of the needs and the survey about the usage of terminologies has been
therefore realized by ASIP Santé involving using different means (e.g. meetings, interviews):



Vendors present in the Health and Social ICT sector in France
Representatives from Institutions, researchers and users in France,
International Organizations working with terminologies
A large consensus on the study conclusions has been reached above all from the vendors;
no several comments were received from the health care providers.
The analysis has pointed out:


the multitude of terminologies that insists on the health and social sector, even when
a single domain is considered;
The fact that each terminology is conceived for satisfying a specific set of use cases
and scopes, when used outside those purposes the terminology loses relevance and
efficiency.
Selection criteria for terminologies have been defined, in line with the criteria defined by the
article 8 of the «Guidelines on Minimum / Non-exhaustive Patient Summary Dataset for
electronic exchange in accordance with the Cross-Border Directive 2011/24/EU »





Fitness for purpose for the considered use case
Long term sustainability and scalability
International standard
Multilingualism and native support for synonyms in each language
Costs / benefits ratio
The analysis determined the following information needs about terminologies (concept
domains) for the laboratory reports:
1. The classifications of the documents (lab report, patient summary…) and of their
sections (problem list, coded results...);
2. the identification of the requested / performed exams;
3. the type of observations (weight, temperature; blood pressure; …);
28
http://esante.gouv.fr/actus/interoperabilite/publication-du-rapport-de-la-phase-2-diagnostic-dans-la-cadre-de-l-etude-sur
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4. Qualitative results for observations (e.g. blood group, serology of the HIV or of the
hepatitis C, allergen identification, identification of infectious agent, histological type
of tissue injury, bone fracture morphology ;…)
5. unit of measure for expressing quantitative (numeric) results for observations
6. unit of measure for daily dosages, volumes of solution in drugs, weight masses of
active base of medications
LOINC has been identified as the most appropriate solution for covering the first three
elements.
For qualitative results it was identified that it was needed a medical terminology having (a) a
large coverage in different fields; (b) with an enough high granularity and (c) that assures a
maintenance process that guarantee the continuous alignment with the current medical
knowledge. Considering those criteria SNOMED CT seems to be the most appropriate
solution. One of its use cases is structuring bacteriology mycology and parasitology results,
and characterizing the resistance mechanisms. Another use case is securing the eprescription of medicinal products, by controlling interactions.
A French specific aspect to be considered about SNOMED is the fact that the rights for a
French translation of SNOMED International V 3.5 have been acquired in the past, and are
currently owned by ASIP Santé. However considering several dimensions (International
Standard; Lifetime and evolution; management of synonyms and relationships; availability of
French Translations; License of use) the final proposal has been to acquire the license of use
of SNOMED CT in France.
If the indications of the task force are followed, hopefully, France will become a member of
IHTSDO on 2017.
For units of measure UCUM is the code system used at the international level and in France.
Therefore in synthesis the proposal for the identified concept domains are
documents classification
LOINC
sections classification
LOINC
the identification of the requested / performed exams
LOINC
Related observations (weight, temperature...)
LOINC
Result of qualitative observations
SNOMED CT
Unit of measure for accompanying the result of a digital observation
(e.g. mmol / L)
UCUM
Unit of measure for daily dosages, volumes of solution in drugs,
weight masses of active base of medications
UCUM
As described before the study committed to ASIP Santé was not only related to the
standardization process, but also to consider other strategic aspects as the governance, the
implementation and the usage of those semantic resources. Four workstreams for the
national strategy has been thus identified:

The governance of the terminology resources. Several industries and associations
expressed interest in the development of a national governance of terminological
resources for the health and social sector, including the terminology selection
process; the translation of terms; the management, maintenance (update) and
distribution of the semantic assets; development of value set, maps and associations.
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


The consolidation of a panel of terminologies serving the purpose. A bottom up
approach based on use cases has been suggested.
Tools and resources for Semantic Interoperability, this includes also the development
of maps to facilitate the migration from legacy to the new terminologies.
Users supporting solutions, this includes the availability of tools and techniques (e.g.
natural language processing) that support a seamless usage of terminologies (i.e.
without requesting health professionals to act as coders).
Focusing on how some of the identified key factors have been implemented for supporting
the semantic interoperability, it can be summarized that:



Terminology services: there are in France service providers (like Phast) that provide
terminology services.
National Competence Center: it has been established since 2009. This role is covered by
ASIP Santé.
Standard Sets: The regulatory framework for the practice of laboratory medicine in
France has been complemented by a decree on January 28th 2016
([https://www.legifrance.gouv.fr/affichTexte.do?cidTexte=JORFTEXT000031922237]).
This makes mandatory for every clinical laboratory to be able to exchange its reports as
CDAr2 documents including a structured body and the provision of each test observation
at the <entry> level, relying on LOINC (translated into French) for the identification of
those tests, and on UCUM for the units of measure, in compliance with the XD-LAB
profile (with French extensions), which is part of the national interoperability framework
for e-health. The major LIS vendors on the French market had anticipated this new
regulation, and their products are ready.
Concerning LOINC, a selection of a subset of LOINC has been made to help users; the
translation process is still on-going (for the time being has been set up 45000 terms) and a
task force involving the major universities and hospitals has been set up, with expertise that
cover the several disciplines and kind of examinations that should be taken in account.
The choice of requesting for CDA level 3 document - with structured and coded elements allows for the importing of the fine grained lab results into the requesting EHR systems, and
in the future for the reuse of those data for other (e.g. secondary) purposes (e.g. public
health)
4.5.2
National/Regional Exchange of Laboratory Procedures and
Results in Finland
In Finland, the primary health care is organized at municipal level and the secondary and
tertiary health care in hospital districts. This causes a situation where even in the same
region, several patient record systems and associated electronic applications can be in use.
Due to patients’ increased options for choosing their health care providers, integration
between various local patient information systems is not sufficient. This is especially evident
regarding laboratory tests and their results. The test laboratory arrangements vary from
larger service providers with their own laboratories to smaller service providers with
outsourced and bought laboratory services. At the moment, 100 % of hospital districts, 88 %
of primary care providers and one tenth of private health care providers can exchange
information on laboratory requests and results at the regional level. One fifth of public
primary and secondary care and private health care providers can also share the laboratory
results electronically with the patients. The information exchange is based on common data
structures and code sets as described in this report.
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As centralized national patient information archiving (Kanta29) and its associated information
system services lead and define the contemporary development of Finnish health care
services, the data content for the laboratory orders or requests and tests with resulting data
were one of the first to be standardized at the national level. In Finland, standardization of
patient information data structures is based on Health Level Seven Clinical Document
Architecture Release 2 data types and formalization. The purpose of standardization is to
ensure the exchange of patient data between heterogeneous patient information systems
and registers, and to maintain consistency in longitudinal electronic records stored in the
Kanta archive.
The Finnish Institute for Health and Welfare (THL) publishes and maintains all nationally
common patient data structures and code sets and terminologies used with them. The
common data structure specifications, code sets and terminologies are downloadable free of
charge from the national code server and used by all social and health care providers in
Finland.
Implementation of national laboratory data structures
The Context
Type of Project: operation
Current status: active / in progress
The laboratory data specifications are divided in three separate CDA structure specifications:
1. Laboratory order or request
2. Laboratory examination and result
3. Laboratory report
Besides these three, an added microbiological assessment is given when needed. The
laboratory CDA structures have been implemented in the laboratory and patient information
systems or are currently in implementation by all Finnish health care providers. The common
laboratory data structures enable data exchange not only between various local patient and
laboratory information systems but also with other regions and service providers. Figure 1
illustrates the data structure specifications.
29
Based on the Act on Electronic Processing of Client Data in Social and Health Care (159/2007), a national health care archive
service known as the National Archive of Health Information (Kanta) is being set up. The National Archive of Health
Information will offer all health care organizations a nationwide, centralized repository for patient information in electronic form.
The system will allow health care professionals to access data for any particular patient irrespective of institutional boundaries
and based on patient’s individual consent.
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Laboratory results
Laboratory order
Laboratory test result
Laboratory order ID (II) M
Laboratory order requester name (PN) M
Laboratory order requester organization unit (II) M
Date of order (TS) M
Additional order information (ST)
Sample quality in requsted test (CV)
Laboratory test name, code and code set (CV) M R
Additonal test information (ST)
Begin and end date for recurring test (IVL_TS)
Maximum number of repeated tests (INT)
Laboratory test (CV) M
Sample quality (CV)
Laboratory test method (CV)
Laboratory order ID (II) M
Date of test (TS) M
Health care professional (ST)
Information reference (CV)M
Method of conducting test (CV) M
State of laboratory result (CV) M
Result completion time (TS) M
Microbiological result (LB) MC
Laboratory test result and unit (PQ) MC
Laboratory test result, text (ST) MC
Reference value interval and normal value (IVL_PQ)
Reference value interval and normal value, text (ST)
Result exeption (CV) MC
Laboratory test additional information (ST)
Report author name (PN) MC
Report author organization unit (II) MC
Report status (CV) MC
Report text (ST) MC R
Report identifier (II) MC R
Laboratory report
Laboratory test ID (II) M
Reported laboratory test name (CV) M
Sample quality (CV)
Laboratory test method (CV)
Date of report (TS) M
Report author name (PN) M
Report author organization unit (II) M
Report status (CV) M
Report test (ST) M
Microbiological result
Microbiological finding, code and name (CV) R
Microbiological finding, additional information (ST)
Microbe amount, estimation (CV)
Microbe amoint (PQ)
Laboratory test method (CV) R
Microbiological drug name and code (CV) R
Microbe sensitivity, measuring method (CV) R
Microbe sensitiity, estimated (CV)
Microbe sensitivity (PQ)
Finding’s significance for hospital hygiene (BL)
Sensitivity measurement’s additional information (ST)
Figure 4 - The laboratory orders, results and reports.
30
Besides patient data exchange in everyday care situations, there are added benefits of
implementing the common laboratory data structures. All laboratory data is fully structured
and each of the three laboratory data sets can perform as a structured entry in the patient
records. All structured entries can be retrieved in the Kanta Information Management
Services31 and processed automatically to generate up-to-date lists of a patient’s structured
data entries to be shown in the patient information systems. The Kanta Information
Management Services can process all structured data entries regardless of the health care
provider that stored the original data. Laboratory results were one of the first to be processed
in the Information Management Service that later will be expanded with, for example,
diagnoses, risk data, procedures, imaging examinations, key physiological measurement
data, vaccinations and medication. Additionally, the Information Management Services
provides patient centered health and care plans, information of all citizens’ Kanta consent
and possible bans of disclosure, living will and organ donor status. All data processed in the
Information Management Service is made accessible for citizens through Kanta portal, My
Kanta pages32.
In the following figures, are examples of laboratory results accessible as summary lists
provided by the Kanta Information Management Service33.
30
The data type abbreviations are HL7 data types, M = mandatory data, MC = mandatory data, conditionally and R = recurrent
data. All code sets (data type CV) are national code sets. Organization unit identifier.
http://www.kanta.fi/en/earkisto-esittely
32
http://www.kanta.fi/en/omakanta
33
Originally in Heikki Virkkunen, Päivi Mäkelä-Bengs, Jari Suhonen, ja Riikka Vuokko. Tiedonhallintapalvelun periaatteet ja
toiminnallinen määrittely, versio 2016 [Information management service principles and functional specifications, version 2015].
National Institute for Health and Welfare (THL). Directions 4/2015. Available online: http://urn.fi/URN:ISBN:978-952-302-4847
31
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Figure 5 - The laboratory results are shown in patient information system with the latest results
34
at top.
Figure 6 - This example shows the laboratory result by dragging the cursor above the column
with the test name abbreviations, all previous results for that test can be inspected.
34
For example, this patient has S-Natrium tests made 14 times and the latest test was conducted in September 12th 2014 with
a result 144 and reference value 1
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Drivers for adoption
Better quality and safety of care to individual patients
Driver
Is Applicable?
How it applies?
More
complete
coded
documentation.
Yes
With the availability of nationally specified structures,
interoperable data enables data exchange between
patient information systems within a region as well as
between regions. When exchanging laboratory result
data, both sending and receiving system understands
and processes the data content in a uniform way. The
data
structure
implementation
supports
the
user/system to supplement all relevant data. Common
terminology and code sets increase data quality.
Better overview of
each
patient’s
information.
Yes
The structured data enables Kanta Information
Management Services to process and provide up-todate laboratory results list for each patient regardless
of the original organization unit storing the data.
Kanta-automated summary lists are shown as the first
information when accessing patient’s data. The
summary content is uniform in all patient information
systems although the display view can vary.
Better records to
enable
decision
support.
Yes
As laboratory result data is well structured and utilizes
code sets, identifiers and numeric values, it is usable
data in decision support. Decision support is typically
integrated in patient information systems to generate
guiding messages and prompts, e.g. based on care
guidelines for the system user.
Support
the
adoption of point of
care evidence based
clinical guidelines
Yes/Partially
These benefits have not yet been established and are
currently in plans or available/in use in some local
systems. It is possible to provide prompts and
recommendations (e.g. care instructions, advice to
contact a health care provider) via citizen portal in the
future.
Improved
patient
safety
and
medication safety
Yes
Data quality increases with common data structures
as the structures support uniform documenting and
decrease the system users need to remember what
data is mandatory. Structured data can be utilized in
automated system functions and alerts/reminders
(e.g. decision support) etc. Free text analysis (e.g.
with NLP tools) is not needed with laboratory data.
Additionally, the common data structures confirm
management of laboratory results for medications
requiring regular control for possible infiltration
(accumulation of medicinal substance in tissue or
cell).
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Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Underpinning multiprofessional
collaboration.
Yes
All professionals in care relationship can access the
laboratory results regardless their organization unit or
professional role. Up to date laboratory result lists are
generated from structured data and provided by Kanta
in timely manner.
Sharing EHRs with
patients.
Yes/Partially
Accessibility through citizen portal My Kanta is yet
only for inspecting the data, and functions such as
reminders or home care guidelines for self-care are in
development. Also citizens’ PHR interface to My
Kanta is under planning. The aim is to increase
citizens’ own active roles in their health care and give
professionals an access to citizen generated data.
However, sharing the laboratory results with patients
is already rather widely used at the regional level and
also provided by several private care providers. Local
applications typically utilize national standardized
code sets.
Cost reduction (in the healthcare system)
Driver
Is Applicable?
How it applies?
Reduce
duplicate
data capture through
better
interoperability
Yes/Partially
All laboratory results are stored in Kanta archive. No
copying and/or multiplying of the results are needed
as all professionals (and the patients themselves) can
access the same information via automated lists.
Full benefits of the automated laboratory result lists
are also based on local patient information systems’
user interface design and its integrated tools and
functions.
Capture
reporting
and reimbursement
codes at source, in a
more efficient way.
Yes/Partially
Consolidate
from
multiple
existing
terminologies.
Yes
Same national code sets are used.
Reimbursement codes are linked to procedure codes.
In Finnish context, the laboratory data structures and
code sets or terminologies used in them are now
standardized. Only these common, national structures
are allowed to be used in the Kanta archiving.
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Optimising reimbursement
Driver
Is Applicable?
How it applies?
Optimizing
reimbursement
Yes/Partially
It is evident that common code sets and document
structures increase data quality and completeness of
the information content. The standardized code
structures can also be used in administrative
processing of orders and claims. The national
standardization creates interoperability between the
EHRs and the administrative databases of the care
providers,
thereby
creating
possibilities
for
benchmarking costs etc.
Analysis (secondary) uses
Driver
Is Applicable?
How it applies?
Analysis
(secondary) uses
Yes
Secondary use benefits are expected with the Kanta
archiving, although full benefits require specifying the
data needed for analysis and also changing legislation
to allow for more versatile use of the rich data in the
Kanta archive. However, published data standards
also support developing new content into national
registries, e.g. for research or other secondary use
purposes.
Cross-border information and knowledge sharing
Driver
Is Applicable?
How it applies?
Cross-border
information
and
knowledge sharing
No
Out of scope of the project/implementation goals.
Others Drivers
Driver
How it applies?
National Kanta archive
and Kanta information
system services
Kanta accession is mandatory for all Finnish health care providers.
It is regulated by law and coordinated by THL. All patient
information systems are evaluated before accession to ensure their
fit to the Kanta requirements.
Adoption and operational strategies
Semantic interoperability strategies that this implementation case relies on:
1. Kanta archiving and Kanta information management service are provided and funded
at national level.
2. Service providers are required to implement the common documenting structure
specifications, code sets and terminologies. All specifications are provided uniformly
at national level, and health care professionals and other subject experts have
participated in this development effort.
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3. For organizations and professionals as system users, national level detailed
instructions for structured documenting have been published by THL. THL arranges
and aids also in training of structured documenting.
4. Kanta implementation is progressing phase by phase, with the public service
providers as the first participants that accessed Kanta. Laboratory orders and results
were one of the first common documenting structures implemented nationwide. The
code sets and terminologies used in structured laboratory entries have all been
published by THL.
5. The laboratory code sets are well implemented in the local EHR systems and while
waiting for the full national services provided by Kanta, their implementation already
supports local and regional health information exchange daily in Finland.
1.
Operational strategies in selecting and applying terminologies / value sets:
1. Laboratory data structures for documenting and storing have been specified in
national level workshops and expert groups organized by THL. The specifications
include the code sets and terminologies utilized in these data structures.
2. THL maintains the structured data specifications and code sets in the national code
server. Maintenance is handled by THL experts and other subject experts, and larger
updates are published as a new version.
3. The code server content can be freely downloaded.
4. Supporting documentation, guidelines etc. are also made freely available by THL.
5. Term harmonization and terminology work has been conducted as a part of the
preparation process. The citizen portal, My Kanta has slightly different terminology
than the professional interfaces.
6. When needed, mapping between terminologies or code sets are provided by THL
(e.g. legacy terminologies).
7. All structures and code sets are provided in Finnish and in Swedish (long names and
descriptions).
Other remarks
Concluding remarks are arranged as question/answer -pairs.





What are/have been - if any - the benefits and the challenges of using this solution?
o The national system is still partially in the implementation phase, it is too early
to show the benefits. Regional systems function well.
Is the value set derived from a guideline? How EU collaboration could help in this
process?
o EU collaboration is needed when cross boarder patient summaries are
developed. The national work is progressing without EU support.
What are /have been the development and maintenance costs if known?
o Since the laboratory information structures are just one part of a larger
development process, the specific cost of their development is not possible to
calculate at the moment.
What are/have been - if any - the lessons learned; and if applicable, what did you do
differently and why?
o The time frame from information structure development to actual
implementation in the daily use of EHRs is very long and this was not taken in
to account in the first plans.
What are - if any - the suggestions and/or the plan for the future (in term of process,
content choice)?
o Next logical step would be concentrating on the issues that are needed for
cross boarder development.
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4.6
4.6.1
National/Regional Exchange
Procedures/Results
of
Lab
Pathology
Case Study Description
This case study consider the sharing of ppathology reports within a specific jurisdiction in
order to allow to different types of clinicians (GPs, hospitals, specialists) to use (display,
import in their systems,..) the results coming from different laboratories. This use case may
consider possible extension like the secondary usage of or the patient access to those
results.
The focus of this case study is on the identification of the type of executed examinations and
the associated qualitative and quantitative results.
Even if the domains are slightly different there are several common aspects with the
Laboratory Report case study.
4.6.2
The NHS Diagnostics Data Service
The Context
Type of Project: operation
Current status: in progress
This implementation case describes the NHS (National Health System) digital diagnostic plan
for the development of new diagnostic data services, with a focus on the sharing of pathology
lab reports.
This project is part of the National Information Board roadmap aiming to progress towards
the goal for a paperless NHS by 2020, than mean to have electronic care records for every
patient and interoperable digital systems replacing paper records across all care providers.
Related goals are:
–
–
–
New models of care / vanguard sites, etc.
Need for efficiency savings
Rising service demands
Two billion pounds has been committed for this goal, about the 25% dedicated to the digital
diagnostic service.
It is a five-year project, starting on April 2016 (end 2020). The plan includes the publication of
Implementation standards for primary care and other prioritised pathology results reporting is
foreseen for April 2017; and routine standards conformance testing and performance
reporting on pathology messages flowing for 2018. Moreover in the recent final report on
“Productivity in NHS hospitals” (Feb. 2016), within the context of implementation of pathology
service quality assurance dashboards, it has been recommended that: “HSCIC (Health and
Social Care Information Centre) should publish a definitive list of NHS pathology tests and
how they should be counted by October 2016, with NHS Improvement requiring trusts to
adopt the definitions from April 2017”
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An essential part of this project is therefore the development of a new NLMC (National
Laboratory Medicine Catalogue). The NLMC is a national reference or compendium of data
standards for use in pathology requests and results communications and in patient records
(see below for further details).
This service will allow the sharing of pathology reports coming from different laboratories with
GPs and Hospitals, but the main scope is that of defining a single and common way to
describe things for being reused for a wide set of use cases.
The background
This section describes the current state of the art for the exchange of pathology report
results.
Based on a national decision made in 2002 Labs report results to GPs are made in a coding
language designed for primary care test requesting (codes used for the order are the same
used for the report). A subset READ V2 (the Pathology Bounded Code List (PBCL)) is used
for this purpose. Data are exchanged using EDIFACT (Report Message). This old-fashion
format shows some shortages: few structured data (a lot of free text); limitations with
SNOMED CT codes (fields too short)…
For what concern the NLMC, the first version (2009) was reportedly adopted by some NHS
labs and are still in use to some extent today. A new version of NLMC (2015) has been
developed, this version focused on professionally defined terms and clinically rich concepts
for pathology requests and reports. NLMC 2015 however has no technical implementation
specification and is not complete for clinical terms and codes. Both of them are linked to
SNOMED CT, but no one to LOINC. Comparing NLMC 2015 with LOINC, LOINC is actually
clinically richer in many cases because it identifies specimen type, measurement method and
investigative approach where relevant in the test name, helping to avoid inappropriate
comparisons of results from similar tests (e.g. names that do not specify test method can
inadvertently ‘group’ results data that legitimately use different units of measure or measure
subtly different aspects of the same thing).
The national primary care pathology data standard currently used is the Pathology Bounded
Code List or PBCL that should be replaced by the NLMC when the “new” NLMC will be
ready.
Summarizing, there are no National Data Standards defined for requests; some standards
are used for results for Primary Care (mainly for blood sciences - roughly 50 million reports
per year; 100.000 cervical Ca screening tests are rejected per year) and for Public Health
screening (for Bowel Ca and new-born bloodspot only)
Drivers for adoption
The solutions currently used for the exchange of Pathology reports are described in the
previous sections, the consequence of that choice is that tests using different measurement
methods (e.g. presence/absence detection, mass/volume, moles/volume, titer, etc.) all use
the very same name and Read code when reported to primary care. This is confusing and
can lead to repeat test requesting when GPs cannot tell which results are comparable and
which are not.
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GPs can sometimes spend time following-up on hard to understand results due to standard
term ambiguities and, sometimes, uneven standards used by labs. Considering that Labs
report roughly 50M test results to GPs each year, that means that even if 1 minute of GP
time could be saved per result report received, the amount of saved time could be estimated
in roughly 100k GP clinical days per year across England. On the requesting side, paper is
still used in some cases, where paper-based communications can be converted to digital, a
cost savings of roughly £1-3 per sample has recently been estimated from one NHS lab,
from avoiding manual data entry, handling, postal and paper. Also, where national standards
could help avoid unnecessary or inappropriate test requesting, patient, clinician and lab
professional time and costs could be saved. For example, Public Health England has
informally communicated that roughly 100k cervical cancer screening tests are rejected by
labs across England every year and it is likely that this number can be significantly reduced
in future with better quality test requesting.
The compelling reasons for compiling a national catalogue can be therefore summarized in:





35
Streamline deployment activity for NCRS acute deployments and by doing this it will
save deployment resources.
Reduce clinical risk by using best practice reviewed by clinical peers.
promote consistency, making ordering easier for clinicians who practice in more than
a single Trust
allow common terminology codes (SNOMED CT) to be applied to things that could be
ordered (e.g. procedures) - and this in turn will enable Spine35 messaging
Less costly to support sites that share a common catalogue. Trusts would need to
build catalogues for individual deployments.
Spine is “a collection of national applications, systems and directories that support the NHS in the exchange of information
across national and local systems. Hosts demographic information for 80 million citizens plus a number of national
applications
including
Summary
Care
Record
and
the
Electronic
Prescription
Service.”
(source
http://systems.hscic.gov.uk/ddc)
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Better quality and safety of care to individual patients
Driver
Is Applicable?
More
complete
coded
documentation.
Better overview of
each
patient’s
information.
Yes
The adoption of the new NLMC will provide more
complete information avoiding the misinterpretation of
the lab test results and missed diagnoses.
Yes
The combination of FHIR resources and NLM
Catalogue will facilitate the consistent reuse of
pathology results.
Yes
The project aims to provide a single and common way
to describe results for being reused for a wide set of
use cases, including decision support. For that
purpose, when LOINC is used the provision of the
LOINC - SNOMED CT Cooperative Project’s mapping
from the LOINC term to the semantically equivalent
set of SNOMED CT codes will allow the use of
SNOMED CT-based reasoning in patient record
systems.
Better records to
enable
decision
support.
Support
the
adoption of point of
care evidence based
clinical guidelines
Improved
safety
How it applies?
See above
Yes
patient
Yes
This is the main expected benefit for Patients,
promoting consistency, reducing misinterpretation,
facilitating reasoning…
Enriched EHR data exchange for continuity of care
Driver
Is Applicable?
How it applies?
Providing pathology data that is comparable across
the NHS and can be used to assess outcomes and
improve patient care.
Underpinning multiprofessional
collaboration.
Yes
Sharing EHRs with
patients.
Yes
Currently in fact it is difficult and at times impossible to
combine pathology information across lab services,
creating a barrier to lab data-sharing and working
seamlessly and safely through NHS service reconfigurations (e.g. lab mergers).
Cost reduction (in the healthcare system)
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Driver
Is
Applicable?
How it applies?
Reduce duplicate data
capture through better
interoperability
Yes
Providing pathology data that is comparable across
the NHS enable the reuse of data across different
systems.
Capture reporting and
reimbursement codes
at source, in a more
efficient way.
No
This is not one of the current drivers, but it could be
considered for future usage.
Consolidate
from
multiple
existing
terminologies.
Yes
See general description above
Optimising reimbursement
Driver
Optimising
reimbursement
Is Applicable?
No
How it applies?
This is not one of the current drivers, but it could be
considered for future usage.
Analysis (secondary) uses
Driver
Analysis
(secondary) uses
Is Applicable?
Yes
How it applies?
The project aims to provide a single and common way
to describe results for being reused for a wide set of
use cases, including decision support. For that
purpose, when LOINC is used the provision of the
LOINC - SNOMED CT Cooperative Project’s mapping
from the LOINC term to the semantically equivalent
set of SNOMED CT codes will allow the use of
SNOMED CT-based reasoning in patient record
systems.
Cross-border information and knowledge sharing
Driver
Cross-border
information
and
knowledge sharing
Is Applicable?
Partially
How it applies?
Even if cross-border data exchange has not been
mentioned, focus has been put on the usage of
international terminologies and on the sharing of
knowledge and experiences with other countries.
Others Drivers
Please indicate if there are other drivers to be considered
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Driver
How it applies?
Reducing the number of test requests rejected by labs (and clinical
and patient time wasted) for not meeting established pre-conditions
for that test;
Improved process
Minimizing the waste GP time when test result code discrepancies
between lab and GP IT systems or ambiguities in current coding
standards require clinical follow-up or, in worst cases, waste
patient, clinician and lab professional time when result ambiguities
lead to repeat test requesting;
Adoption and operational strategies
The background and the drivers of the NHS Diagnostics Data Service Case Study have been
described in the previous sections. As indicated, the Digital Diagnostics workstream, part of
the of National Information Board (NIB) roadmap, foresees the completion and the usage of
the National Laboratory Medicine Catalogue (NLMC) as one of the nation’s highest priority
future health information standards within the next 1-3 years. This is supposed to be done
through a collaboration strategy described in the “National Laboratory Medicine Catalogue
(NLMC) Delivery Strategy” document and below summarized, that includes the following
steps: (1) Primary care and other prioritized report Standards; (2) Primary care and other
prioritized Request Standards; (3) Cancer Diagnostics; (4) Genetics and Personalized
Medicine; (5) Chronic Care ; (6) Public Health; (7) Communicating with Patients; (8)
Pathology Services Quality Indicators; (9) Pathology Interoperability Certification Service.
Several dimensions have been considered in order to achieve a complete and technically
usable NLMC within the next few years:



Governance and management (development and maintenance) processes
Stakeholders involvement
Standards set selection
Starting from the last item, the expectation for the next NLMC generation is that of combining
the positive aspects of both previous NLMC versions, while at the same time joining the
NLMC seamlessly with existing international pathology data standards, and with national
technical standards for clinical communications and shared patient records.
This national reference for pathology requests and results data standards should include
national electronic communication and record standards for:
1. Pathology test identification
2. Pathology test descriptive results or clinical interpretations (qualitative)
2. For these two elements it is supposed to be used
o UK standard display text and
o International Standard Codes
3. Pathology test result (quantitative). This includes
o Standard Units of Measure
o Reference Range (if nationally agreed or examples)
4. Recommended pre-conditions for test requesting
o e.g. reflecting NICE guidelines or other published national professional
guidance
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5. Term/code national implementation guidance
o e.g. dual reporting during a transition period for method changes
The following table summarizes what are the current proposals for the results; the evaluation
for the requests is still in progress.
Test identification
Descriptive results or clinical interpretations (qualitative
results)
Units of measure (quantitative results)
Standard Boolean (e.g. positive/negative) results
Nationally recommended pre-conditions for test requests
LOINC (UK display terms)
SNOMED CT
UCUM expressions
NHS Data Dictionary
SNOMED CT or
Dictionary
NHS
Data
To support the transition and the adoption of this standards set the following additional
resources will be provided (where applicable):







Mapping the NLMC result code to the legacy PBCL (previous primary care pathology
data standard) code
Example reference range (where applicable)
Link to pathology instrument product identification standard
Link to relevant test information for patients
Term and code national implementation guidance
LOINC - SNOMED CT technical expression mapping
Mapping of result code to legacy NHS data standard
It is interesting to note how the proposed solution relies on a combination of different
international code systems: LOINC, SNOMED CT and others. This approach seems to be
today the best solution in this domain, being those code systems complementary considering
the different types of clinical information that has to be managed. This propriety is a positive
consequence of the collaboration agreement between IHTSDO and Regenstrief Institute, in
which they effectively agreed not to duplicate clinical terms between LOINC and SNOMED
CT and also agreed that both coding systems should be used together in electronic patient
records. To better support this choice they are in the process of producing mappings from
LOINC codes to SNOMED CT (multiple) code expressions. This technical mapping between
LOINC and SNOMED CT should enable electronic patient record systems to ‘find’ LOINC
codes using the SNOMED CT concept hierarchy (e.g. for automated reasoning purposes).
For what concern the exchange of data, the HL7 FHIR standard has been selected
(DiagnosticReport resources) this allows to take the advantages of the best-of-breed ICT
technologies and simplifying the implementation, without however loosing the alignment to
HL7's previously defined patterns and best practices.
The adoption and operational process recognizes the need to involve all stakeholders in
NLMC production and use.
A Collaborative NLMC Governance has been defined involving a large set of different
stakeholders. Stakeholders considered have been : (a) clients (patient and care providers
representatives, NHS England, …) ; (b) key product development partners( HSCIC,
Professional Record Standards Body (PRSB),…) ; informatics products direct users (NHS
diagnostics professionals / their IT systems; NHS primary care providers / their IT
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systems;…) ; linked international and national products (SNOMED CT; LOINC, NHS data
dictionary;..). All those classes of stakeholders have been / are planned to be involved with
different roles in the tasks and phases identified.
Processes for the development and for the maintenance and the delivery of the NLMC have
been defined as well.
The following table summarizes how key users are expected to contribute
Key NLMC Users
NHS Lab professionals
Public health and care
research professionals
Health IT System suppliers
For checking and using standard
terms and units of measure
As a pathology data reference
For system design and update
And through them, it will positively impact:
Patients and their care providers
NHS commissioners and planners
Enabling safer, clinically rich and unambiguous
electronic communications and records
Enabling the analysis of clinically rich and
comparable pathology service data from across
England
Other remarks
The main expected benefits of this project can be summarized in




Save lives by avoiding pathology results misinterpretations and missed diagnoses
Save patient, laboratory and clinical time with improved electronic communications
Improve care by enabling rich pathology data pooling and analysis across all NHSsupporting laboratories
Support new models of care by enabling pathology communications that do not
depend on local knowledge for understanding and use
Considering as beneficiaries:



Patients and GPs (Increased safety, improved monitoring, improved experience
Hospital clinicians (Hospital clinicians who work in multiple Trusts and don’t have time
to learn or get used to the bespoke ‘language’ and units of measure used by each
lab)
People delivering shared care records and Analysts (People delivering shared care
records involving information from multiple labs (e.g. regional or locally between
secondary and primary care or between newly merged hospitals, etc.))
Another relevant aspect pointed out is the collaboration with other countries. Even if UK
has a strong and long experiences with terminology and standards collaboration (see for
example the big contribution that UK gave and gives to the SNOMED CT development ) it is
recognized the importance of establishing international collaborations for exchanging
experiences and learning from others.
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5
Appendix 3: Overview of European Countries
(Questionnaire)
This report is based on responses gathered before march 1st 2016, covering 21 Member
States: Austria; Belgium; Bulgaria; Croatia; Czech Republic; Denmark; Estonia; Finland;
France; Germany; Greece; Hungary; Italy; Luxembourg; Malta; Netherlands; Portugal,
Slovakia; Spain ; Sweden, United Kingdom; plus Norway.
The response from the United Kingdom, collected during a meeting organized with UK
representatives, is included in this report with the caveat that the answers reported haven’t
received yet an explicit validation by respondents.
The results of the Country Overview was prepared and shared with the interested parties for
the content review and therefore shared during the revision workshops.
All the received changes have been tracked and considered for this deliverable.
The consolidated report is provided hereafter.
5.1
About your country
This section of the questionnaire aims to provide an overview of main characteristic of each
country.
5.1.1
Which statement describes your country best (IHTSDO
membership and SNOMED CT adoption)?
This questionnaire confirms the current limited usage of SNOMED CT in the interviewed
countries: for the large majority of them the adoption is in fact in progress or under
consideration.
Austria
Non IHTSDO Members (12)
Adoption
For future
Under evaluation
consideration
X
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IHTSDO Members (10)
Adoption
In progress
Local
National
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Malta
Finland
Germany
Sweden
Croatia
Netherlands
United Kingdom
Belgium
Estonia
Slovakia
Greece
Italy
Czech Republic
Portugal
Luxembourg
Denmark
Spain
Norway
Bulgaria
Hungary
France
TOTAL
Member
State
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
7
5
8
1
1
Which statement describes your
Comment
country best It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
It is an IHTSDO member and the
Early stages, use case based approach
adoption of SNOMED CT at the national
level is in progress.
It is not an IHTSDO member state, the adoption of SNOMED CT is under evaluation.
It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is not an IHTSDO Member State, the adoption of SNOMED CT is under evaluation.
It is not an IHTSDO member state, the
The adoption of SNOMED CT is currently
adoption of SNOMED CT is under
under evaluation at the National level.
evaluation.
However, some hospitals are already using
it either because they use clinical solutions
embedding SNOMED CT or in the context
of research projects to experiment it.
It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
It is not an IHTSDO member state, the adoption of SNOMED CT might be considered
for the future.
It is not an IHTSDO Member State, the adoption of SNOMED CT might be considered
for the future.
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Member
State
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
Which statement describes your
Comment
country best It is not an IHTSDO member state, the
adoption of SNOMED CT is under
evaluation.
It is an IHTSDO member and SNOMED
The intention is to adopt SNOMED CT as a
CT is mainly adopted for health and
national standard. However, to date
social data at the organizational (e.g.
implementation has been at the
hospital, local project) level.
organisational level.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is not an IHTSDO member state, the
adoption of SNOMED CT is under
evaluation.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and SNOMED
NRC supports the UK and all (England,
CT is nationally adopted for health and
Wales, Scotland, North Ireland) contribute
social data.
to IHTSDO membership.
The strategies and the approaches are
however different across the 4 countries.
This questionnaire mainly describes
England for which there are several uses
cases where SNOMED CT is the adopted
solution.
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5.1.2
Which of the following statements apply to your country
(usage of terminologies at the national level)?
Almost all the countries use terminologies at the national level for secondary or
administrative purposes or for very specific use cases. Almost an half of countries claim that
a national strategy for terminology is under discussion.
Table 1- There are terminologies used at the national level for health and social data, for.
Member
State
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
A wide range of
use cases (e.g. in
a nation-wide
EHR/PHR).
Very specific use
cases (e.g.
prescription,
pharmacovigilanc
e).
At the national
level but a
national
terminology
strategy is still
under discussion.
No
No
No
Yes
Yes
Secondary or
administrative
purposes (e.g.
reimbursement;
governance;
costs-control;
registries…).
No
Yes
No
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
Yes
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No
No
No
Yes
Yes
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Member
State
A wide range of
use cases (e.g. in
a nation-wide
EHR/PHR).
Very specific use
cases (e.g.
prescription,
pharmacovigilanc
e).
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
No
No
No
No
Yes
Yes
No
Yes
No
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes
Yes
5.1.3
Secondary or
administrative
purposes (e.g.
reimbursement;
governance;
costs-control;
registries…).
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
At the national
level but a
national
terminology
strategy is still
under discussion.
Yes
Yes
Yes
Yes
Yes
No
No
No
Yes
No
Is/are there national competence center(s) for terminologies
in your country?
About 60% of the countries declared to have a National Competence Center(s) for
Terminologies: AT, BE, BG, DK, EE, FI, DE, NL, NO, PT, SL, SP, SE, UK. (See table below).
This is an important aspect to be taken in account also in the perspective of terminology
policies at the national level.
Member
State
National competence center(s) for terminologies
Austria
Yes
Federal Ministry of Health, ELGA (EHR)
Belgium
Yes
Belgian NRC, known as the Terminology Center, governance rests with
stakeholders defined by the National Action Plan e-health 2013-2018
Bulgaria
Croatia
Yes
No
National Center of Public Health and Analyses
Czech
Republic
No
Denmark
Estonia
Yes
Yes
National eHealth Authority (NSI)
The Institute of Estonian Language, Medical Terminology Commission
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Member
State
National competence center(s) for terminologies
Finland
Yes
The National Institute for Health and Welfare (THL) has this role by law
France
Yes
Germany
Yes
ATIH and CepiDC represent the WHO collaborating center for ICD and
ICF.
Medical terminologies, classifications and standards are maintained by
DIMDI (German Institute of Medical Documentation and Information) for
the use at national level.
Greece
No
Hungary
Italy
No
No
Luxembourg
Malta
No
No
Netherlands
Yes
Nictiz
Norway
Yes
Portugal
Yes
Norwegian Directorate of Health - Section for Classification and
Terminology
Clinical terminologies Centre in Portugal: CTC.PT:
www.ctcpt.net
Slovakia
Yes
Narodne centrum zdravotnickych informacii
Spain
Yes
MSSSI CNR
Castilla y León
Centro de Competencias TicSalut
Galician Sergas
Andalusian Healthcare Interoperability Office
... and more
Sweden
Yes
SNOMED CT National Release Centre
National Release Centre for WHO classifications/other national
classifications
United
Kingdom
Yes
National Release Centre (NRC) serving the UK: is supported by a number
of UK governance and editorial functions
There are National representative organizations for specific terminologies:
e.g. LOINC Italia for LOINC; the Italian Collaborating Centre for the WHOFIC (Friuli Venezia Giulia Region); etc. Even if the Health policies are
under the responsibility of the Ministry of Health, there is not for the
moment a specific competence center dedicated to terminologies.
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5.1.4
Are there international terminologies used nationally for
health and social data?
Concerning the question about the usage of international terminologies at the national level
only the Czech Republic has asserted that they are not using international terminologies.
ICD-10 (with or without local extensions) and ATC are the most commonly used (even if with
different scopes) [See table below for details]
Member
State.
International terminologies used nationally for health and social data: name,
scope, and - if known - who is responsible for them.
Austria
ICD 10 BMG 2014 - Health Ministry
LOINC - ELGA
ATC - AGES
Belgium
LOINC - laboratory
ICD-10 - different uses e.g. causes of death
ICPC-2 - general practitioners
ICD-10-CM/PCS - policymaking and reimbursement purposes - Federal Public
Service
ICD-O - research - cancer registry
ICF - occupational medicine
APR-DRG - grouping of ICD-10-CM/PCS for reimbursement purposes - Federal
Public Service
Bulgaria
Croatia
ICD-10
Australian CMP
ICD-10
ATC
Czech
Republic
No International Terminologies used for health and social data at the national level.
Denmark
ICD-10 Danish extension - NSI
Nordic Classification of Surgical Procedures (NCSP) Danish Extension - NSI
NPU - NSI
SNOMED CT Danish extension - NSI
ICF - NSI
ATC - Danish Health and Medicines Authority
ICPC-2 - DAK-E
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Member
State.
International terminologies used nationally for health and social data: name,
scope, and - if known - who is responsible for them.
Estonia
ICD-10-for diagnosing and statistics-Ministry of Social Affairs;
ATC-drug prescriptions-Republic of Estonia Agency of Medicines;
International Standard Codes for the Representation of the Names of CountriesStatistics Estonia;
UICC TNM-for cancer diagnosis-Estonian Cancer Association;
LOINC-for laboratory procedures-Estonian Laboratory Medicine Association (in the
near future it will be ours);
International Standard Classification of Occupation - Estonian Statistics.
Finland
ICD-10 (THL)
ICD-0-3 (Cancer Society + THL)
ICPC2 (Association of Munincipalities + THL)
International classification of Nursing (localization, The University of Eastern Finland
+ THL)
The Nordic Classification of Surgical Procedures (THL)
ATC (The Finnish Medicines Agency)
ICF (THL)
FinLoinc (THL)
EN/ISO:9999: Assistive products for persons with disability
France
ICD10 - procedure accounting purposes - ATIH (Health Ministry)and CepiDC
(National Health Research Institute)
LOINC - care coordination and observation results - ASIP Santé (Health Ministry)
UCUM - Measure units - PHAST (association)
ATC - classification of drugs - just used
MedDRA - classification of adverse events - just used
Germany
ICD-10 -for diagnosis-coding in mortality, for morbidity national adaptation was
created (ICD-10-GM, German Modification, see below) - responsibility for German
version at DIMDI
ICD-O-3 -for coding of oncology diagnosis - responsibility for German version at
DIMDI
ATC/DDD - for coding of drug information - responsibility for German version at
DIMDI
ICF - ICF-terminology in use for all kinds of applications in rehabilitation medicine responsibility for German version at DIMDI
UMDNS - for coding of medical devices - responsibility for German version at DIMDI
EDMA - for coding of in-vitro devices Provided for national use, but not fully
implemented:
UCUM and LOINC - for coding of Laboratory information
MeSH and UMLS - The medical thesaurus MeSH (Medical Subject Headings) and
the UMLS (Unified Medical Language System) as a metathesaurus and semantic
network are used for cataloging of library holdings, indexing of databases and
improvement of retrieval.
Greece
ICD10 diagnosis and for reimbursement purposes - MOH
ATC drug control - Greek drug authority
ICPC-2 eP system
CPT considered for medical procedures not established yet MOH
Hungary
ICD10 - Health Secretariat, National Healthcare Service Center
national implementation of ICPM - Health Secretariat
ATC - National Institute for Pharmacy and Nutrition
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Member
State.
International terminologies used nationally for health and social data: name,
scope, and - if known - who is responsible for them.
Italy
ICD-9-CM:2007 - procedure accounting purposes (DRG) ; morbidity statistics ; other
clinical contexts (e.g. Patient Summary) - Health Ministry
EN/ISO:9999: 1998 - Assistive products for persons with disability (as part of the
national nomenclature) ATC - Drugs classification - AIFA
ICD 10 mortality statistics
ICD-O-3: tumor registries.
MedDRA pharmacovigilance
Luxembourg
- ICD-10 - Diagnosis
- CCAM - procedure and accounting (national version)
- ATC - Pharmacies /Cefip database
- LOINC (partly) - Laboratories
- ENP - Care sector
ICD-10: Used at national level for classification of diseases
ICD-9-CM: Used by Government hospitals for classification of surgical operations
and other procedures
ATC: Used by certain Government Health Service departments for classification of
pharmaceutical products
ICPC: Used by Government Health Service departments for classification of
concepts in the primary health care sector
Malta
Netherlands
ICD-10: Classifications/Mortalities: RIVM (WHO-FIC), for statistical and analytical
purposes
ICF: Functioning: RIVM (WHO-FIC)
Omaha Systems Support - Omaha Systems, some home care organizations
Raiview - Some Eldery homes
Nanda (Nic/Noc) - Some hospitals
ICPC(1) for GP’s
ATC
EN/ISO:9999
LOINC - In some labs
Norway
There are a few international terminologies - like ICD-10 for reporting of diagnosis,
ATC for reporting on drugs and ICPC for primary care.
There are a few Nordic based terminologies - like NCMP, NCSP, NCRP that for
reporting on procedures.
ICD-0-3, ICF, ICNP, HL7, ICPC-2 ;SNOMED-CT ; ATC
ICNP - Nurses' order
ICD-9-CM and ICD-10-CM - procedure accounting purposes - Health Ministry
CPAL - Portuguese Catalogue of Lab. Analysis - Health Ministry
ICD-9 procedure
CPARA - Portuguese Catalogue for Allergies and Other Adverse Events - Health
Ministry
CIPE (ICNP)- International Classification for Nursing Practice - Health Ministry
ICD10 - National Cancer Registry; Mortality
ICDO - National Cancer Registry;
Portugal
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Member
State.
International terminologies used nationally for health and social data: name,
scope, and - if known - who is responsible for them.
Slovakia
ICD - 10./SK - DRG- International Statistical Classification of Diseases and Related
Health Problems 10.version Slovak republic Diagnosis Related Groups
(responsibility: Urad pre dohlad nad zdravotnou starostlivostou)
ATC- Anatomical Therapeutic Chemical classification system (responsibilty: Statny
ustav kontroly lieciv),
LOINC- Logical Observation Identifiers Names and Codes
INN- International Nonproprietary Names
EDQM- European Directorate for the Quality of Medicines & HealthCare
UCUM- The Unified Code for Units of Measure
Spain
ICD-9-CM
ICPC-2
ICD-O-3
SNOMED CT
... and more
ICD-10 - National Board of Health Welfare
Sweden
United
Kingdom
LOINC (in some devices)
READ2, CTV3 currently co-exist in primary care with SNOMED CT
Secondary care: ICD 10 and OPCS 4.1
Mortality: ICD 10
5.1.5
Are there relevant domains for which you feel that - in your
country - Nationally adopted terminologies are missing?
The large majority of interviewed countries, with the exception of Austria, Slovakia, and
Spain and United Kingdom, asserted that relevant domains are not actually covered by
nationally used terminologies.
Domains mentioned spans across very different types of classes of information and use
cases. The most cited ones are:
 Lab Procedures
 Procedures
 Allergies
 Medical Devices
 Vaccines
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Future investigations can better analyze the reasons of the lack of usage of terminology for
those domains at the National Level. For example challenges related to the selection and
adoption of terminologies; lacks on agreed information models and tools for capturing those
data as structured and coded information; etc.
Member State.
Relevant domains for which is felt that Nationally adopted terminologies are
missing
Austria
No
Belgium
Yes
Health care - different domains - semantic and technical interoperability
Health care - different domains - reuse of date and administrative
simplification
Health care - patient safety and decision support
Rare diseases
Health care - research
Croatia
Yes
Most healthcare data is unstructured; clinical terminologies missing;
terminologies used mostly for administrative and financial purposes.
Czech
Republic
Yes
lab procedures - mapping to LOINC is needed
allergies - often uncoded
Estonia
Yes
We are heading towards the thinking that more and more international
terminologies could be in use. We would like an international terminology
to be use for diagnoses because ICD-10 is more for statistical uses, also
we are analyzing possible international terminologies for procedures,
administrative health services, dental care.
Finland
Yes
Anatomy, clinical status, expressed as free text in many contexts
Germany
Yes
The adopted terminologies for national do cover only a certain range of
areas. For specific applications sometimes nationally accepted and
adopted terminologies are missing (infectious disease reporting, cancer
data reporting throughout all different sections of data collection, etc.).
Projects are ongoing to evaluate the necessity of alignment of different
terminology solutions for local applications that are in place or to adopt a
new international terminology
Greece
Yes
lab procedures,
clinical procedures
Italy
Yes
Allergies (agents, type of reactions,..) - often uncoded
Illnesses (for clinical purposes)
lab procedures - locally defined
procedures (for clinical purposes)
substances (excluding the ATC classifications)
vaccinations
medical devices
Malta
Yes
Lab procedures: local dictionaries are used (rather than LOINC
)
Netherlands
Yes
Procedures
Nursing terminologies
Lab
Allergies
Medical devices
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Slovakia
No
Sweden
Yes
Several domains - in general local (and not national) terminologies are
used.
United
Kingdom
No
All the needed domains are covered by the selected terminologies, even if
activities are in progress for improving some of them.
Portugal
Yes
Vaccines
Lab analysis
Surgery procedures
Clinical Procedures, Outcomes, Complications
Medical equipment and devices
Social Context- very relevant in our country
Perioperative and intensive care
Luxembourg
Yes
Denmark
Yes
In healthcare:
- Radiology domain
- Laboratory domain - different local code systems are used, (LOINC
adoption has been started)
- Documentation of medical acts
- Allergies and Vaccinations
...
Nursing
Allergies
Spain
Norway
No
Yes
Bulgaria
Yes
Hungary
France
Yes
Yes
5.1.6
There is currently an investigation in process on selecting a terminology
for the dental domain that does not have an established national
terminology today.
In previous investigations it has been indicated possible needs for
terminology for physical variables, clinical observations, nutritions and
fluids, scoring systems and medical devices.
primary health care procedure
LAB
coded part of EHR
Health record documentation and clinical patient profiles description uncoded
Are there nationally defined terminologies used at the
national level for health and social data?
With the exception of Bulgaria, Denmark, Malta and Slovakia, all the countries declared to
use, at the national level, national defined terminologies covering very different areas. Some
recurring cases are drugs nomenclature / classification; procedures; codes for accounting
(details below).
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Member State
Nationally defined terminologies used at the national level for health and
social data
Austria
Yes
Belgium
Yes
Croatia
Yes
National version of DRG-type terminology (HZZO)
Czech
Republic
Yes
SUKL ID (national drug registration ID) - SUKL is responsible
NCLP (national list of lab procedures) - Group of vendors is
responsible
DASTA CODELISTs (national vocabulary for communication protocol
(like HL7 Vocabulary)) - Group of vendors is responsible
List of procedures (procedure -> payment) - General Health
Insurance Company
Estonia
Yes
Medical specialties - for defining the specialty of healthcare workerHealth Board;
Classification for Nations-Estonian Statistics;
List for health services-Estonian Health Insurance Fund;
many other smaller value sets.
Finland
Yes
We have over 250 classifications/ code-systems for health and social
care available via the national code server. THL is responsible.
http://91.202.112.142/codeserver/
Germany
Yes
ICD-10-GM - for diagnosis-coding of morbidity information
Alpha-ID - more detailed code for coding of diagnoses
PZN (Pharmazentralnummer) - for identification of drug packages
OPS (Operationen- und Prozedurenschlüssel) - Procedure coding
system
Greece
Yes
medical procedures for reimbursement purposes
Italy
Yes
AIC (national drug registration ID) - medicinal product identification AIFA
Gruppi di Equivalenza - medicinal product clustering - AIFA
Malta
No
Netherlands
Yes
Procedures Catalogue - Health Ministry
Intensive Care Classification - Health M
Pharma-Zentralnummer - AGES
maybe others
G-Standard - Pharmacy: Z-index
PALGA - Pathology: Palga
NHG tables - Modified ICPC: NHG
DBC - Equivalent of DRG’s
Cineas - Rare deceases
Slovakia
No
Sweden
Yes
National/Regional classifications for procedures
United
Kingdom
Yes
OPCS4 - procedures
READ codes (Clinical Terms Version 3)
Imaging codes
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Member State
Nationally defined terminologies used at the national level for health and
social data
Portugal
Yes
Portuguese Catalogue for Allergies and Other Adverse Events
(CPARA) Portuguese Ministry of Health Shared Services(SPMS)
ICNP - Nurses
. CNPEM- Drugs identification- Infarmed- National Authority Centre
of drugs
. Vaccines. DGS- General-Directorate of Health
. WebGDH- Medical diagnosis. ACSS- Central Administration for
Health Systems
National drug registration ID - INFARMED;
CIPE - International Classification Nursing Practice (Ordem dos
Enfermeiro);
SICD/E - Sistema Informático de Classificação de Doentes em
Enfermagem
CNPEM - SPMS/Infarmed - National Drug Authorty
Vaccines - DGS (Directorate General of Health)
PRVR (Prescribers authentication Portal) - SPMS
Luxembourg
Yes
Cefip - Medical products: C.E.F.I.P
CNS Catalogue - Medical act / Billing: CNS
Care act catalogue / Billing: Cellule d'évaluation et d'orientation de
l'assurance dépendance
Denmark
Spain
No
Yes
Norway
Yes
Bulgaria
Hungary
France
No
Yes
Yes
CN National Code for Medicines
ICD-9-CM
ICPC-2
ICD-O-3
SNOMED CT
... and more
There are a large set of national code sets - around 900 code sets
are published at the Norwegian Directorate of Healths portal Volven.
pharmaceutical product identification - Health Insurance Fund
CCAM, CSARR, NABM, NGAP: all are medico-economical
classifications (national health insurance / health Ministry)
CLADIMED: classification of medical devices (association)
UCD, CIS, CIP and DC: drugs (ANSM)
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5.1.7
How the nationally adopted terminologies are are managed
(administration; authoring ;…)?
The authoring and administration of the terminology assets (value sets, code systems,..)
seems to be in most cases ( about 50%) managed not using terminology systems/services,
but using alternative solutions as for example by means of excel files. A quite similar
percentage of countries declare, however to use also a set of terminology systems, while
only about the 20% declare to use central terminology systems (Sweden, UK and Spain).
Details below.
Member
State
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
Central
terminology
management
system
No
No
No
No
No
Set of terminology
management
systems
Central
terminology
service
I don’t
know
Yes
No
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
Yes
No
Yes
No
No
No
No
No
No
No
Yes
No
Yes
No
Yes
Yes
No
No
Yes
No
Yes
No
No
No
No
No
Yes
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
No
No
No
No
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
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Other











Belgium: define "terminology management system"
Croatia: MS Excel Spreadsheet
Czech Republic: mostly in MS Excel
Estonia: some are managed in our organization, some in other organizations
Germany: Not specified
Greece: no enforcement for common data sets
Hungary: each terminology is managed by the relevant authority
Italy: local solutions (e.g. excel)
Luxembourg: Proprietary databases
Malta: They are managed manually using standard office automation tools, without a
specific terminology management system.
Netherlands: Each terminology has its own tooling and/or excel sheets
Additional Information
Austria
Procedures and IC maintained yearly,
Pharma - connected to authorization
Belgium
Basic systems: Locally developed applications, flat files, ...
A central terminology management system, with authoring is lacking.
Croatia
Currently, no system for national DRG-type terminology administration is used. DRGs
are managed via MS Excel Spreadsheets. Updates are managed manually at HZZO.
Estonia
We do not have common system for managing terminologies, usually the organization
that develops the terminology will also be the manager in the future. But this is in some
change in Estonia at the moment, some of the terminologies are moving to our
organization.
Finland
We have a code server and a system of expert groups (20+) for defining and upgrading
the codes/classifications.
Germany
DIMDI uses a central terminology and classification management system for most of its
classifications
Greece
some terminologies has been brought to Greece in Greece by the national school of
public health
some others via Universities and Academia
some adopted by the MoH
no basic maintenance scheme
the eP system has increased awareness and national needs.
Hungary
a central terminology system used for distribution (but not really for authoring) is in the
implementation phase
Classifications and code sets are managed by the Norwegian Directorate of Health.
Mesh is organized by Kompetansesenteret.
Clinical terminologies Centre in Portugal is governed by SPMS, ACSS and DGS, three
bodies inside the PT Ministry of Health (Centro de Terminologias Clínicas em Portugal
http://www.ctcpt.net/ )
Classifications and terminologies are maintained and governed or extended by
different units, under same Direction General
The international/national/regional classifications are managed by the unit for
classifications and terminology at the National Board of Health and Welfare.
The SNOMED CT release centre is located in a different part of the NBHW.
Norway
Portugal
Spain
Sweden
United
Kingdom
A number of bespoke tools for terminology editing/distribution, request submission,
mapping to classifications and supporting mapping from legacy terminologies. In the
order of 5/6 different tools. Authoring Tooling pre-existed IHTSDO workbench.
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5.1.8
How the nationally adopted terminologies are
available for usage?
made
Almost all the countries use the Web publication as a mean for distributing terminologies.
Only 7 (Netherlands; Estonia; Greece; Spain; Austria; Finland; Czech Republic) over 22
(about 30%) declare to use local or central terminology services.
Member State
Austria
Belgium
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
Central terminology
server
Yes
No
No
No
Yes
No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Local terminology
services
No
No
No
No
No
No
Yes
No
No
No
Yes
No
No
No
No
Yes
No
No
No
Yes
No
No
Published on the web
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Other

Belgium: Made available as reference files, in some cases integrated through APIs
with data capture screens.
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


Portugal: sent by email, after a contact is made with the responsible authority
Spain: Reference Terminology Server is under deployment
Sweden: via email exchange
Additional Information
Bulgaria
Estonia
excel, pdf
See above, delivered via the code server, also published guides for usage
Finland
International and national terminologies and classifications are published on the
open web via the code server. They all can be downloaded as Excel sheets, XML
and. text formats. In addition some major classifications are available as
published/electronic books (ICD-10, Surgical procedures). When a license to
share the codes openly via the web is needed, it has been asked for from the
license owner. Some licenses have costs that are covered with state funding from
THL budget.
Germany
Excel spreadsheet containing the national DRG-type terminology is published on
the web and publically available.
Discussions about the need for a central (national) terminology server have
recently started, but today it doesn't exist.
Hungary
Malta
a central terminology system is in the implementation phase
Published on the web
Norway
Spain
National terminologies are made available at www.volven.no.
Reference Terminology Server is under deployment
5.1.9
Tools and technologies that have been applied in your
country for facilitating the usage of nationally adopted
terminologies by end users
About 40% of countries asserts that no tools or technologies are used for facilitating the
usage of nationally adopted terminologies. Most of the mentioned tools refer to solutions for
supporting the access and distribution of terminologies (terminology servers, web browsing
tools...); few refer to user interfaces solution to help code selection. Further details in the
following table.
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Member
State
Please describe what tools and the technologies have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users
Austria
Yes we have : see
notes
Belgium
We do not have any
Bulgaria
Croatia
I don’t know
We do not have any
Czech
Republic
We do not have any
Denmark
Yes we have : see
notes
Estonia
We do not have any
Finland
Yes we have : see
notes
France
Germany
We do not have any
Yes we have : see
notes
Greece
Yes we have : see
notes
Hungary
Italy
We do not have any
We do not have any
Luxembourg
Yes we have : see
notes
Yes we have : see
notes
Provisioning of data exports for import in third party systems
to integrate in their applications.
In some systems (e.g. Electronic Case Summary system), ad
hoc software functionality facilitates the choice of terms for
diagnoses, procedures and pharmaceutical products.
Standard internet-based browsing tools and other reference
materials are also used.
Netherlands
Yes we have : see
notes
We use the ART-DECOR platform for browsing, editing and
extension mismanagement. The SNOMED CT NRC is also
using SnowOwl.
Norway
Yes we have : see
notes
Yes we have : see
notes
Several of the terminology servers expose content through
web-services
Publication by a National Guidelines Authority (DGS)
Official notification by national authorities responsible by
them
Meetings, workshops, etc.
Local education by peers
Malta
Portugal
Slovakia
We do not have any
Spain
Yes we have : see
notes
Sweden
Yes we have : see
notes
Public terminology server,
published on health ministry website www.bmg.gv.at;
www.gesundheit.gv.at
Central file distribution
Implementation Guidelines
Subsets
The national code server, usage guide books, information on
the code server web site.
The tool in use for most classifications provided by DIMDI is
a toolkit that was developed in a joined effort with WHO and
which is specially customized to fit the needs of classification
and terminology users (CTK, i.e. Classification Tool Kit).
Some terminologies available via the web by MoH or other
institutes.
Models and terminologies are made available via Internet.
Workshops are organized with participants from every region
(individually)
Web browsers for ICD10 and SNOMED CT
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Member
State
Please describe what tools and the technologies have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users
United
Kingdom (*)
Yes we have : see
notes
Distribute browsers for terminologies.
End user can browse the content in order to make a subset
User Interfaces:
No national requirement. National procurement of EHRs
required SNOMED CT to be included and thus left with
system supplier.
Some guidance on user interfaces provided.
5.1.10 Methodologies applied in your country for facilitating the
usage of nationally adopted terminologies by end users
The following table reports the answer provided by the responding countries. Several
responses seem to be related more to technological solutions used rather than
methodologies applied; those answers can be however interpreted as a way for facilitating
the accessibility to terminologies and classified in such a way.
Member
State
Please describe what are the methodologies that have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users -
Austria
Public terminology server,
published on health ministry website www.bmg.gv.at; www.gesundheit.gv.at
Belgium
e.g. Implementation of the MLDS of IHTSDO that can be used to distribute RF2 files,
and other services made available by IHTSDO
Bulgaria
Croatia
there are not methodologies
There is no methodology used for facilitating the usage of nationally adopted
terminologies by end users
Czech
Republic
All is distributed simply by implementation in software (HIS/LIS)
Denmark
Newsletters
Implementation guidance
Support end users via NRC's
Estonia
We basically have the obligations from the legislation that make the end users use
the nationally adopted terminologies.
Finland
Available free of charge via web, wide participation of experts from different
stakeholder groups, published guides, workshops, training, legislation
France
Germany
Methodologies applied to help the usage of terminologies are based on regulatory
requirements.
Some national terminologies are mandatory to use by law, e.g. the ICD-10-GM
Greece
n/a
Hungary
Italy
no one
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Member
State
Please describe what are the methodologies that have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users -
Luxembourg
Since they are used for billing purposes / reimbursement, there is vital interest of the
participants to use.
Not yet forced by law to use other Terminologies like e.g. CCAM, but on the way.
Malta
In some systems (e.g. Electronic Case Summary system), ad hoc software
functionality facilitates the choice of terms for diagnoses, procedures and
pharmaceutical products. Standard internet-based browsing tools and other
reference materials are also used.
Netherlands
Initially topic focused projects were supported by the NRC when opportunity came
up. Now Snomed is also designated as the clinical terminology in some national
projects like Diagnoses thesaurus for hospitals, clinical building blocks for university
hospitals and national nursing problem list.
Norway
Today there are few formal methodologies for facilitating the usage of nationally
adopted terminologies.
However, Norway has a set of eLearning-programs for facilitating understanding and
use of the most the most used terminologies, classifications and code sets.
Portugal
mandatory use of terminologies for software
"Education measures
Going into the ""field"" and talk to physicians
Announcement through the media: TV, radio.. "
"Creation of a National Competence Centre for Terminologies.
Tender to acquire Specialized Terminology
Management SAAS - HealthTerm
Interoperability team (Technical and SEmantic) responsible for terminologies
supervision, implementation guidance and management. "
By the issue of directive and guidelines from the DGS (Directorate-General of
Health).
"Publishing on websites the docs
Making databases available with the data to vendors"
Local education by peers
https://interop-pt.atlassian.net/wiki/display/CTCPT/English+version
web distribution of cancer registry data
Software installation
Meetings, workshops, etc.
Through de national electronic health patient record (Sclinic)in use for all the national
health service
Training users of information systems with the terminologies in use; Disclosure about
the use of terminology; working groups
National implementation by law
Slovakia
Administrative Activities
Spain
Three step approach: mind map, grid-mockup, archetype; terminology binding;
refsets for main data elements from the CMDIC regulation; development of a
reference terminology server; development and hosting of a modeling server.
Sweden
Training of users and implementers.
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Member
State
Please describe what are the methodologies that have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users -
United
Kingdom
Support for contents:
Identify the “content” that experts want in a system, match to equivalent content in
SNOMED CT.
A number of subject matter experts who provide the NRC with editorial and
implementation guidance and support decision making in relation to the UK
Extension and implementation products and guidance. There is regular engagement
with national professional bodies on the development of both content and refsets.
Education:
- Guidance, workshops, webinars
Based on the responses provided a set of classes have been identified and answers
remapped into them. The following table and figure summarize this classification.
Member State
Austria
Belgium
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United Kingdom
Facilitated
access
No specific
methodologies
applied, No
Answers
Normative
requirement
Education
Stakeholder
involvement
Smart GUI
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
future
X
X
X
X
X
X
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5.2
5.2.1
About SNOMED CT adoption and usage
Which approach has been followed in your country for
introducing SNOMED CT as a terminology for health and/or
social care data?
Almost all the countries that has, or is going to introduce SNOMED CT, has indicated the
project / use case based approach as the reference approach, with the exception of
Sweden, Portugal and United Kingdom (top down approach). A mixed approach should be
however considered for those countries, as explicitly mentioned in the UK response. For
what concern Netherlands the project based approach used in the startup phase, is
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progressively turned towards a centrally managed approach (embedded in national policy
documents and projects).
Member
State
Which approach has been followed in your country for introducing SNOMED
CT as a terminology for health and/or social care data-
Austria
Not Applicable (e.g. not an IHTSDO member country)
Belgium
On projects / use cases basis
Croatia
It is still under evaluation
Czech
Republic
Not Applicable (e.g. not an
IHTSDO member country)
Estonia
On projects / use cases basis
Finland
It is still under evaluation
Germany
Not Applicable (e.g. not an IHTSDO member country)
Greece
It is still under evaluation
Italy
Not Applicable (e.g. not an IHTSDO member country)
Malta
On projects / use cases basis
Netherlands
Formerly on projects / use cases basis. Now it is increasingly embedded in national
policy documents and projects.
Slovakia
It is still under evaluation
Sweden
Top down approach, e.g. as part
of a National project
So far national Projects have been considered the
best approach, but since interest and level of
knowledge of SNOMED CT is growing, the next
step will probably be "use case basis" with
support from the national level.
United
Kingdom
Top down approach, e.g. as part
of a National project
A mixture of 1 and 2.
Portugal
Top down approach, e.g. as part
of a National project
Luxembourg
Denmark
Spain
Norway
It is still under evaluation
On projects / use cases basis
On projects / use cases basis
Not Applicable (e.g. not an
IHTSDO member country)
Bulgaria
Not Applicable (e.g. not an
IHTSDO member country)
Hungary
Not Applicable (e.g. not an
IHTSDO member country)
France
It is still under evaluation
Ministry of Health just paid the license fee. No
central strategy, no university research.
So far, SNOMED CT has been used in specific
situations, e.g. to guide the construction of local
dictionaries, and in specific projects, such as the
National Patient Summary and the epSOS
Project. It is expected to be used on a wider
basis in upcoming National projects, such as the
National Electronic Health Record and the
National ePrescription System.
HCDSNS is the umbrella for adoption.
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5.2.2
For which use cases/purposes is currently used SNOMED
CT in your country?
The following table reports the answer provided. Use cases/purposes have been described
at a very different level of detail, in dependence also on how the usage of SNOMED CT in
that country is wide.
Member
State
For which use cases/purposes is currently used SNOMED CT in your country
Austria
Maybe in international research activities.
Belgium
Use cases under development
Bulgaria
Croatia
hospital care
SNOMED CT is currently not in use.
Czech
Republic
none
Denmark
SOR - Health organisations registry
Microbiology - MIBA
Drug terminology
Nursing
Decision support (drug prescription)
Pathology use case; infectious disease use case; defining the technical data field.
Estonia
Finland
We have not so far identified only the use of old versions of SNOMED CT in
pathology. We participated in epSOS-project in defining Patient Summary but did not
pilot it. epSOS eP was piloted.
France
Germany
SNOMED CT is currently used for research projects and in healthcare solutions
embedding it (Philips, intensive care units).
Not applicable
Greece
for R/D projects.
Hungary
Italy
not applicable
Research (limited use); International projects;
Luxembourg
Malta
Not used yet
Creation of clinical vocabularies based on SNOMED CT concepts, with mapping to
standard classifications (ICD-10, ICD-9-CM, ATC).
Coding of other clinical concepts as the need arises.
Coding of concepts in the Electronic Case Summary system and the National Patient
Summary system (pilot project).
Netherlands
National Diagnosis reference set for hospital
Ophthalmology diagnosis and procedures reference set
Clinical research databases
Norway
Portugal
Slovakia
Spain
Sweden
Pathology
Allergies
Not decided yet
Medicines interoperability between regions (large deployment).
Data elements from EHR minimum dataset.
National coding system for safer prescribing of drugs (not yet live).
For transfer of patient data to registries ("quality registries") - going live in 2015.
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Member
State
For which use cases/purposes is currently used SNOMED CT in your country
United
Kingdom
In England used in many settings including primary care, secondary care, community
care and mental health.
Used for recording all reusable information pertinent to delivery of health care - most
commonly for procedures and diagnoses though expected to expand as systems
become more sophisticated.
Also beginning to be used for secondary uses extracts.
5.2.3
In which care settings is SNOMED CT used?
Twelve countries of the twenty-two responding (> 50%) do not consider applicable for the
usage of SNOMED CT any of the care settings indicated.
Only UK seems to have a wide coverage spanning over almost all the care settings.
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Prevention &
health
promotion
Primary care
Primary
prescribing
Inpatient:
Elective &
Day case(*)
Inpatient:
non-elective
Outpatient
Other
secondary
care
Ambulance
Accident and
Emergency
Community
care
Care
provided in
other setting
Non
health/social
care
Other
X
X
X
Un. Kingdom
Sweden
Spain
Slovakia
X
Portugal
X
Norway
Luxembourg
X
Netherlands
Italy
X
Hungary
Greece
X
Germany
X
France
Czech Rep.
X
Finland
Croatia
X
Estonia
Bulgaria
X
Denmark
Belgium
Not
Applicable
Austria
Member
State
Malta
ASSESS CT – D1.3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
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(*)
Patient that comes into hospital for treatments/procedures and is dealt with and released in the
course of one day.
Other



5.2.4
Finland: We suspect possibly some use in pathology
Denmark: Microbiology, SOR
Spain: Medicines e-prescription and dispensation
For the indicated use cases how SNOMED CT is actually
used?
Thirteen countries (AT, BE, HR, CZ, FI. DE, GR, IT, NO, HU, LU, SK) of the twenty-two
responding (> 50%) have indicated as not applicable the question about how SNOMED CT is
actually used.
Malta and United Kingdom declare to use SNOMED CT as Reference, Aggregate and
Interface Terminology;
France as reference and aggregate terminology for the indicated use cases (research):
Netherlands, Spain, Portugal and Estonia as Reference terminology.
When used as reference terminology SNOMED CT it is often used also for capturing data,
with the exception of France and Portugal.
Sweden (“Other”) indicated that “codes are used for transfer of patient data to registries, but
not yet for data capture/patient records”, that seems to fall into the aggregate case.
Denmark (“other”) that is used for “data harmonization”.
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Interface
terminology
(capturing patient
data)
Reference terminology (recording
patient data with unique codes
and precise, formal meaning)
Austria
Not Applicable
Belgium
Not Applicable
Croatia
Not Applicable
Czech
Republic
Not Applicable
Estonia
Yes
Yes
Finland
Not Applicable
Germany
Not Applicable
Greece
Not Applicable
Italy
Not Applicable
Aggregate terminology
(classifying patients based on
their characteristics)
Other
No
No
Malta
Yes
Yes
Yes
No
Netherlands
Yes
Yes
No
No
Slovakia
Not Applicable
Sweden
No
No
No
Yes
United
Kingdom
Yes
Yes
Yes
No
Portugal
No
Yes
No
No
Yes
Luxembourg
Not Applicable
Denmark
No
No
No
Spain
Yes
Yes
No
Norway
Not Applicable
Bulgaria
Not Applicable
Hungary
Not Applicable
France
No
Yes
Yes
No
Other


Sweden : “codes are used for transfer of patient data to registries, but not yet for data
capture/patient records”
Denmark : “data harmonization”
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5.2.5
For the indicated use cases what of SNOMED CT do you
actually use?
Coherently with the previous answer, the same 13 countries have indicated this question as
not applicable.
All the remaining countries (EE, MT, NL, SE, UK, PT, DK, SP. FR) use the SNOMED CT precoordinated concepts, two of them use also the compositional syntax (NL, UK) , and two (NL,
DK) declares to use the full SNOMED CT description logic.
Member State
Pre-coordinated concepts
Compositional Syntax
(post-coordination)
Austria
Not Applicable
Belgium
Not Applicable
Croatia
Not Applicable
Czech Republic
Not Applicable
Estonia
Finland
Yes
No
Full description logic
(concepts,
relationships...)
No
Not Applicable
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Member State
Pre-coordinated concepts
Compositional Syntax
(post-coordination)
Germany
Not Applicable
Greece
Not Applicable
Italy
Full description logic
(concepts,
relationships...)
Not Applicable
Malta
Yes
Netherlands
Yes
Slovakia
No
No
Yes
Yes
Not Applicable
Sweden
Yes
No
No
United Kingdom
Yes
Yes
No
Portugal
Yes
No
No
Luxembourg
Not Applicable
Denmark
Yes
Spain
Yes
No
Yes
No
No
Norway
Not Applicable
Bulgaria
Not Applicable
Hungary
Not Applicable
France
5.2.6
Yes
No
No
Did (or will) the introduction of SNOMED CT in your country
affect existing terminologies
For about half of the countries interviewed (~ 40%) no impact on existing terminologies are
expected by the introduction of SNOMED CT in their country.
Member State
Did (or will) the introduction of SNOMED CT in your country affect existing
terminologies
Austria
Not applicable
Belgium
No
Bulgaria
Croatia
Not applicable
No
Czech
Republic
No
Denmark
Estonia
No
Yes
As a general principle, SNOMED CT is not considered
to be a competitive system
After Snomed CT is translated (if ever), harmonization is
perceived in all matching domains.
We will replace the national terminologies with the
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SNOMED terminology.
Finland
Yes
France
Germany
No
Yes
Greece
Yes
Hungary
Italy
Not applicable
Yes
Luxembourg
Yes, please indicate
which one
Malta
No
Netherlands
Yes
less local terminologies
Norway
No
Portugal
Yes, please indicate
which one
Snomed CT is still under evaluation and we do not
currently have the full overview over consequences for
existing terminologies.
ICD-0-3
ICD-9-CM
ICD-10
CPARA
Slovakia
No
Spain
Yes, please indicate
which one
No
ICPC-2 will be deprecated
Yes
READV2 CTV3 NICIP
Sweden
United
Kingdom
5.2.7
All of them
All national terminologies for the use in the medical field
might be affected because intense mapping and
adaption is needed before joined use. Parallel use of
two systems can only be handled, if automatic joined
use is possible. Otherwise the additional workload for
the user will be tremendous.
Therefore the national and international terminologies
currently in use in Germany will have to be revisited,
mapped or adapted one by one
ICD-9-CM
It is too early for us to give definite answer but we
expect to replace locally used terminologies, for
communication between actors in health sector.
Behavioral changes may be necessary, but no
substantive impact is expected on existing terminologies
per se.
Could you briefly describe what has been (or what will be
according to your current evaluation) the impact of the
introduction of SNOMED CT in the existing IT architecture
(including software)?
The following table reports the answer provided for this question.
Member State
Could you briefly describe what has been (or what will be according to your
current evaluation) the impact of the introduction of SNOMED CT in the
existing IT architecture (including software)
Austria
SNOMED CT introduction not decided.
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Member State
Could you briefly describe what has been (or what will be according to your
current evaluation) the impact of the introduction of SNOMED CT in the
existing IT architecture (including software)
Belgium
This depends on the implementation approach. Different implementation
approaches are possible with different impact.
Bulgaria
Croatia
will be very helpful
IT architecture will have to be changed significantly.
Czech Republic
Snomed CT is too complex for current level of ICT industry.
Anyway establishing a central terminology service will be the first step.
Denmark
Estonia
no comments
So far the adoption hasn´t influenced because we have used the RefSets that fit
into our IT architecture. Possible impacts in the future we haven´t analyzed very
thoroughly so far.
Finland
Chosen subsets from SNOMED CT would be mapped to existing terminologies.
This would likely mean some changes to the used ones. Since everything is
digital in Finland, all changes mean changes in national and local health care ICT
systems such as EPRs, but the main components, the way the health information
infrastructure is structured (information architecture) would not change
France
We anticipate that the introduction and adoption of SNOMED CT will promote (i)
the development of industrial solutions for patient-centered care provision, (ii) the
development of new services for secondary use of care data, (iii) the development
of transversal services to support the access to semantic resources, and (iv) help
provide contextual access to knowledge-based resources.
not applicable
Germany
Greece
Hungary
Italy
The large adoption of terminology at the national level (not limited to SNOMED
CT) should require the development of a semantic infrastructure (Terminology
servers/services) at the national level. (including also the support for the
mappings).
This would also implies the adaptation of the consumer systems.
Moreover it will require the update of most of the used EHR-S (e.g. that used by
GPs) for facilitating the capture and the representation of structured and coded
data.
Luxembourg
Aim to use fully coded documents, terminology server aimed to be provided,
terminologies need to be synchronized and used in primary care applications.
Malta
The impact is expected during the introduction of SNOMED CT in major projects
at national level (National EHR, National ePrescription system). The aim is to
include look-up and capture of SNOMED Clinical Terms within the core
functionality of the software.
Netherlands
On one hand more complex as implementing Snomed the 1st time is really
different than other content
On the other hand less complex as the number of sources will reduce.
Norway
Currently the primary goal is to adopt Snomed CT for domains that lacks
sufficient terminology.
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Member State
Could you briefly describe what has been (or what will be according to your
current evaluation) the impact of the introduction of SNOMED CT in the
existing IT architecture (including software)
Portugal
It will take major adaptation of software to refer to SNOMED CT
It will take development and the building of interfaces
It will require mapping between SNOMED CT and other codes (national and
international), using HL7 and for pass records purposes.
The impact will be great, most of the systems are not prepared to adopt a coding
system like SNOMED CT.
it has not been enough time for changes to occur
we are still in the beginning, and our IT architecture is very asymmetric between
institutions.
APIs will be created to allow for researching the unified terminology.
We did not do such evaluation yet
Slovakia
Spain
Sweden
United Kingdom
Strong contribution to interoperability, if used according to well defined clinical
models.
Very Little experience of this so far, but it has started discussions about the need
for a national terminology server.
redesign of the business processes
re-engineering of the IT system for supporting the new processes
X
X
X
X
X
X
X
X
United Kingdom
Sweden
X
X
X
X
Spain
X
X
X
Slovakia
Portugal
X
Norway
X
Netherlands
Malta
X
Hungary
X
Greece
X
Germany
X
France
X
Finland
X
Estonia
X
Denmark
Luxembourg
Czech Republic
Croatia
Bulgaria
Italy
Update of the
existing EHRSystems
Semantic
Infrastructure (e.g.
Terminology
Services/Systems)
Under Evaluation
Answers to be
clarified, no
answers
General changes in
the ICT architecture
Changes due to the
redesign of the
business process
Other
Belgium
Austria
The answers about the experienced, or expected, impacts of the introduction of SNOMED
CT in the existing IT architecture (including software) can be classified according to the
categories listed in the following table. It is interesting to note how UK faced the problem
starting from the Business Architecture from which all the other consequent impacts can be
derived, following an Enterprise Architectural approach.
X
X
X
X
X
X
X
X
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5.2.8
Could you briefly describe what has been the main
challenges (or what will be according to your current
evaluation) of the transactional scenario (i.e. moving toward
the adoption of SNOMED CT)?
The following table reports the answer provided for this question.
Member State
Could you briefly describe what has been the main challenges (or what will
be according to your current evaluation) of the transactional scenario (i.e.
moving toward the adoption of SNOMED CT)-
Austria
N.A. SNOMED CT introduction not decided!
Belgium
Training, education and information of users and software providers, translation,
vendor engagement, regulation
Croatia
Changes will have to be made on legal, organizational, semantic and technical
levels. Challenges are expected on all levels.
Czech Republic
1) Translation of Snomed CT (substantial work)
2) Education of all HIT industry.
3) Education of healthcare professionals to understand the need for coding.
Estonia
Translation has been one of the challenges. And also from technical point of view,
how to unite SNOMED CT logic and HL7 v3 based CDA documents
Finland
We need to do the mapping. The main challenges is that we have lots of
information structures that are missing form SNOMED CT.
Germany
Not Applicable
Greece
a five to ten yards plrs
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Member State
Could you briefly describe what has been the main challenges (or what will
be according to your current evaluation) of the transactional scenario (i.e.
moving toward the adoption of SNOMED CT)-
Italy
end users acceptance
support for mapping
system usability
terminology governance
translation
Malta
Although the initial challenge is to establish and implement the necessary
software functionality, the main challenge is likely to be the changes that will be
required in the behavior of health professionals.
Netherlands
- availability of Dutch terms/concepts
- adoption by caregivers
- adoption by vendors
Slovakia
- training of the workforce,
- setting up of training establishment
Sweden
There's very little tradition of using standardized/controlled terminology in patient
data documentation and the level of maturity when it comes to using such
systems has been fairly low.
United Kingdom
Change all the supporting administration tasks including payment, measure of the
activities, quality measures.
(It was not just a problem of mapping but of redesign of the whole business
process)
Portugal
cultural adaptation; adoption of new tool; perceiving of SNOMED Ct advantages
Implementation in the different health Software present in the PT Health System
Human and Financial resources in order to implement it
Human resources in order to promote adoption
Political elections coming soon
Resistance from Health and Non-health professionals
Education in order to build critical mass in PT, regarding SNOMED CT
the mapping between Snomed CT and other terminologies before implementation
stage
Raise the awareness with the software vendor and the internal development
teams.
The training of physicians
the people are not very receptive to change their ways to deal with classifying
information
incorporation in obsolete it systems
Software Usability
Getting the different health centers to adopt the new unified terminology, as they
are used to their own.
I have no knowledge on this topic
Many languages and informatics systems in use
resistance to change
- Political decisions
- Motivation and convince the health professionals
- Knowledge acquirement in the sector, finding and supporting experts
- Tools provisioning
- Editors to integrate in their products
Luxembourg
Denmark
Spain
Reimbursement is using another classification system.
No national decision for general use of SNOMED CT
Poor applications support.
Detractors (very badly informed, but very active).
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Member State
Could you briefly describe what has been the main challenges (or what will
be according to your current evaluation) of the transactional scenario (i.e.
moving toward the adoption of SNOMED CT)-
Norway
Bulgaria
Hungary
The evaluation has not come far enough to conclude on this.
will be very useful
Expected challenges are: translation, mapping to existing terminologies, end user
acceptance
The main challenge will be to leverage the development of industrial tools to mask
the complexity of the terminology to end-users.
France
Answers to be clarified, no
answers
End users Acceptance &
Education
Vendors (Engagement,
Education & Systems maturity)
Implementation with Info
Models
Translation
Mapping
X
X
X X
X
X X
X
X
X
France
Hungary
Bulgaria
Norway
Spain
Denmark
Luxembourg
Portugal
Czech Republic
Italy
Greece
Slovakia
Estonia
Belgium
United Kingdom
X
X X
X X X X
X
X X X
X
X
X
X
X X
X
X
Terminology governance,
Policy and normative Support
System Usability
Business process changes
5.2.9
Netherlands
X
X
Lack of knowledge and
resources (human & financial)
Croatia
Sweden
Germany
Finland
Malta
Austria
Based on the responses provided a set of classes have been identified and answers
remapped into them. The following table and figure summarize this classification.
X X
X
X X
X
X
X
X X X
X
X
X
X
X X X
X
X
X
X X
Could you briefly describe how those challenges have been
managed (or are planned to be managed)?
The following table reports the answer provided for this question.
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Member
State
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembour
g
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
Could you briefly describe how those challenges have been managed (or are
planned to be managed)
N.A. SNOMED CT introduction not decided!
Training, education: participating into IHTSDO's SNOMED CT Foundation and
Implementation courses
International collaboration efforts on translation accord to IHTSDO translation
guidelines
Actualization of the National Action Plan for e-health
there are the main strategy in MoH with connection of eHealth
If SNOMED is accepted in Croatia, HZZO will coordinate all the activities regarding the
implementation on all levels. Currently, there is no strategy for managing SNOPMED
CT implementation challenges.
Such a big change cannot be planned. It will simply be revolution.
Working with the strategy for adoption of SNOMED CT as a supplement to existing
terminologies and classifications
Regarding to translations-we are working on developing our own guidelines based on
the IHTSDO-s guidelines and searching for suitable persons. Regarding to the HL7
issue we used the extra translation code next to the code element.
If we decide on the purchase of SNOMED CT license, we would start looking for
suitable subsets together with the expert working groups
These challenges would be managed by setting up a National governance of semantic
resources which would not only distribute the resources but also will provide support,
tools and training to promote and guide the implementation in commercial solutions.
not applicable
This describes how might be managed not how they have been planned to be
managed. No plan for SNOMED CT is in place.
Training
make end users aware about the value proposition
create a terminology governance group supported by well-defined policies.
Not applicable yet, just study for now
In the case of the software, the challenge will be addressed through the specification
of the software functionality and the setting of data standards.
In the case of the behavior of the health professionals; the plan is to provide training
and support and to implement terminology reference sets that are relevant to the
health professionals in question.
- Working with reference sets
- start a project for (targeted) translation of Snomed
N/A
education; workshops; internal and external actions involving national stakeholders
Improving education and awareness between IT's and non IT's.
the challenge that we might have with end users is regarding the descriptions used by
Snomed CT but this is managed through the use of synonyms
Development of workshops and events.
By educating the health professionals to understand the importance of unifying the
terms.
Stressing benefits for all intervening person in the project
By communication with the universities
Training efforts, policies formulation (explicit), demonstrate benefit for clinical safety.
Training of users and implementers
Enabling the business process to be supported by SNOMED CT
Prevent the business process by legacy terminology
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Expert Involvement
X
X
United Kingdom
Sweden
Slovakia
Portugal
Norway
Netherlands
Malta
X
Luxembourg
X
Italy
X
Spain
X
Hungary
X
Greece
France
Finland
Estonia
Denmark
Czech Republic
Croatia
Bulgaria
X
Germany
Answers to be clarified,
no answers
Education (training,
guidelines, awareness
risen)
International
Collaboration
Policy enforcement
Belgium
Austria
Based on the responses provided a set of classes have been identified and answers
remapped into them. The following table and figure summarize this classification.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Software & Tools
Updates
Focused Projects &
RefSets
Business Process
Revisions
X
X
X
X
X
X
5.2.10 Could you summarize the main steps accomplished for the
adoption of SNOMED CT
The following table reports the answer provided for this question.
Member State
Main steps accomplished for the adoption of SNOMED CT
Austria
N.A. SNOMED CT introduction not decided!
Belgium
2013: membership IHTSDO, concept selection, translation
2014: use case approach, concept selection, translation
2015: RefSetting, translation QA, updating
Croatia
First steps undertaken for stakeholder analysis. Negotiations underway.
Czech
Republic
My guess only: Approved translation of core concepts will be done in 2020
Estonia
2014 we were in analytic phase and had some test use cases
2014-today we are moving project based adoptions
Finland
We have had a small evaluation study in 2009 and some negotiations with
SNOMED CT IHTSDO and are now participating in ASSESS CT to gather more
information on SNOMED CT.
Germany
not applicable
Greece
no steps adopted yet
Italy
n/a
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Member State
Main steps accomplished for the adoption of SNOMED CT
Malta
Before 2011: evaluation of the potential of SNOMED CT
.
2011: Malta became a national member of the IHTSDO.
2011 onwards: practical use of SNOMED CT terms in the Electronic Case
Summary system, the National Patient Summary system, and the epSOS project
(2011-2014).
Netherlands
Ongoing - Training - presentations
2013 - Ophthalmology diagnose refset
2014 - Ophthalmology - Procedures refset
2014-2015 - Microbiology Organisms refset
2014-2015 - Diagnoses reference set
2015 - Nursing problem list
Slovakia
Not available yet
Sweden
2007-2010: Translation of core concepts (full translation)
2011-now: biannual releases of national extension including translated core
concepts and added national concepts.
2014: addition of national synonyms started
2014: production of refsets started
2014-2015: collaboration with other national projects such as the national
information structure initiative, national project for transfer of patient data to quality
registries; inclusion of standardized/coded terminology in national Clinical
guidelines; creation of a national coding system for reasons for prescription.
United
Kingdom
2002 creation of UK extension for SNOMED
2010 content development (national specific content and capability for creating
refsets)[proxy for involving professionals]
2010 professionally validated set of maps from old coding schemes
Work closely with IT companies in order to make them use SNOMED CT in a
standard way.
Portugal
2014-2015- Acquisition of the license for usage of SNOMED CT at a National level.
Establishment of a Reference Set for Allergies. PT Translation of these concepts.
Establishment of a NRC for SNOMED CT ant other terminologies, as a place also
to download SNOMED CT international edition. acquisition of a Central
Terminology Server. Development of National Reference Sets regarding mainly
Pathology, Nutrition, Lab Analysis and Oncology, which involves also the
translation of the terms. Involvement of vendors, academy, institutions, and other
stakeholders, in the promotion of SNOMED CT adoption. Events for external as
well as for internal teams regarding SNOMED CT. Promotion of IHTSDO SNOMED
CT eLearning Foundation Course, with 158 applicants now gathering the course.
Luxembourg
Denmark
Still evaluation
Translation of SNOMED CT to Danish - ended 2009
Establishment of a NRC
Release of the Danish extension
Spain
Extensions; site for downloading; quality of translations efforts. Workshops
organization.
Project established September 2015 for evaluating Snomed CT
not applicable
not applicable-
Norway
Bulgaria
Hungary
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Member State
Main steps accomplished for the adoption of SNOMED CT
France
2014 - 2015 : elaboration and distribution to all stakeholders of a pedagogic
document presenting the definitions, concepts and tools related to semantic
interoperability
2015 : Interviews of about 35 organizations in France and abroad to elicitate the
French needs in terms of reference terminologies
2015 - 2016 : Argument proposals to the French Health Ministry for the setup of a
National governance for semantic resources along with a calendar to first adopt 2
new terminologies: ICPC-2 and SNOMED CT.
5.2.11 What has been the content selection approach applied (or
planned to be applied) for introducing in your country
SNOMED CT?
For the about half of the countries interviewed the actual or planned approach for the
introduction of SNOMED CT has not been yet identified, or the question is not applicable.
Considering only the positive responses (9) in four cases (DK, UK, SP, SE) the full SNOMED
CT core has been considered; while, a RefSet based approach has been chosen by the
other 5 countries (MT, NL, BE, PT, EE) (55 %).
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Austria
Belgium
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United Kingdom
Full Core SCT
+ Extensions
Full Core SCT
National
RefSets
Use cases
specific
No Answer,
still under
evaluation
Not
Applicable
ASSESS CT – D1.3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
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5.2.12 Who was (is planned to be) responsible for selecting the
contents?
Clinicians and Terminology Experts
Under evaluation
Not Applicable.
Mainly Clinicians
0%
10%
20%
30%
40%
50%
60%
About half of respondents indicates the “Clinicians and Terminology Experts” the role
involved (or to be involved) in the refset selection, while about the 35 % consider this topic
not applicable or under evaluation.
Member State
Austria
Belgium
Croatia
Czech Republic
Estonia
Finland
Germany
Greece
Italy
Malta
Netherlands
Slovakia
Sweden
United Kingdom
Portugal
Luxembourg
Denmark
Spain
Norway
Bulgaria
Hungary
France
Responsible for selecting the contents
Under evaluation
Mainly Clinicians
Clinicians and Terminology Experts
Not Applicable
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Under evaluation
Not Applicable
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Under evaluation
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Under evaluation
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Clinicians and Terminology Experts
Under evaluation
Not Applicable.
Under evaluation
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5.2.13 For supporting the indicated use cases, which selection
approach has been applied in your country?
The percentage of not applicable or under definition answers increase to more than 60% for
the same type of question applied to the indicated use cases (i.e. not only for the introduction
of SNOMED CT). Only UK indicated that “The Full SNOMED CT core with national
extensions is being used, “National Refsets” have been indicated for Estonia and
Netherlands and Portugal, and “Several Refset” for Malta, Belgium, Denmark and Spain.
In the following table are summarized the answers for this question (X) with those provided
about the actual or planned approach for the introduction (Y) (see § 5.2.11 What has been
the content selection approach applied (or planned to be applied) for introducing in your
country SNOMED ).
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Bulgaria
Y
X-Y
X-Y
Croatia
Czech Republic
X-Y
Denmark
X
Estonia
Finland
Y
Italy
Luxembourg
X
X-Y
X-Y
Greece
Hungary
X-Y
X-Y
X-Y
X-Y
Malta
X-Y
Netherlands
Norway
X-Y
X-Y
Portugal
Slovakia
Y
X
X-Y
Spain
Sweden
Y
X-Y
France
Germany
Full Core SCT +
Extensions
X
Full Core SCT
Y
Belgium
National RefSets
X
Use cases
specific
No Answer, still
under evaluation
Austria
Not Applicable
ASSESS CT – D1.3
X
X
Y
Y
United Kingdom
X-Y
5.2.14 Can you quantify (and qualify) the selected SNOMED CT
Refset(s)?
The following table list the answers provided for the SNOMED CT Refset defined in each
country
Member State
Austria
Belgium
Croatia
Czech Republic
Estonia
Finland
Germany
Greece
Italy
Can you quantify (and qualify) the selected SNOMED CT Refset(s) Nursing: 32.000 concepts
Medicine: 80.000 concepts
No REFSETS currently selected.
3 pathology Refsets;
2 infectious disease Refsets.
Not available
Not Applicable
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Member State
Can you quantify (and qualify) the selected SNOMED CT Refset(s) -
Malta
(Figures are not easily available). There are three RefSets in current use:
allergies, diagnoses and medications
Ophthalmology - Diagnoses: 600
Ophthalmology - Procedures: 38
Microbiology Organisms refset: 2500
Hospital Diagnosis refset: 31 000
No areas are covered with SNOMED CT in Slovakia at the moment.
Refset: Reasons for prescription, approx. 1400 concepts
Refset: Lifestyle habits (used in connection with the national clinical guidelines
for disease preventing methods), approx. 50 concepts
Refsets with administrative concepts, approx. 10 concepts in each.
Several hundred refsets for numerous sue cases.
UK uses all of SNOMED CT Core, plus a UK Clinical Extension (more the
73,000 concepts), UK Drug (more 283,000 concepts)
A significant number of national subsets/refsets of varying content and hence
size including a number of specialties specific e.g. Renal exist. There is no
single refset for national use and suppliers utilize all of SNOMED CT within their
products.
Allergies
Lab analysis
Nutrition
Malignant Neoplasms for Oncology/Pathology
Not used yet, we are in evaluation
n/a
48 major refsets available.
66 minor refsets available.
N/A
Netherlands
Slovakia
Sweden
United Kingdom
Portugal
Luxembourg
Denmark
Spain
Norway
Bulgaria
Hungary
France
No
5.2.15 What is the approach followed for translating terms and
collect possible synonyms?
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The translation and the collection of synonyms is nationally coordinated and realized for the
majority of the countries for which this answer is applicable. The international cooperation
aspect is a key factor pointed out by Belgium in its comment.
Member
State
Approach followed for translating terms and collect possible synonyms
Austria
Not Applicable
Belgium
It is Nationally coordinated and
realized.
Croatia
It is coordinated nationally, but realized through different levels (national, subnational and
organizational).
Czech
Republic
Not Applicable
Estonia
It is coordinated nationally, but realized through different levels (national, subnational and
organizational).
Finland
Not yet defined
Germany
Not Applicable
Greece
It is coordinated and realized at subnational and/or organizational level.
Italy
Not Applicable
Malta
Not Applicable
Netherlands
It is coordinated nationally, but realized through different levels (national, subnational and
organizational).
Slovakia
It is Nationally coordinated and realized.
Sweden
It is Nationally coordinated and realized.
United
Kingdom
It is Nationally coordinated and realized.
Portugal
Luxembourg
Denmark
Spain
It is Nationally coordinated and realized.
Not yet defined
It is Nationally coordinated and realized.
Other (please add notes)
Central IHTSDO activity. Spain cooperates with QA
for translation.
Not yet defined
Not yet defined
Not Applicable
Not yet defined
Norway
Bulgaria
Hungary
France
Started nationally, completion international
cooperation
Standard English versions are used.
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5.2.16 Who is responsible for translating designations and collect
possible synonymous?
When applicable both the roles of Terminology experts and Professional translators have
been that mainly indicated in the translation of terms (only Sweden indicated also Clinicians
and Spain other without however providing further details).
The following table summarizes the “applicable” results.
Member State
Clinicians
Terminology
experts
Professional
translators
Not yet defined
Croatia
Finland
Germany
Greece
Slovakia
Sweden
Luxembourg
Spain
Norway
France
No
No
No
No
No
Yes
No
No
No
No
No
No
No
Yes
No
Yes
No
No
No
No
No
No
No
Yes
No
Yes
No
No
No
No
Yes
Yes
Yes
No
Yes
No
Yes
No
Yes
Yes
5.2.17 What are the main on-going activities?
The following table reports the answers provided about the on-going activities
Member State
Austria
Belgium
Bulgaria
Croatia
What are the main on-going activities
N.A. SNOMED CT introduction not decided!
Mapping SNOMED CT to ICD-10-PCS
Completion translation process
Review of registers
Review of ALL existing registers
No on-going activities regarding description translation.
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Member State
Czech
Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
What are the main on-going activities
Review of ALL existing registers makes sense.
see above
Extending the pathology Refsets (including translating the concepts);
we are analyzing the possibilities of creating procedure Refsets and Refsets for
administrative health services.
We are defining and delivering the national health and social care information
structure. In this work we use international classifications/coding whenever
available and do mapping like ICD-10-ICPC2
No on-going activities yet.
Not Applicable
setup a roadmap for the next years
not applicable
n/a
Evaluation
Creation of specific refsets and their mapping to standard classification (ICD-10,
ICD-9-CM, ATC).
Planning for use within national-scale eHealth projects.
Creating reference sets
Starting translation project
Validating the Snomed CT - ICD-10 (v2014) mapping
There is an ongoing national program under the Norwegian Directorate of Health
that includes activities like:
- evaluating national adoption of Snomed CT
- revise terminology for pathology (Snomed), ICPS (synonyms), adm terminologies
- identify terminologies for domains like dental, prehospital, radiation
. Mapping ICD 10 CM/PCS
. Building the Malignant Neoplasms RefSet
. Finalizing the Nutrition Catalogue
. Implementing CPARA v3.0 in the Emergency software
. Implementing CPAL in the clinical software
. Implementing a national registry for diseases at the patient portal
There are no ongoing activities at the moment.
Refsets availability.
Data elements identification using SCT concepts.
Mapping SCT procedures to PCS.
Coding of patient data needed for transfer to the national quality registries.
Providing user support to help health/social care services understand and start
implementing SNOMED CT.
National coding systems such as the reasons for prescription
The number of projects that use some form of SNOMED CT are innumerable, some
in England which are national strategic initiatives and have been in live use for
some years - e.g. Electronic Prescription Service, Summary Care Record and
Choose and Book (referrals from primary care). All of these have subsequent
phases which will extend the usage of SNOMED CT. As the UK has been working
with SNOMED for some years there are also a number of projects that are led
outside of the NRC and we provide advice as and when requested. Internationally
the UK input into the collaboration on harmonization of Medical Device
nomenclature (GMDN) with SNOMED CT. Output is expected to inform the basis
for the UK medical device extension to support prescribing, recording, and analysis
of secondary care devices.
5.2.18 Could you briefly describe your future plans?
The following table reports the answers provided about the future plans
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Member State
Could you briefly describe your future plans
Austria
Usage in ELGA has to be decided, no usage in general health documentation
within the next years.
Belgium
Complete the translation of selected terms
Complete RefSets
Complete mappings
National extension
Putting in place a terminology management system
Implementation projects
Croatia
Strategy for SNOMED CT implementation is under consideration. Further
elaboration of the strategy depends on SNOMED CT adoption.
Czech
Republic
There are attempts to institutionalize services for national terminologies in a body
with a long-term secure funding.
Estonia
We are planning to initiate the translation project with the help of IHTSDO.
Launching the first Estonian Extension. Managing and extending our existing
Refsets. Broadening the knowledge about SNOMED as well as in our organization
and also in Estonia.
Finland
We are evaluating the possible value of SNOMED CT and will use the work done
within the ASSESS project and use the national stakeholder group that is created
also for national discussions outside ASSESS. The results from the evaluation will
be given for discussion and decision making to the MoH and national authorities.
Germany
not applicable
Greece
n/a
Italy
n/a
Malta
Introduction of SNOMED CT in major projects at national level (National EHR,
National ePrescription system).
Netherlands
Translating 33 000 terms in 2015, another 100 000 in 2016
Slovakia
Translation of selected 200 terms.
Sweden
User support to selected Projects who want to start implementing a standardized
terminology/SNOMED CT in information systems.
Participate in study of national terminology server needs
United
Kingdom
- 2020 : the whole healthcare to be covered by a single terminology (SNOMED CT)
Portugal
. Expanding the RefSets
.Translating Educational Materials for SNOMED CT, in PT
.Implementing PT Catalogues in Clinical software.
Luxembourg
Stepwise bottom-up approach, Vaccinations and Patient Summary prototype
(based on epSOS/EU Guideline and national requirements).
see above
Improve coverage and traceability of translation. Preview QA.
There is an ongoing national program under the Norwegian Directorate of Health
that includes activities like:
- evaluating national adoption of Snomed CT
- revise terminology for pathology (Snomed), ICPS (synonyms), adm terminologies
- identify terminologies for domains like dental, prehospital, radiation
do not know
We are evaluating the different steps needed to be a member of IHTSDO.
Denmark
Spain
Norway
Bulgaria
Hungary
France
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5.3
5.3.1
About non-IHTSDO member countries
What are according to you the main reasons for which your
country is not currently an IHTSDO member?
The following figure shows the distribution of the reasons for which some countries are not
IHTSDO members. The percentage are calculated based on the non IHTSDO member
responding countries
Austria
Bulgaria
Croatia
Czech Republic
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Norway
The License Cost is the most cited reason, mentioned by almost all the countries (with the
exception of Austria, Bulgaria and Luxembourg). It is very interesting to note how the
perceived absence of national policies on semantic interoperability (somehow related to the
low need perception and to the absence on national programs) is indicated by almost half of
those countries, as well as no one believe that that choice is related to the limited fitness for
purpose.
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
No
Yes
No
Yes
No
Yes
No
No
Yes
No
Yes
Member State
License costs.
Change management
costs.
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Austria
Bulgaria
Croatia
Czech Republic
Finland
France
Germany
Greece
Hungary
Italy
Luxembourg
Norway
ASSESS CT – D1.3
Yes
No
Yes
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
No
Yes
No
Yes
No
No
No
Yes
Yes
No
No
No
No
Yes
No
Yes
No
No
No
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
Member State
There are no national
health programs that
justify the
membership.
There is no need of
using SNOMED CT
There is no the
perception about the
need of such a kind of
terminologies.
Lack of national
competence/decisional
centers.
Limited fitness for
purpose.
No relevant benefits
respect to other
used/usable
terminologies.
Other


5.3.2
Finland: We do not know yet what to expect as the added value, international
collaboration?
Germany: High cost for mapping to national classifications and terminologies and for
translation
Are you aware about any current or past plan, discussion or
evaluation regarding the adoption of SNOMED CT in your
country?
This question applies mainly to non IHTSDO member countries.
The following figure describes the global distribution of answers.
While this figure provides the response distribution of the Yes/No answers.
About the 70% of the respondents for the NON-IHTSDO member countries indicated that
they are aware “about any current or past plan, discussion or evaluation regarding the
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adoption of SNOMED CT” (Austria, Croatia, Finland, Germany, Italy, Luxembourg, Norway
and France).
This table reports the complete list of the provided answers
Member State
Austria
Belgium
Croatia
Czech
Republic
Estonia
Finland
Could you provide any detail about the identified adoption strategy
Yes
SNOMED CT introduction for a minor use in ELGA (national EHR
system) is under discussion
N/A
Yes
Previous discussions have been made on introducing SNOMED CT.
Unfortunately, no steps have been made on the fitness analysis for
SNOMED CT implementation.
No
N/A
Yes
Germany
Yes
Greece
Italy
Malta
Netherlands
Slovakia
Sweden
United
Kingdom
Portugal
Luxembourg
No
Yes
N/A
N/A
N/A
N/A
N/A
Denmark
Spain
Norway
Bulgaria
N/A
N/A
Yes
No
N/A
Yes
See previous answers, evaluation, discussion, possible decision making
and an implementation plan if the decision is to adopt in at least some
user cases
In the realm of different projects there has been discussion of using
SNOMED CT in the future but so far none of the discussions justified
immediate decision to adopt SNOMED CT
strategy is under revision
Very preliminary thoughts have been made at the Ministerial Level
Several years ago there was a national study on the usage of
international terminologies and SNOMED (not SNOMED CT) as well as
ICD-10 and CCAM were taken into account. At that point of time a
decision has been taken into the direction of using ICD-10 and CCAM.
As we (as the Agence eSanté) are working on the national eHealth
platform and as we are also involved in European projects related to
healthcare, we recognize a trend towards the usage of SNOMED-CT.
This is why we start an evaluation of SNOMED-CT as an Affiliate with
the aim to create a feasibility study and prototype showing the
capabilities of SNOMED-CT. The aim is to use this work for further
evaluation and discussions by the Stakeholders of the sector and the
government.
An evaluation process of Snomed CT has just begun.
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Member State
Hungary
France
5.3.3
Could you provide any detail about the identified adoption strategy
No
Yes
The adoption of SNOMED CT has been recommended by the outcomes
of the previously mentioned study. The implementation is currently
under evaluation.
Are you aware about any IHTSDO affiliate in your country?
Member State
Affiliates you know and in which context they use SNOMED CT (if
known)
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Denmark
Estonia
Finland
France
Germany
No
N/A
No
No
Yes
Greece
Hungary
Italy
Luxembourg
No
No
No
Yes
Malta
Netherlands
Norway
Portugal
Slovakia
Spain
Sweden
United
Kingdom
N/A
N/A
No
N/A
N/A
N/A
N/A
N/A
N/A
N/A
No
Yes
Yes
EuroMISE LTD - for research
Philips, PHAST and VisioMed
There are very few research license holders to our knowledge, e.g. the
University of Krefeld
n/a
- Agence eSanté that is our organization, as described in this document
- Zithaklinik, used for evaluation internally years ago, but not in use
anymore
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6
Appendix 4 - Overview
Countries (Questionnaire)
of
non-European
This report is based on responses gathered before the 2015, December 31st , covering 7
Non-European IHTSDO members Countries: Australia; Canada; India; Israel; Malaysia;
New Zealand; Uruguay.
In the following table the list of persons that kindly supported the ASSESS CT project. Work
Package 1 team would like to acknowledge them for their help.
Country
Name
Organization
Role
Australia
Australia
Matthew Cordell
Heather Grain
NEHTA
eHealth Education
Canada
India
Andrea MacLean
Sunil Sharma
Israel
Julian Zelingher
Canada Health Infoway
Ministry of Health,
Government of India
Clalit Health Services
Malaysia
Sheikh Ahmad Md.
Khadzir
Anastasiya Cassie
Alastair Kenworthy
Jorge Forcella
Terminology Specialist
Implementer and Course
Developer
Manager, Standards
Handling the e-Gov initiatives
of the Ministry of Health
Director, Medical Planning &
Development
Head of Health Informatics
Centre
Advisor
Principal Sector Architect
Director of Salud.uy
New Zealand
New Zealand
Uruguay
Ministry of Health Malaysia
Ministry of Health
Ministry of Health
Salud.uy - AGESIC
Results associated to each question are documented in the following sections following the
structure of the questionnaire.
With a single exception, for which it has not been yet possible to harmonize responses, a
single response has been reported for each country. In case of multiple responses the policy
applied has been the following: (a) textual answers have been merged; (b) the OR operator
has been applied to the multiple choices answers (i.e. the answer is Yes if at least one Yes
has been provided).
This report has been shared well in advance with respondents for their review. No change
requests have been received so far.
Evaluations and comments provided in this report refer only to the responses collected by
this questionnaire and don’t pretend to represent the global situation of the Non-European
IHTSDO member countries.
6.1
About your country
This section of the questionnaire aims to provide an overview of main characteristic of each
country.
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6.1.1
Which statement describes your country best (IHTSDO
membership and SNOMED CT adoption)?
Figure 7 - Which statement describes your country best (IHTSDO membership and SNOMED
CT adoption)
Country
Which statement describes your country best
Australia
It is an IHTSDO member and SNOMED
CT is nationally adopted for health and
social data.
Canada
It is an IHTSDO member and SNOMED
CT is nationally adopted for health and
social data.
It is an IHTSDO member and SNOMED
CT is mainly adopted for health and social
data at the organizational (e.g. hospital,
local project) level.
It is an IHTSDO member and the adoption
of SNOMED CT at the national level is in
progress.
India
Israel
Malaysia
New
Zealand
SNOMED CT has been mandated as the
preferred terminology for healthcare
information exchange for at least years.
Actual implementation has progressively
increased and more so in recent years.
Different states, specialties and software
vendors are at various stages of maturity (in
regards to SNOMED adoption)
National standard that is implemented at the
jurisdictional and local level
Implementation on national level is in
progress, depending on the decisions of the
states.
SNOMED-CT selected by Israeli MOH as
national standard in 2012. Israeli healthcare
system (HMO & Hospitals) awaiting
budgeting of transition from government
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
It is an IHTSDO member and the adoption
of SNOMED CT at the national level is in
progress.
National endorsement: SNOMED
implementation is recognized as a key
element of the national digital health strategy
going forward. It is now a requirement that all
business cases for investment in clinical
information systems, electronic medical
records and longitudinal electronic health
and wellness records support SNOMED.
NZ is a founder member. SNOMED CT is
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Uruguay
mandated for clinical information systems in
the public health sector. Implementation is
underway in a number of projects, including
the national EHR which is at the design
stage.
It is an IHTSDO member and the adoption of SNOMED CT at the national level is in
progress.
For the majority of the interviewed countries claims to have in-progress adoption of
SNOMED CT (Israel, Malaysia and New Zealand), even if New Zealand recognizes
SNOMED CT “as a key element of the national digital health strategy going forward” and that
it is “mandated for clinical information systems in the public health sector”; implementation is
moreover “underway in a number of projects, including the national EHR”. Canada and
Australia declared that is “nationally adopted for health and social data”. In India it “is mainly
adopted for health and social data at the organizational (e.g. hospital, local project) level”.
This result differs from the result for the European IHTSDO members countries for which the
“Adoption of SNOMED CT at the national level is in progress” happens for the 80% of the
cases. The other two cases (national and local adoption) have the 10%).
6.1.2
Which of the following statements apply to your country
(usage of terminologies at the national level)?
About the 80% of the interviewed countries asserts that they are using nationally adopted
terminologies for a wide range of use cases, while this case is reported by only the 40% of
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the responding EU countries. On the contrary it is quite comparable the percentage of
countries that assert to use them for secondary or administrative usages (EU 80% - NON-EU
70%).
Country
There are terminologies used at the
national level for health and social
data, for a wide range of use cases
(e.g. in a nation-wide EHR/PHR).
There are some terminologies used at
the national level for health and social
data, for very specific use cases (e.g.
prescription, pharmacovigilance).
There are terminologies mainly used at
the national level, for secondary or
administrative purposes (e.g.
reimbursement; governance; costscontrol; registries…).
There is a need for terminologies for
health and social data at the national
level (e.g. nation-wide EHR/PHR), but a
national terminology strategy is still
under discussion.
There is no need for terminologies to
be used at the national level for health
and social data.
6.1.3
Australia
Canada
India
Israel
Malaysia
New
Zealand
Uruguay
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
No
No
Yes
No
Yes
No
Yes
Yes
Yes
Yes
No
No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
Is/are there national competence center(s) for terminologies
in your country?
[N/A = No Answers]
The percentage of countries that have not national competence centers is much lower than
that of European respondents (14% NON EU compared to 40% EU); this is coherent with the
fact that this survey cover only IHTSDO member countries that are requested to establish a
National Release Center, while the EU-countries responses includes also NON-IHTSDO
member.
Country
National competence center(s) for terminologies
Australia
Yes
Canada
Yes
India
Yes
We have a national release centre that manages the SNOMED
extension. Various other groups manage other classifications etc.
Infoway is the NRC for SNOMED CT, LOINC and HL7 in Canada
We also host IHE Canada and ISO/TC215
Name still to be inserted here
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Israel
No
Malaysia
Yes
Health Informatics Centre, Ministry of Health
New Zealand
Yes
Health IT program team and SNOMED national release centre at the
Ministry of Health
Uruguay
N/A
6.1.4
Are there international terminologies used nationally for
health and social data?
All countries asserted to use international terminologies at the national level. ICD-10 (with or
without local extensions) is the most commonly used terminology, SNOMED CT is
mentioned by the 70% of respondents and only two indicated LOINC.
Country
International terminologies used nationally for health and social data: name,
scope, and - if known - who is responsible for them.
Australia
SNOMED CT (Australian extension)
AMT (Australian drug extension of SCT)
LOINC
UCUM
ICD-10AM
ICPC2 and ICPC2Plus
ISO and HL7 code systems are also used as are international statistical classifications.
HL7 vocabulary
LOINC
SNOMED CT
ICD-10-CA (classification)
CCI (classification)
UCUM
No national drug vocabulary
ICD-10, (...)
Canada
India
Israel
ICD-9-CM for in hospital diagnosis & procedure reporting
ICD-10 for mental health
Malaysia
SNOMED CT, ICD-10, ICD-9-CM,LOINC
New
Zealand
SNOMED CT international release for national EHR. emergency care systems, surgical
audit system and all new clinical information systems
ICD-10-AM, ACHI and AR-DRG for activity based funding and reporting
Read Codes (being phased out) for personal injury claims and used in primary care
New Zealand Medicines Terminology (SNOMED national extension)
ATC for drugs classification
Uruguay
SNOMED CT implementation is in progress and will be used to capture health
information at the point of care.
SNOMED will be the language of the electronic health records. ICD-10-AM is used for
clinical coding.
SNOMED CT
ICD-10
CIAP-2
CIE-O
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6.1.5
Are there relevant domains for which you feel that - in your
country - Nationally adopted terminologies are missing?
The majority of interviewed countries, with the exception of India, Malaysia and New
Zealand, asserted that relevant domains are not actually covered by nationally used
terminologies. This percentage (about the 60% for NON EU countries) is however lower than
that of EU countries asserting that there are relevant domains not covered by nationally
adopted terminologies (about the 80%).
Domains mentioned spans across very different types of classes of information and use
cases. The most cited ones are:
 Lab Procedures (as in Europe)
 Procedures (as in Europe)
 Medications
Country
India
Relevant domains for which is felt that Nationally adopted terminologies are
missing
Yes
The relationship of terminologies in local systems and local system information
models are poorly understood and not really implemented, much of the data is
collected the 'old' way and mapped to SNOMED CT - this does not deliver the
maximal benefits.
Yes
Immunization and vaccines (started)
Allergies and Intolerances
IDNT (customer request)
Drug
to name a few
No
Israel
Yes
Malaysia
No
New
Zealand
No
Uruguay
Yes
Australia
Canada
Medications - locally defined
Laboratories- locally defined
Procedures - some locally defined
Lab procedures (LOINC)
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6.1.6
How are the nationally adopted terminologies are managed
(administration; authoring ;…) and distributed?
The authoring and administration of the terminology assets (value sets, code systems...)
seems to be managed for the large majority of the cases (> 60%) using central terminology
systems/services and publishing data on the Web. Hereafter the details.
Country
Australia
Canada
India
Israel
Malaysia
Through a central
terminology
management system
Through a set of
terminology
management systems
Through a central
terminology service
Published on the Web
(e.g. RF2, ClaML, excel,
pdf...)
I don’t know
Yes
No
Yes
No
Yes
No
No
Yes
No
Yes
No
Other
Uruguay
Yes
New
Zealand
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
No
Yes
Yes
Yes
No
No
No
No
No
No
Yes
no
national
service
Additional Information
Australia
Canada
India
Primarily web access.
(terminology services) in development and role out
Infoway authors a Canadian SNOMED CT extension, a Canadian version of LOINC also known as
pCLOCD and develop subsets to meet some specific Project requirements.
Published in the web in various formats on our InfoCentral wiki, Terminology Gateway and HL7
Explorer
Indian Pharmacopeia
Israel
Malaysia
Health Informatics Council (as a Governance Agency)
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New
Zealand
Uruguay
6.1.7
We use the IHTSDO Member Licensing and Distribution System to distribute SNOMED to our
affiliates. We post our own refsets in Excel format on a website. We are moving to distribute solely
through the MLDS. The NZ Medicines Terminology is also downloadable from a website.
SNOMED CT is managed at an NRC level
Other terminologies as published on the web
Tools and technologies that have been applied in your
country for facilitating the usage of nationally adopted
terminologies by end users?
Almost all the countries assert that tools or technologies are used for facilitating the usage of
nationally adopted terminologies, in comparison with the 50% of the interviewed EU
countries. Most of the mentioned tools refer to solutions for supporting the access and
distribution of terminologies. Please refer to the following table for further details.
Country
Australia
Please describe what tools and the technologies have been applied in your
country for facilitating the usage of nationally adopted terminologies by end users
Yes
We're in the process of deploying a national terminology server, based on
FHIR APIs. This will function as an alternative way for users to access
terminology and value sets. Details were presented at recent IHTSDO
conference
https://confluence.ihtsdotools.org/pages/viewpage.action?pageId=12780136
Australia1
Yes
Canada
Yes
India
Yes
Israel
We do not have any
Malaysia
Yes
My-Harmony (tool to harmonize and codify terminologies to the databases)
and ICD-Code Generator (is in progress to facilitate ICD-10 Coding)
New
Zealand
Yes
The Ministry of Health operates a national release center for distributing
SNOMED. Local affiliates have recently started using an online member
licensing and distribution service hosted by IHTSDO.
Uruguay
Yes
National distributed terminology service.
Lack of clearly defined skills and roles however means that organizational and
vendor decision makers are not in a position to recognize opportunities or
risks.
Wiki, InfoCentral, Terminology Gateway, HL7 Explorer, TermWorks mapping
tool
(Happy to discuss to provide more detail)
ICMR (Indian Council of Medical Research)
We don't offer a terminology server, but we advertise the availability of the
IHTSDO SNOMED browser so that new users can become familiar and
participate in developing refsets as part of national project teams
Terminology services at the implementation level
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6.1.8
Methodologies applied in your country for facilitating the
usage of nationally adopted terminologies by end users ?
Country
India
Please describe what are the methodologies that have been applied in your
country for facilitating the usage of nationally adopted terminologies by end
users
National EHR which supports and encourages use of SNOMED CT though does not
insist upon it at initial role out - but moving a progressive bar up.
On-line working groups, communities for collaboration, education sessions,
Webinars, on-line forums, SDO conference reports
Federal legislation
Israel
Only local adaptation of ICD-9-CM by various healthcare organization
Malaysia
1. Through stakeholder engagement that provides decision on the use of
terminologies
2. Directive on the use of the terminology for every Ministry of Health-funded project
3. Engagement with the private healthcare facilities to facilitate the use and to
enforce private Healthcare Facilities and Services ACT (1998)
SNOMED implementation received an endorsement from the National Health IT
board, and all business cases going forward have to show support for SNOMED.
However, we recognize that stakeholder engagement is essential. We maintain
effective working relationships with a variety of people, including software vendors,
clinicians and health service managers. SNOMED is a topic that we often discuss at
various forums, workshops and meetings. We make sure that the stakeholders are
aware of the value SNOMED CT adds and that they know we are there for them.
Australia
Canada
New Zealand
Uruguay
We form clinical working groups to select content from the SNOMED international
release to create refsets in the various clinical domains. The Ministry of Health funds
and supports these working groups, which operate at national level and work within
the national health information standards development framework.
Terminology services at the implementation level
Based on the responses provided a set of classes have been identified and answers
remapped into them. The following table and figure summarize this classification.
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Country
Australia
Canada
India
Facilitated access to resources
Malaysia
X
Normative requirements
Usage Endorsement
Israel
X
Uruguay
New
Zealand
X
X
X
X
Funding
X
Education
Stakeholder involvement & support
X
X
X
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6.2
About SNOMED CT adoption and usage
6.2.1
Which approach has been followed in your country for
introducing SNOMED CT as a terminology for health and/or
social care data?
On the contrary of the EU countries, for which almost all those using (or planning to use)
SNOMED CT indicated the project/use case based approach as the reference one, the
Non-European respondents indicated the top down approach as the most commonly used,
with the exception of Canada and New Zealand.
Country
Australia
Canada
India
Israel
Malaysia
New
Zealand
Uruguay
Which approach has been followed in your country for introducing SNOMED CT
as a terminology for health and/or social care data
Top down approach, e.g. as part Primarily directed from a top down approach for our
of a National project
national health record. But we're seeing a lot of
adoption among vendors who won't necessarily be
posting to the national record.
On projects / use cases basis
Project/use case basis
Education
Subsets for EMR, Immunization and communicable
disease
No Answers
It is still under evaluation
Top down approach, e.g. as part of a National project
On projects / use cases basis
Initially, it was on a projects / use cases basis,
(Top down approach, e.g. as
however now it is a requirement that all new e-health
part of a National project)
business cases show support for SNOMED.
We started by supporting selected projects to
implement SNOMED based applications, e.g. a
district level hospital emergency department
application and a national ambulance solution
Top down approach, e.g. as part of a National project
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6.2.2
For which use cases/purposes is currently used SNOMED
CT in your country?
Country
For which use cases/purposes is currently used SNOMED CT in your country
Australia
Interoperable shared health records.
Everything
Laboratory requesting, adverse reactions, problem diagnosis, clinical history etc...
National shared EHR and local use in some larger hospitals - to support reporting, limited use for
clinical pathways and decision making (in a very small number of the larger hospitals). In national
medication programs
Canada
India
Diagnostic imaging
Public Health: Immunization and Communicable Disease
Surgical synoptic reporting
Pathology synoptic reporting
EMR content standard
No Answers
Israel
Not used yet
Malaysia
-Implementation at the back-end through mapping of prioritized Refsets to databases in order to
produce SNOMED CT-coded databases for analytic purposes
New
Zealand
The use of SNOMED CT is rapidly growing in a variety of settings and applications - in ambulance,
primary care, referral systems, medicines and adverse reactions and so on.
Uruguay
SNOMED Is now mandated for all national and large regional clinical information system
implementations
EHR
6.2.3
For the indicated use cases how SNOMED CT is actually
used?
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No countries indicated to use SNOMED CT for aggregating data (while in EU Malta and UK
does). Only Israel considered this question as Not Applicable, compared to the nine over
fourteen cases identified in the European Survey.
Malaysia claims to use SNOMED CT only as Reference terminology, all the others (Australia,
Canada, New Zealand and Uruguay) use it as both Reference and Interface terminology.
Country
Interface terminology
(capturing patient data)
Reference terminology
(recording patient data with
unique codes and precise,
formal meaning)
Aggregate terminology
(classifying patients based
on their characteristics)
Australia
Yes
Yes
No
Canada
Yes
Yes
No
India
No Answers
Israel
Not Applicable
Malaysia
No
Yes
No
New Zealand
Yes
Yes
No
Uruguay
Yes
Yes
No
Other
[1]
[1] Mapping of locally used and legacy terms to SNOMED CT concept ID PT is used by some as the User
Interface Term
6.2.4
For the indicated use cases what of SNOMED CT do you
actually use?
Figure 8 - For the indicated use cases what of SNOMED CT do you actually use
Coherently with the previous answer, Israel indicated this question as not applicable.
With the exception of Uruguay all the other respondents declared to use pre-coordinated
concepts; on the contrary the 100% of EU countries using SNOMED CT asserted to use precoordination.
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Malaysia; New Zealand and Uruguay indicated to use the SNOMED CT compositional
syntax, while only England and Netherlands declared to do it among the EU respondents.
The full SNOMED CT description logic seems to be used by two countries (Malaysia; New
Zealand ) of six; in comparison with the two (NL, DK) of twenty-two (ten IHTSDO members)
derived from the European questionnaire.
Country
Pre-coordinated concepts
Australia
Yes
Compositional Syntax
(post-coordination)
No
Canada [2]
Yes
No
India
No Answers
Israel
Not Applicable
Full description logic
(concepts, relationships...)
No
No
Malaysia
Yes
Yes
Yes
New Zealand
Yes
Yes
Yes
Uruguay
No
Yes
No
[2] Comment: “Pre-coordinated concepts Legacy applications do not support post coordination”
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6.2.5
Country
Australia
Did (or will) the introduction of SNOMED CT in your country
affect existing terminologies?
Did (or will) the introduction of SNOMED CT in your country affect existing
terminologies
Yes
Primarily existing GP terminologies. There's a variety of systems using various
code systems. Most vendors are in agreement to migrate. Some want to
maintain existing interface terminology, and map to SCT in backend. However
our preference is it's used natively, to minimize mapping burden (maintenance
& errors)
Some systems also use classifications as interface terms.
Some of the less functional or non-standardized terminologies used by
vendors have not been replaced but maps have been applied, with limited
conformance requirements.
Perhaps. CIHI is looking to move some of their legacy terminology
requirements to SNOMED CT. No formal decision as of yet
This may impact ICD-10-CA and CCI
Canada
Yes
India
Israel
Malaysia
New
Zealand
No Answer
Yes
Diagnosis coding in the EHR
Yes
we need to harmonize to NHDD (National health Data dictionary)
Yes
Will replace Read Codes in primary care
Will replace any use of ICD-10-AM for other than activity based funding
purposes
No
Uruguay
6.2.6
Could you briefly describe what has been (or what will be
according to your current evaluation) the impact of the
introduction of SNOMED CT in the existing IT architecture
(including software)?
The answers provided about the impact on existing IT architecture do not go into details
about the impact, identifying however some remarkable aspects like the impact on DB design
and user interface. It is interesting to note how no one mentioned the availability of
terminology services.
Country
Australia
Could you briefly describe what has been (or what will be according to your
current evaluation) the impact of the introduction of SNOMED CT in the existing IT
architecture (including software)Mostly the cost of general change.
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Canada
Hopefully SCT provides a better experience (if implemented well) with more accurate
recording of health, and improved localization.
It supports national interoperability but is not supporting longitudinal EHR meaning
clarity - which requires consideration of the information model as well as the concept
representation terminology.
New understanding of reference terminology. New database design perhaps.
India
Need to accommodate post coordinated expressions
No Answers
Israel
Some changes will be necessary in existing applications mainly in database architecture
(field sizes) and user interfaces.
Malaysia
Diplomatically difficult question to respond to effectively
New
Zealand
Will impact many existing systems. Retrofitting SNOMED does not realize its full
potential. SNOMED is easier to introduce with new applications that have modern web
based architecture. It is a natural fit for new applications and new vendors are excited to
be able to use SNOMED.
No Answers
Uruguay
6.2.7
Country
Australia
Canada
Could you briefly describe what has been the main
challenges (or what will be according to your current
evaluation) of the transactional scenario (i.e. moving toward
the adoption of SNOMED CT)?
Could you briefly describe what has been the main challenges (or what will be
according to your current evaluation) of the transactional scenario (i.e. moving
toward the adoption of SNOMED CT)Changes to existing established software. New software readily adopts, but existing
systems need incentives/compensation.
Vendor resistance
Decision maker lack of understanding of what is actually needed to achieve their
objectives.
Lack of skills throughout healthcare and IT professions regarding utility and opportunities
of terminology based approach when combined with robust, standardized and clinically
relevant information model (the focus on IT based model is fine for exchange but does not
support clinical engagement which is required as well - there are many parts to the puzzle
- this is not a one solution issue.
Reaching vendors and stakeholder before system are procured
Formal RFP requirements for SNOMED CT enabled systems
India
Defining system, business and functional requirements as they pertain to SCT
No Answer
Israel
Funding!
HMO's and government hospitals request funding from MOH, which was not allocated yet
Malaysia
We avoid implementation at the transactional level but opt for the back-end approach
because we will not be ready and because many vendors and countries could provide an
insight into the front-end approach if we decide to do that later
1) Getting a very wide variety of stakeholders engaged and involved is always a big piece
of work, but I feel we have been able to secure support of key players and are in a very
good place on our SNOMED journey.
New
Zealand
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2) Mapping existing coding systems/terminologies to SNOMED are often required.
Uruguay
6.2.8
Country
Australia
The single biggest challenge presently is to complete the migration from Read to
SNOMED in relation to personal injury claims (big business in NZ) and in primary care.
GP systems use Read and not SNOMED. Replacing ICD-10-AM in point of care
applications is the biggest challenge in hospitals.
Adoption barriers. Requires to simplify encoding at the doctor's desk
Could you briefly describe how those challenges have been
managed (or are planned to be managed)?
Could you briefly describe how those challenges have been managed (or are
planned to be managed) Implementation assistance and compensation/incentive programs
India
Centralized approach with limited engagement with healthcare organizations at this stage
and virtually none with clinicians who are logical adopters and champions.
Planned:
Vendor engagement
RFP language
Outreach
For Canada, alignment with US requirements where applicable is important as most of
our vendors are US based and we are a small market population wise for the vendors to
make Canadian specific modifications
No Answer
Israel
There have been negotiations between the MOH and MOF
Malaysia
we chose this type of approach which is more manageable to us before we embark to this
approach
New
Zealand
1) Through stakeholder engagement and relationship management.
Canada
Uruguay
6.2.9
We are taking a top-down, cross-government agency approach to drive the change so
that health providers cannot but avoid moving to SNOMED. We are using the very strong
advocates for SNOMED developed through our pilot projects to win the hearts and minds
for the change.
Using Terminology services for semi-automatic encoding
Could you summarize the main steps accomplished for the
adoption of SNOMED CT
The following table reports the answer provided for this question.
Country
Main steps accomplished for the adoption of SNOMED CT
Australia
Establish national release around 2009.
Development of refsets for specific projects 2009 onwards
Release of AMTv3 RF2 compliant Medicines extension, with concrete domains (2014).
Systemic improvements to localization 2012-2015+
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National sub sets available
National record able to receive and deliver SNOMED CT content from and to local
systems
the basic infrastructure is in place but SNOMED CT has been implemented in some
local systems without knowledge or understanding (basically feral once the licenses are
out there.
Canada
India
Canadian English and French extensions (May 2015)
Canadian extensions are now in the IHTSDO browser
Canadian edition available in Apelon TermWorks in support of mapping project
Some education
Wiki for release publication
SNOMED CT community established, but need further growth and development
2009 initial FR translation
Jurisdiction and pan-Canadian projects using SCT: such as Immunization
No Answer
Israel
2011-13 National committees, Agreement on adoption in national level
2013-today awaiting funding :)
Malaysia
"end of 2012: Beginning membership in IHTSDO
2013: Formalization of approach
2014: Confirmation of refset-methodology-development (Use case: Cardiology)
2015: Validation and Feedback-gathering from international community on my-harmony
that will harmonize and codify SNOMED CT to the databases
2016: Implement the use of SNOMED CT-coded database in the analytics
New
Zealand
2010 establishment of national medicines terminology (SNOMED national extension)
2013 hospital emergency department information system goes live using SNOMED
refset for diagnoses
2015 national ambulance information system goes live using SNOMED for clinical
impressions and interventions
2015 SNOMED now required as a matter of policy for all significant investments in
clinical information systems
No Answer
Uruguay
6.2.10 What has been the content selection approach applied (or
planned to be applied) for introducing in your country
SNOMED CT?
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About half of the countries interviewed declared that the full SNOMED CT core has been
selected and national extension defined when SNOMED CT were introduced, this is really
different with what has been derived from the EU country survey, where the privileged
approach was that based on the development of use case specific refsets and in which only
UK declared to have adopted the “full SNOMED CT” approach.
This answer is perfectly in line with the top down approach stated above.
Country
Australia
Canada
India
Israel
Malaysia
New Zealand
Uruguay
What has been the content selection approach applied (or planned to be
applied) for introducing in your country SNOMED CT
The Full SNOMED CT core has been selected and national extensions
defined.
REFSETs have been defined
Subset development in key critical areas
for specific use cases
Canadian Extension to support precoordinated concepts for Diagnostic
imaging that include laterality and contrast
Subsets are available and published for
pan-Canadian use as is our national
extension
No Answer, still under evaluation
Other
Health Informatics Council provides direction and consensus
provided by the stakeholders
The Full SNOMED CT core has been selected and national extensions
defined.
The Full SNOMED CT core has been selected and national extensions
defined.
6.2.11 Can you quantify (and qualify) the selected SNOMED CT
Refset(s)
The following table list the answers provided for the SNOMED CT Refset defined in each
country
Country
Australia
Canada
India
Israel
Malaysia
Can you quantify (and qualify) the selected SNOMED CT Refset(s) Currently published refsets can be previewed at
http://ontoserver.csiro.au/shrimp/rt.html?refset=None&versionId=http%3A%2F%2Fsnom
ed.info%2Fsct%2F32506021000036107%2Fversion%2F20150531
We encourage maximal content. With refsets used to ensure context compliance. (I.e.
not select inappropriate concepts). Many vendors still complain about them being "too
big" however our belief is that suitable search strategies should mitigate noise.
emergency - presenting problem, diagnosis, and others
Alerts
Others - I don't have the details with me
Available on our Terminology Gateway
Happy to have a discussion to show you the Gateway and meet with our Solutions team
as well.
Immunization (7 subsets)
Communicable Disease (1 subset)
Primary health care (numerous subsets)
No Answers
No Answers
1. Cardiology Refset, 518 concepts and confirmed with Cardiologists
2. Oncology/Cancer, (XXX), awaiting confirmation from oncologists
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New
Zealand
Uruguay
3. Drugs (in progress)
Emergency department refset 3000 concepts
ED variant now also using unconstrained SNOMED
Ambulance refset 600 concepts
No Answers
6.2.12 What are the main on-going activities?
The following table reports the answers provided about the on-going activities
Country
Australia
What are the main on-going activities(E.g. Mapping ICD-10/ ICD-10 CM - ICPC2)
Localization of interface terms.
Improving search functionality
Addressing content gaps.
Assisting colleges to develop approved content/refsets.
Canada
India
Map maintenance by vendors to national medication terminology
Mapping of local terms to SNOMED CT
No Answers
Israel
None at the moment
Malaysia
NAD
New
Zealand
Migrating from Read Codes to SNOMED
Developing refsets for approximately 60 clinical specialties, refsets sized at about 100
concepts on average
No Answers
Uruguay
6.2.13 Could you briefly describe your future plans?
The following table reports the answers provided about the future plans
Country.
Australia
Canada
India
Israel
Malaysia
Could you briefly describe your future plans(e.g. complete the translation of the selected 40.000 terms)
Integration of AMT into SNOMED CT.
Currently the two terminologies are published together, but AMT only shares a common
metadata. It duplicates ingredients, forms etc. We'd like to integrate better so that things
like allergy monitoring etc., are easier.
Undetermined - though it seems clear that there is an intention to enable and encourage
and provide support for local implementation
Move to RF2
develop more comprehensive plan and approach for supporting the Canadian extension
(English and French) and our subsets
Expansion of the Terminology Gateway
No Answers
No Answers
We are now implementing LOINC as laboratory standard and harmonizing with
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New
Zealand
Uruguay
implementation of SNOMED CT and following all mapping activities conducted at
international level
Complete refsets for all specialties while at the same time promoting more sophisticated
search engine based approaches
Creating refsets is a means to engage clinicians and give them familiarity with SNOMED
No Answers
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7
Appendix 5 - Report on 2nd revision workshop
On 13th October 2015, the second ASSESS CT validation workshop was held in
Berlin. This workshop has been used by WP1 for validating the results obtained by the Focus
Groups and Questionnaires and gathering inputs for the second phase of the project.
This has been realized sharing in advance with the participants the most relevant36 aspects
derived from those investigations and summarized in a list of statements grouped per topic
Stakeholders have been therefore invited to express their opinion about those statements
and in general to provide comments and suggestions during the workshop directly and using
on-line tools.
A concrete experience with SNOMED CT has been therefore presented by Andrew Perry, by
setting the scene in the UK regarding primary and secondary care.
Finally, candidate use cases have been presented to get suggestions for their refinement
and selection.
7.1
Highlights from the country focus groups and
questionnaires
The statements summarizing the most relevant aspects derived from the focus groups and
questionnaires (see D1.2 for details) has been shared in advance with participants and
summarized during the presentation of Giorgio Cangioli. During this presentation, the results
and issues were shown and illustrated and attendees asked to indicate how much they agree
with the presented conclusions and they consider them relevant. The plan for the workshop
was that of using those feedbacks as additional input for the general discussion.
The role of SCT as a
reference terminology and
mappings broker
Use cases for
SNOMED CT
adoption
The current lack
of evidence of
benefits
Strategic longterm benefit
Market maturity and
potential impact of the
adoption of SCT
Suggested
approaches for
introducing SCT
Usability and
users acceptance
Pre-conditions for
pursuing semantic
interoperability
Licensing and cost
issues
Figure 9 - Highlights from the country focus groups and questionnaires
36
Relevance is evaluated either because it is mentioned more times in questionnaires, FGs and/or during the workshop; or
because deemed to be particularly noteworthy.
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nd
Figure 10 - 2
validation workshop questionnaire
A second optional questionnaire was also prepared to allow respondents to provide - if
needed - more specific evaluations about each of the proposed statements. (See figure
below)
nd
Figure 11 - 2
validation workshop detailed questionnaire
Obtained results have been summarized in the following figures
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Figure 12 - Agreement with statements per topic
A general agreement about the conclusions derived from the focus groups and
questionnaires is shown by the provided responses, with a larger consensus on “Strategic
long term benefit” of SNOMED CT and issues related to license and costs.
All the proposed topics has been evaluated relevant for further discussions with a special
focus on approaches to be followed for the introduction of SNOMED CT; market maturity and
lack of evidence of benefits.
Figure 13 - Relevance of considered topics
People responding to the question about relevant domains not covered by nationally used
terminologies indicated in problems, medical devices and allergies the main areas.
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Specific statements for which at least one “disagree” has been collected are listed below.
# of “disagree” : 2
Statement
The end user acceptance plays an essential role in the adoption of
SNOMED CT (or any other terminology). This implies several
different aspects such as availability of tools that facilitate the usage
of terminology; awareness about the benefits; and effectiveness in
the real business (i.e. clinical) processes
# of “disagree” : 1
Statement
Terminologies have to be used and assessed only within well
specified purposes or contexts of usage
Terminologies should not be used beyond their purposes, although
this is a not uncommon practice. This happens usually with
classification systems since they are often the only terminologies
actually used at the jurisdictional level
In the large majority of cases only pre-coordinated SNOMED CT
concepts are used for SNOMED CT adoption
There is a low maturity of the EHR systems (ICT) market for the
usage of SNOMED CT, although some progress has been made in
the last years
The introduction of SNOMED CT may play a role in the
standardization of the EHR contents, and therefore in the
marketplace of EHR systems and related solutions
Terminologies require governance and management: there is
however a lack of supporting National Competence Center(s)
The SNOMED CT license cost is a critical barrier in the decisional /
start-up phase when the potential benefits of this change have not
been yet completely evaluated / experienced. Even though many
people recognize that this is only a part of the overall routine costs,
supporting actions/policies for facilitating the initial adoption of
SNOMED CT are strongly suggested in order to overcome the “allor-none”-policy of IHTSDO.
The actual, or perceived, complexity of SNOMED CT, in all its
different aspects (e.g., description logic, compositional syntax,
versioning and extensions management, collaboration process with
IHTSDO, software implementation) is a barrier that has to be
properly managed. Different means for each of those challenges (like
for example education, software investments) have to be identified
and adopted in order to overcome them or hide the complexity of
SNOMED CT to the users
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Comments
The end user acceptance
plays an essential role in the
adoption of SNOMED CT :
- How do you define an end
user?
---clinician?
---vendor?
---IT architect?
---information architect?
there is a HUGE difference
thus my respond a clinician
should not accept SNOMED
CT
Comments
it is not always lack of
supporting
National
Competence Center(s), they
are there, but is a lack of
enough resources to support
the
education
and
implementations
All terminology management
is complex. SNOMED CT is
not more complex than others
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7.2
Implementing SNOMED CT in General Practice in the
UK
Andrew Perry started his presentation by setting the scene in the UK regarding primary and
secondary care.
5-Byte READ2
RctCtv3Map
Ctv3RctMap
!
SctRctMap
Clinical Terms Version 3
RctSctMap
!
Ctv3SctMap
SctCtv3Map
!
SNOMED CT
OPCS 4.6
ICD10
Figure 14 - Implementing SNOMED CT in General Practice in the UK
After the description of the current state in the UK and the migration of terminology he
explained what has been done in the UK in order to implement SNOMED CT:
1. The GP requirements were updated in order to mandate the use of the UK edition
of SNOMED CT.
2. GPs were educated on the JGPITC through workshops and webinars with live and
recorded presentations.
3. Implementation guidelines were set concerning issues like terminology services,
data migration, data entry and storage as well as reporting and data exchange.
SNOMED CT evolved from Read codes and is more extensive. It accommodates
requirements of all health professionals and all specialties. Read codes are in the process of
being deprecated and withdrawn. SNOMED CT delivery is now under GPSoC.
7.3
Selecting use case scenarios and case studies for
reference terminologies in the health sector
Catherine Chronaki presented the candidate case studies identified by WP1, the criteria that
have been agreed and how those cases cover those criteria. A consultation with attendees
then started about the overall question on how to decide which use case should be selected.
Discussed criteria have been: scope, granularity, availability of value sets, frequency of use,
jurisdictional contexts and potential impact on EU eHealth policies.
A concrete study on the usage of LOINC and SNOMED CT as reference clinical
terminologies to cross-query two large anonymized ICU databases. The conclusion of this
study was that those standard terminologies are rich, but a large variability in disease and
diagnoses coding has been experienced. Hierarchical queries, as well as a better mapping
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resources and techniques could help and need to be explored. Professional training is also
suggested to avoid under and overcoding.
7.4
Final discussion
At the end of the WP 1 session Veli Stroetmann moderated the discussion among attendees
The most relevant inputs have been:
 It has been suggested to consider in the overall analysis the needs of the European
Reference Network (ERN). More in general it should be considered how cases may
contribute to the current priorities of the eHealth Network.
o Note: one of the selected case studies has been at the end the Rare Diseases
Registry. An external expert Rémy Choquet, involved in the ERN, has been
engaged for supporting this case study.
o Note: the impact on European health policies has been included as additional
selection criteria
 The scope of the considered cases should be better identified (and reduced) to help their
prioritization. Do not mix up use cases, case studies…
o Note: after the workshop the cases have been furtherly refined and their scope
reduced (with the exception of the rare disease registry case). The patient
summary case has been for example split into two different cases: the crosscountries exchange and the national / regional case. A formal representation of
what is meant here with case study, use case, etc. has been provided. (see D1.3
section 7)
 Semantic interoperability doesn’t mean only coded information: only what needs to be
processed by a computer needs to be coded, humans use text.
 SNOMED CT has become the label for discussion on whether or not using terminology. It
is one of the best means at this moment, when you start with terminology. It is just a
building block in terminology and it not solving the whole (semantic interoperability)
problem.
o Difference between SNOMED CT and other terminologies is the relative ease of
extensibility. The problem for many people is the licensing issue. One of the
attendees stated that it is easier to use LOINC than SNOMED.




Finance and Public health could be two important drivers for terminology adoption.
Even if someone proposed a top-down approach for a successful implementation of
terminologies, several concerns have been risen on this, in fact politicians want quick
results which cannot be achieved with a pure bottom-up or top-down approach; moreover
a meet-in-the-middle approach allow to mediate between the need of addressing and
achieving long term goals and that of taking in account field experiences and constrains.
Concerning the lack of evidences on wide-spread use of SNOMED CT there is a time
scale (several years) that needs to be evaluated for being able to experience the return of
investments, so the time factor should be carefully considered before becoming
judgmental on terminology / SNOMEC CT adoption.
Data exchange is not the only focus for finding the value of SNOMED CT: a basic
question could be how are we supporting the people asking questions (with clear
common and agreed definitions)? Using and applying SNOMED CT for asking the
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questions, decision support and rules for quality indicators could be a strong driver for the
usage of SNOMED CT.
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8
Appendix 6 - Literature Review on the Use of
SNOMED CT
8.1
Introduction
The objective of this study was to investigate the use of SNOMED CT by providing an
overview of published scientific literature. The last comprehensive literature reviews on this
topic were published by Cornet et al. [1] in 200837 and Lee et al. in 201338 (in the following
will be referred to as ‘2013 Review’). The review from 2008 focused on papers published
between 1996 and 2006 including all versions of SNOMED that were available until that
time.39 Later, the 2103 Review focused only on SNOMED CT papers published between
2001 and 2012.
Moreover, compared to the 2008 Review, for the 2013 Review the classifications criteria
were enhanced. For this Literature review, we used the practical experience of both
precedent studies and not only slightly refined the classification criteria but also customized it
to our main objective within the ASSESS CT. Because Work Package 1 is attempting to
provide evidence on the current use of SNOMED CT worldwide, it was considered as
eminent to produce more granular processed results for papers dealing with implementation
and evaluation.
However, this Literature Review still enables the reader to have a comprehensive, global and
systematized overview of all currently published scientific literature on SNOMED CT.
A description of the methodology applied is provided in the D1.3 body document.
8.2
Results
The searches on PubMed (n=189) and Embase (n=214) resulted in 304 unique papers. 62
publications were considered as being ineligible: 61 papers were excluded because the
version of SNOMED was not SNOMED CT. Only 1 other paper was excluded because other
than its title, the abstract and full-text was written in Dutch.
Figure 15 gives an overview of the scoring of papers.
The full bibliographic list of the 242 eligible papers with the naming of their respective
groupings and classifications is available in 8.4 Full list of eligible publications:
37
Cornet, R., de Keizer, N. (2008): Forty years of SNOMED: a literature review; in: BMC Med Inform Decis Mak; Vol. 8; (Suppl
1):S2.
38
Lee, D., de Keizer, N., Lau, F. et al (2014): Literature review of SNOMED CT use; in: Journal of the American Medical
Association; Vol. 21; pp. e11-e19
39
SNOP, SNOMED, SNOMED II, SNOMED Version 3.0, LOINC codes integrated into SNOMED, SNOMED Version 3.5,
SNOMED RT and SNOMED CT
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PubMed (198)
Embase (214)
Unique (304)
Eligible (242)
Focus Category 1:
Indeterminate (42)
Ineligible (62)
Focus Category 3:
Pre-develpment
(45)
Focus Category 2:
Theoretical (94)
Focus Category 4:
Implementation
and Evaluation
(61)
Other versions of
SNOMED (4)
1. Other (14)
3.Illustrate
terminology
systems theory
(10)
7. Translation (6)
12. Research (15)
Unknown version of
SNOMED (57)
2. As an example
(28)
4. Description of
SNOMED CT and
other standards
(18)
8. Prospective
content coverage
(13)
13. Clinical
Practice (12)
Paper with no
English abstract
(1)
5. Terminology
auditing (18)
9. Prospective
inter-rater
agreement (2)
14. Retrieve or
analyse patient
data (26)
6. Cormpare to or
map to other
terminology
systems (48)
10. Standard for
electronic health
records (8)
15. Prove merit (8)
11. Design
considerations (16)
Figure 15 - Overview of scoring of papers
8.2.1 SNOMED CT Focus and Usage Category
A summary of the number of eligible articles per usage category (left column and blue bars)
and focus category (right column) is provided in Figure 16. While Figure 17 shows a detail on
usage categories.
INDETERMINTAE
14
1. OTHER
10
3. ILLUSTRATE TERMINOLOGY SYSTEMS THEORY
THEORETICAL
4. DESCRIPTION OF SNOMED CT AND OTHER STANDARDS
18
5. TERMINOLOGY AUDITING
18
6
7. TRANSLATION
PRE-DEVELOPMENT/
13
8. PROSPECTIVE CONTENT COVERAGE
10. PLANNED STANDARD FOR EHR
45
DESIGN
2
8
16
11. DESIGN CONSIDERATIONS
15
12. RESEARCH
12
13. CLINICAL PRACTICE
IMPLEMENTATION
&
26
14. RETRIEVE OR ANALYSE PATIENT DATA
15. PROVE MERIT
94
48
6. COMPARE TO OR MAP TO OTHER TERMINOLOGY SYSTEMS
9. PROSPECTIVE INTERRATER AGREEMENT
42
28
2. AS AN EXAMPLE
8
EVALUATION
61
Figure 16 - Number of papers by usage category and focus category
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Figure 17 - Percentages of the Focus Categories with further breakdown of “Implementation
and Evaluation”
The majority of SNOMED-CT-related publications are theoretical papers (n=94; 39%),
followed by 61 papers that deal with SNOMED CT implementation & evaluation (61=25%).
Papers on Pre-Development and Design make a share of 19% of the total with 46 papers. 17
percent of papers (n=42) were grouped in the category “Indeterminate”, which consists of
editorials, letters to journals and results of surveys, literature reviews, and systematic
reviews, but also papers that referenced SNOMED CT very briefly as a standard
terminology.
Implementation and Evaluation
Focusing on the “Implementation and Evaluation” category40: in 26 publications SNOMED CT
is used to retrieve or analyze patient data; in 15 papers it is used for research proposes; 12
papers describe scenarios where SNOMED CT is implemented got daily clinical practice,
and only a very small number (n=8) deals with evaluating and proving the merit of SNOMED
CT.
Hereafter a detailed list of the papers belonging to the “Implementation and Evaluation”
category is reported, showing for each paper these additional information: (a) how it has
been used (e.g. as interface terminology); (b) the list of applicable Use Cases; (c) the country
of implementation or publication respectively.
Clinical Practice
Table 2 - Publications within the Usage Category “Clinical Practice“ with specification of the
country of implementation
No.
ID
Year
Authors
Title
1
79
2011
Sampalli T,
Shepherd M, Duffy
J
Clinical vocabulary as a boundary
object in multidisciplinary care
management of multiple chemical
sensitivity, a complex and chronic
condition.
40
Elaboration of
implementatio
n
Done by local
interface
terminology
Use Case
Country of SCT-Implementation
Patient Summary:
Problem List;
Patient Summary:
(Surgical) Procedure
Canada: Regional and Domestic
Health Authority, Nova Scotia
See the smaller circle diagram at the right side in Figure 3 that shows the sub-categories’ distribution for the “all
implementation & evaluation” papers:
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No.
ID
Year
Authors
Title
2
86
2014
Computerized decision support
system and naive bayes models for
predicting the risk of relapse in breast
cancer.
3
10
6
2013
Lopez J, PalaciosAlonso D,
Tortajada S,
Moreno A, Casitas
E, Garcia-Gomez
JM, Gonzalez Otal
R, PerezGonzalez A,
Martinez A, Parra
Calderon CL, Rivin
E, Leal S, Ortiz
Gordillo MJ
Passiment E,
Meisel JL,
Fontanesi J,
Fritsma G,
Aleryani S,
Marques M
Maheronnaghsh
R, Nezareh S,
Sayyah MK,
Rahimi-Movaghar
V
Wei W-Q, Cronin
RM, Xu H, Lasko
TA, Bastarache L,
Denny JC
Development and evaluation of an
ensemble resource linking
medications to their indications.
4
5
11
0
11
1
2013
2013
Developing SNOMED-CT for decision
making and data gathering: a
software prototype for low back pain.
11
3
2013
Greibe K
Development of a SNOMED CT
based national medication decision
support system.
7
17
1
2013
Implementing an interface
terminology for structured clinical
documentation.
17
7
2013
Rosenbloom ST,
Miller RA, Adams
P, Madani S, Khan
N, Shultz EK
Galanter W, Falck
S, Burns M,
Laragh M,
Lambert BL
18
9
2015
Cartagena FP,
Schaeffer M, Rifai
D, Doroshenko V,
Goldberg HS
Leveraging the NLM map from
SNOMED CT to ICD-10-CM to
facilitate adoption of ICD-10-CM.
Sutherland M,
Nathanson LA,
Horng S
Proof of concept application to extract
structured chief complaints using an
ontology based method.
9
10
11
12
22
3
23
5
24
2
2014
2013
2015
Abbas Z, Magrey
MN
Martínez-Costa C,
Cornet R,
Karlsson D,
Schulz S, Kalra D
Use Case
Country of SCT-Implementation
Other
Other
Spain: not further specified
Laboratory Procedures
(order)
United States: American Society
for Clinical Laboratory Science,
Tysons Corner, VA
Patient Summary:
Problem List
Iran: Sina Trauma and Surgery
Research Centre, Tehran
University of Medical Sciences
(TUMS), Tehran
Mapping to
other
terminologies
Other
United States: Vanderbilt
University, Nashville
Mapping to
other
terminologies
Other
Denmark: Not further specified
Other
United States: Department of
Biomedical Informatics, Vanderbilt
University, Nashville, Tennessee
Decoding laboratory test names: A
major challenge to appropriate patient
care.
6
8
Elaboration of
implementatio
n
Other
Using
inference;
Using postcoordination;
Using
reference sets
Done by local
interface
terminology
Indication-based prescribing prevents
wrong-patient medication errors in
computerized provider order entry
(CPOE).
Risk of cardiovascular disease among
patients with psoriatic arthritis
compared to ankylosing spondylitis
(retrospective cohort study).
United States: Department of
Medicine, University of Illinois at
Chicago, Chicago, Illinois, USA 2
Other
Other
Mapping to
other
terminologies
Other;
Patient Summary:
Problem List
United States: Information
Systems, Partners HealthCare
System,
Wellesley, MA
Mapping to
other
terminologies
Patient Summary:
Problem List
United States:
Jefferson Medical College,
Philadelphia, PA;
Beth Israel Deaconess Medical
Center /
Harvard Medical School, Boston,
MA
Done by local
interface
terminology
Other
United States: Case Western
Reserve University at Metrohealth
Medical Center, Cleveland, OH
Other
Patient Summary:
Problem List
SemanticHealthNet-Project
Semantic enrichment of clinical
models towards semantic
interoperability. The heart failure
summary use case.
Table 2 lists the 12 identified articles mainly describing SNOMED CT implemented in a daily
clinical practice. With few exceptions these routine patient care implementations mostly take
place in the United States. However, all other presented clinical practice cases are not
country-specific and therefore their results are transferrable to other countries. Nor can it be
assumed that the findings represent the actual distribution of worldwide clinical use
implementations.
Research
Other than for daily clinical routine or as a terminology used in EHRs, SNOMED CT is also
used for research purposes, i.e. to classify or code in a research study. Those kind of studies
could also be identified (n=15) with the help of this Review and are listed in Table 3.
Table 3 - Publications within the Usage Category “Research“
No.
ID
Year
Authors
Title
Country
1
6
2014
Palacios D, Lopez Guerra JL,
Tortajada S, Casitas E, PerezGonzalez A, Gonzalez Otal R,
Martinez A, Moreno A, Parra
Calderon CL, Ortiz Gordillo MJ
A clinical decision support system for breast
cancer treatment planning.
Spain
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An update on the use of health information
technology in newborn screening.
United
States
Other
Other
Analyzing SNOMED CT and HL7
terminology binding for semantic
interoperability on post-genomic clinical
trials.
Attitudes toward and beliefs about the use of
a dental diagnostic terminology: A survey of
dental care providers in a dental practice.
Spain
Other
Other
United
States
Other
Other
Biomedical informatics: we are what we
publish.
Content analysis of physical examination
templates in electronic health records using
SNOMED CT.
Patient safety and clinical efficiency gains
following implementation of an integrated
health information system in east london.
Population-based incidence and prevalence
of systemic lupus erythematosus: The
Michigan lupus epidemiology and
surveillance program.
United
States
Denmark
Other
Other
Done by local
interface
terminology
Using reference
sets
Other
United
States
None
None
Priority queuing models for hospital intensive
care units and impacts to severe case
patients.
United
States
Done by local
interface
terminology
Patient
Summary:
Problem List
Paterson GI, Christie S,
Bonney W, Thibault-Halman G
Synoptic operative reports for spinal cord
injury patients as a tool for data quality.
Canada
Using postcoordination
Patient
Summary:
(Surgical)
Procedure
Meystre SM, Ferrández O,
Friedlin FJ, South BR, Shen S,
Samore MH
Windle T, McClay JC, Windle
JR
Text de-identification for privacy protection: A
study of its impact on clinical text information
content.
The impact of domain knowledge on
structured data collection and templated note
design.
UCbase 2.0: ultraconserved sequences
database (2014 update).
United
States
Other
Other
United
States
Other
Other
Italy
Using inference
None
Utility-preserving privacy protection of textual
healthcare documents.
Visualizing sets of SNOMED CT concepts to
support consistent terminology
implementation and reuse of clinical data.
Spain
Using inference
Other
Denmark
Using inference
Other
2
44
2015
Abhyankar S, Goodwin RM,
Sontag M, Yusuf C, Ojodu J,
McDonald CJ
Aso S, Perez-Rey D, AlonsoCalvo R, Rico-Diez A, Bucur A,
Claerhout B, Maojo V
3
46
2013
4
53
2015
5
65
2013
6
89
2014
Gøeg KR, Chen R, Højen AR,
Elberg P
7
214
2013
Freeman C, Atkinson K, Hart
D, Bowles L, Gutteridge C
8
215
2014
9
222
2013
Somers EC, Marder W,
Cagnoli P, Lewis EE, DeGuire
P, Gordon C, Helmick CG,
Wang L, Wing JJ, Dhar JP,
Leisen J, Shaltis D, McCune
WJ
Hagen MS, Jopling JK,
Buchman TG, Lee EK
10
260
2015
11
264
2014
12
268
2013
13
286
2014
14
296
2014
15
299
2013
Ramoni RB, Walji MF, Kim S,
Tokede O, McClellan L,
Simmons K, Skourtes E,
Yansane A, White JM,
Kalenderian E
Elkin PL, Brown SH, Wright G
Lomonaco V, Martoglia R,
Mandreoli F, Anderlucci L,
Emmett W, Bicciato S, Taccioli
C
Sanchez D, Batet M, Viejo A
Randorff Højen A, Sundvall E,
Rosenbeck Gøeg K
United
States
Other
Retrieve or analyze patient data
A total of 26 publications were classified as describing implementations where SNOMED CT
is being used to retrieve or analyze patient data for secondary questions. Two countries
protrude: Nearly half of the articles (n=12) were published in the United States, followed by 6
from Australia. Thus, these articles (see Table 4) do not specify details on the SNOMED CT
implementation, yet can serve as hints to where and in which setting it is being used.
Table 4 - Publications within the Usage Category “Retrieve or analyze patient data“
ID
Year
Authors
Title
Country of
Publication
28
2013
Edlund W, Schenk C, Jain A, Miller M, Lerner A
Adherence to AAN guideline recommendations that may
prolong survival in ALS.
United States
38
2013
Saez C, Breso A, Vicente J, Robles M, GarciaGomez JM
An HL7-CDA wrapper for facilitating semantic
interoperability to rule-based Clinical Decision Support
Systems.
Spain
43
2013
Mabotuwana T, Lee MC, Cohen-Solal EV
An ontology-based similarity measure for biomedical dataapplication to radiology reports.
United States
45
2014
Sohn S, Liu H
Analysis of medication and indication occurrences in
clinical notes.
United States
59
2015
Koopman B, Karimi S, Nguyen A, McGuire R,
Muscatello D, Kemp M, Truran D, Zhang M,
Thackway S
Automatic classification of diseases from free-text death
certificates for real-time surveillance.
Australia
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ID
Year
Authors
Title
Country of
Publication
60
2013
Zuccon G, Wagholikar AS, Nguyen AN, Butt L,
Chu K, Martin S, Greenslade J
Automatic Classification of Free-Text Radiology Reports to
Identify Limb Fractures using Machine Learning and the
SNOMED CT Ontology.
Australia
61
2015
Koopman B, Zuccon G, Nguyen A, Bergheim A,
Grayson N
Automatic ICD-10 classification of cancers from free-text
death certificates.
Australia
71
2013
Mitchell RJ, Bambach MR, Muscatello D,
McKenzie K, Balogh ZJ
Can SNOMED CT as implemented in New South Wales,
Australia be used for road trauma injury surveillance in
emergency departments?
Australia
83
2013
McDonald CJ, Vreeman DJ, Abhyankar S
Comment on "time to integrate clinical and research
informatics".
United States
112
2014
Gobbel GT, Reeves R, Jayaramaraja S, Giuse
D, Speroff T, Brown SH, Elkin PL, Matheny ME
Development and evaluation of RapTAT: A machine
learning system for concept mapping of phrases from
medical narratives.
United States
116
2013
Lerner A, Schenk C, Miller M, Jain A, Tatsuoka
C
Diagnostic testing and medication utilization in Alzheimer's
disease in a large de-identified database.
United States
121
2014
Cohen DA, Takei H, Rivera AL
Discordant malignancy findings on autopsy at a tertiary
care hospital: A continuing opportunity for quality
improvement.
United States
130
2014
Hulse NC, Long J, Xu X, Tao C
Enabling locally-developed content for access through the
infobutton by means of automated concept annotation.
United States
131
2015
Alonso-Calvo R, Perez-Rey D, Paraiso-Medina
S, Claerhout B, Hennebert P, Bucur A
Enabling semantic interoperability in multi-centric clinical
trials on breast cancer.
Spain
132
2013
Barrett N, Weber-Jahnke JH, Thai V
Engineering natural language processing solutions for
structured information from clinical text: extracting sentinel
events from palliative care consult letters.
Canada
138
2015
Pradhan S, Elhadad N, South BR, Martinez D,
Christensen L, Vogel A, Suominen H, Chapman
WW, Savova G
Evaluating the state of the art in disorder recognition and
normalization of the clinical narrative.
United States
144
2014
Northey LC, Bhardwaj G, Curran S, McGirr J
Eye trauma epidemiology in regional Australia.
Australia
170
2015
Alkhouri H, Murray M, Maka K, Joyce S, Haydon
R, McCarthy S
Implementing an event tool in Cerner FirstNet to identify
the physiotherapy service in the emergency department
and determine its impact on patient care.
Australia
211
2013
Demir OM, Ahmed Z, Logan RPH
Optimising the use of faecal calprotectin for early diagnosis
of IBD in primary care.
United States
219
2013
Bansal A, McGregor DH, Anand O, Singh M,
Rao D, Cherian R, Wani SB, Rastogi A, Singh V,
House J, Jones PG, Sharma P
Presence or absence of intestinal metaplasia but not its
burden is associated with prevalent high-grade dysplasia
and cancer in Barrett's esophagus.
France
230
2014
Zhou L, Lu Y, Vitale CJ, Mar PL, Chang F,
Dhopeshwarkar N, Rocha RA
Representation of information about family relatives as
structured data in electronic health records.
China
246
2015
Paraiso-Medina S, Perez-Rey D, Bucur A,
Claerhout B, Alonso-Calvo R
Semantic Normalization and Query Abstraction Based on
SNOMED-CT and HL7: Supporting Multicentric Clinical
Trials.
Taiwan
271
2014
Lee B, Smola B, Roh MH, Hughes DT, Miller
BS, Jing X
The impact of using the Bethesda System for reporting
thyroid cytology diagnostic criteria on the follicular lesion of
undetermined significance category.
United States
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ID
Year
Authors
Title
Country of
Publication
279
2015
Pendry K
The use of big data in transfusion medicine.
283
2013
Kate RJ
Towards Converting Clinical Phrases into SNOMED CT
Expressions.
United
Kingdom
United States
297
2014
Rahimi A, Liaw ST, Taggart J, Ray P, Yu H
Validating an ontology-based algorithm to identify patients
with type 2 diabetes mellitus in electronic health records.
Iran
Prove merit
The following table lists the articles that prove merits, please refer to the Deliverable 3.2 for a
more detailed representation of findings on this topic.
AUTHORS (YEAR):
[PUBLICATIONID]
TITLE
STUDY OBJECTIVE & DESIGN
RESULTS STATING THE BENEFIT OF USING SNOMED CT
1
2
2015
Rossos PG, Lane K,
Holland
SG
et
al.:
Shaken,
not
stirred.
Towards
standardized
synoptic reporting in GI
endoscopy
electronic
medical records (EMRs).
Proposition of a general framework
that provides semantically-grounded
comparison, aggregation and sorting
of operators
Exploiting a structural medical knowledge base like SNOMED CT,
and relying on the theory of semantic similarity, these operators
enable a semantically-coherent interpretation of non-numerical
attributes, while also considering their distributional features.
2
16
2014
Martínez S, Sánchez D,
Valls
A
(2014):
A semantic framework to
protect the privacy of
electronic health records
with
non-numerical
attributes.
Canada Health Infoway Investment
program to achieve pan-Canadian
colonoscopy
and
colposcopy
consensus data models and creating
an
endoscopy
EMR;
for
interoperability SNOMED CT was
incorporated
Almost all endoscopists agreed the data model and endoscopy
EMR supported timely communication, quality standards and
improvement
3
18
2015
Oluoch T, de Keizer N,
Langat
P
et
al.:
A structured approach to
recording
AIDS-defining
illnesses in Kenya: A
SNOMED
CT
based
solution. [18]
Description of a structured approach
to deriving an ADI (AIDS defining
illness) reference set based on SCT
and the implementation of an interface
terminology at a provincial hospital in
Kenya
SCT provides high coverage in the domain of ADI; anticipation that
the context-specific reference set will support improved recording of
high quality data ensuring completeness and reusability
4
85
2013
Yasini M, Ebrahiminia V,
Duclos
C
et
al.:
Comparing the use of
SNOMED CT and ICD10
for
coding
clinical
conditions to implement
laboratory guidelines.
Comparing the use of SCT and ICD10
for coding clinical conditions to
implement laboratory guidelines (test
ordering recommendations, whether
or not to order tests based on clinical
conditions): ICD10: 43.1%; SCT:
80.1%
SCT is a good choice and covers almost all of the clinical conditions
in laboratory guidelines which are needed to implement Clinical
Support Systems
5
11
4
2014
Song TM, Park HA, Jin DL:
Development of health
information search engine
based on metadata and
ontology.
Developing a metadata and ontologybased health information search
engine ensuring interoperability to
collect and provide health information
using different application programs.
Vocabulary for health information
ontology was mapped to SNOMED
CT
SCT helps to overcome obstacles in managing non-structured and
non-indexed health and medical information
6
12
5
2014
Dewenter H, Heitmann KU,
Treinat L et al (2014):
Effective ways for the
transmission of infection
prevention data according
to
German
legal
specifications
via
the
medical
terminology
SNOMED CT used with
HL7 CDA templates.
Transmission
of
Infection
Prevention data according via SCT
used with HL7 CDA templates
in Germany
The results demonstrate that the entirety of notifiable infectious
agents is displayed via SCT codes by 100 percent.
The use of SCT for the purpose of infection prevention in Germany
shows evident advantages in this field an an implementation of the
terminology can be recommended
7
17
8
2014
Liaw ST, Taggart J, Yu H et
al.: Integrating electronic
health record information to
support integrated care:
practical
application
of
ontologies to improve the
accuracy
of
diabetes
disease registers. [178]
Clinical
Informatics
program
enabling the reuse of knowledge
already
represented
in
SNOMED
CT-AU
tp
perform
semantic
retrievals
for
different
applications
and
clinical domains.
This ontology driven approach can improve the accuracy of EHRbased disease registers and potentially lead to improved
and coordinated chronic disease management, patient safety, and
quality outcomes.
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8
26
2
2014
Rafiei M, Pieczkiewicz D,
Khairat
S
et
al.:
Systemized Nomenclature
of Medicine Clinical Terms
for
the
structured
expression of perioperative
medication
management
recommendations.
Validating the use of structured
terminology concepts in pharmacy to
express
clinical
procedures

by manually extracting, examining and vetting MTM
concepts in SCT, we were able to show that they can be
used to code PMM recommendations with sufficient clarity
SCT has proven to be an excellent mechanism to start
expressing clinical thoughts in standardized terminology as
computerized healthcare systems become more and more
knowledge intensive
possible use of SCT concepts within the EHR with the goals
of enhancing decision support capability for clinicians and
providing error-free data transmission across disparate
facilities, potentially enhancing patient safety


Elaboration of Implementation and Use Case
What can be said about the distribution of the implementation papers by ‘elaboration of
implementation’ and ‘use case’?
In the majority of papers SNOMED CT was mapped to other terminologies (n=28, 45%),
whereas also in a remarkable amount of papers SNOMED CT-reference sets were utilized
(n=20, 29%). In 14 out of 61 implementation & evaluation papers inference was utilized, i.e.
implementations with the use of terminological reasoning such as description logic
classifiers. Ten papers describe implementations where local terminology is applied in user
interfaces in which that local terminology is distinct from the descriptions provided by
SNOMED CT. Another ten papers were grouped as implementations where post-coordinated
expressions were utilized.
The results are shown in the following figure. Multiple selections were allowed.
DONE BY LOCAL INTERFACE TERMINOLOGY
10
MAPPING TO OTHER TERMINOLOGIES
28
USING INFERENCE
14
USING POST-COORDINATION
10
USING REFERENCE SETS
20
OTHER
30
0
5
10
15
20
25
30
35
Figure 18 - Number of papers by elaboration of implementation (Total = 61)
Even though they are not directly comparable data is interesting to note that the percentages
referring to the usage of post coordinates (16%) and usage of the description logic (23%) are
closer to the results of the EU countries questionnaires (about 20 % for both) rather than the
equivalent derived for NON-EU IHTSDO member countries (50% for post coordinates and
30% for the description logic).
Taking a look into the grouping into use cases (see Figure 19), the majority of
implementation papers (n=24) describe the use of SNOMED CT for the collection, recording
and potential processing of problems and diagnosis. In 9 papers, SNOMED CT was used in
a scenario of sharing laboratory test data, whereas just in 6 articles SNOMED CT came to
use for procedures in conjunction with patient summary. No publications dealt with the use of
SNOMED CT in the framework of the EU Rare Diseases Registry. The vast majority of
articles were considered encompassing other than theses use cases. Moreover, no single
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article is treating the cross-border or national/ regional exchange of patient summaries. Also
here, multiple selections were possible.
PATIENT SUMMARY: PROBLEM LIST
24
PATIENT SUMMARY: (SURGICAL) PROCEDURE
6
LABORATORY PROCEDURES
9
EU RARE DISEASES REGISTRY
0
OTHER
60
0
10
20
30
40
50
60
70
Figure 19 - Number of papers by use case (Total = 61)
8.2.2 Medical Domains and countries
1
1
1
PHSYCHIATRY
1
ANAESTHESIOLOGY
1
1
PAEDIATRICS
NEONATOLOGY
1
DERMATOLOGY
OPHTHALMOLOGY
PALLIATIVE CARE
2
2
OPHTHALMOLOGY
1
2
BIOLOGY
SURGERY
2
PROCEDURES
NEPHROLOGY
3
IMMUNOLOGY
2
3
CHRONIC CARE
ANATOMY
3
NEUROLOGY
INTENSIVE CARE
4
3
GASTROENTEROLOGY
5
4
RHEUMATOLOGY
5
PRIMARY CARE
6
NURSING
INTERNAL MEDICINE
7
6
7
RADIOLOGY
ALLERGOLOGY
7
EMERGENCY MEDICINE
GENETICS
8
LABORATORY
11
10
CARDIOLOGY
11
ONCOLOGY
PATHOLOGY
14
12
OTHER
PHARMACOLOGY
PROBLEM LIST / DIAGNOSES
NO SPECIFIC CLINICAL DOMAIN
15
113
The papers spanned 32 medical domains and specialties, while it was also possible to
choose “No specific medical domain” as well as “other” besides them. Problem list/diagnoses
(n=15), Pharmacology (n=12), Oncology (n=11), Pathology (n=11), and Cardiology (n=10)
were medical domains, that ten or more papers dealt with. The full ranking of medical
domains can be seen in the following figure. However, it should be mentioned, that the
outmost part of publications (n=113) were not dealing with any specific medical domain.
Figure 20 - Ranking and amount of medical domains (Total=242)
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The papers were from 33 countries with over 40 percent of the papers coming from the
United States (n=105). Refer to Figure 7 for the ranking of countries of origin of the first
authors with at least 5 publications.
120
105
100
80
60
40
20
19
15
13
11
10
8
6
6
6
5
5
0
Figure 21 - Ranking of countries of origin of the first authors with more than 5 publications
(Total=242)
Table 5 shows the total list of countries with their numbers of publications and their status of
IHTSDO41-membership. More than forty percent of the papers were published by authors
from the United States. It is remarkable that even not being full member of the IHTSDO,
France, Austria, Germany and Italy, are among the countries with at least five publications
between 2013 and 2015.
41
International Health Terminology Standards Development Organization
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Table 5 - Total list of countries, number of publications and their status of membership in the
IHTSDO
Country
No.
of
publications
IHTSDO
Country
No.
of
publications
IHTSDO
Algeria
1
no
Japan
1
no
Australia
11
yes
Kenya
2
no
Austria
10
no
Luxembourg
1
no
Belgium
1
yes
Malaysia
1
yes
Brazil
2
no
Netherlands
6
yes
Canada
6
yes
New Zealand
1
yes
Chile
1
yes
Norway
2
no
China
3
no
Portugal
1
yes
Czech Republic
1
yes
Saudi Arabia
2
no
Denmark
8
yes
South Korea
3
no
France
15
no
Spain
19
yes
Germany
6
no
Sweden
5
yes
Greece
1
no
Taiwan
1
no
Hungary
2
no
Turkey
1
no
Iran
2
no
United Kingdom
13
yes
Israel
3
yes
United States
105
yes
Italy
5
no
Total
242
Overall, three quarters of the papers were published from authors of IHTSDO-Members
States. Even though a not negligible share (25%) still comes from Non-IHTSDO-Members.
Figure 22 - Shares of papers from IHTSDO- and Non-IHTSDO-Members
8.3
Search Queries
Hereafter the detail of the queries used for searching the paper in the used databases
PubMed Query
("systematized nomenclature of medicine"[MeSH Terms] OR ("systematized"[All Fields] AND
"nomenclature"[All Fields] AND "medicine"[All Fields]) OR "systematized nomenclature of
medicine"[All
Fields] OR "snomed"[All Fields]) AND ("2013-01-01"[PDAT]: "2015-08-31"[PDAT])
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Embase Query
1 SNOMED.mp. or exp "Systematized Nomenclature of Medicine"
2 limit 1 to (english language and yr="2013 - 2015")
3 SNOMED.af.
4 limit 3 to (english language and yr="2013 - 2015")
5 2 or 4
8.4
Full list of eligible publications:
ID
Year
Authors
Title
Country
Usage Category
1
2014
Ash N
Israel
Compare to or map to other terminology
systems
2
2015
Rossos PG, Lane K, Holland SG,
Lam M, Mcgaw BG, Sharma R,
Theal J
Canada
Prove merit
3
2013
Code Blue for coding discharge
diagnoses in the emergency
department.
Shaken, not stirred. Towards
standardized synoptic reporting in GI
endoscopy electronic medical records
(EMRs).
2014 Edition Electronic Health Record
certification criteria: revision to the
definition of "common Meaningful Use
(MU) Data Set." Interim final rule with
comment period.
United States
Planned standard for electronic health
records
6
2014
A clinical decision support system for
breast cancer treatment planning.
Spain
Research
7
2015
United States
Compare to or map to other terminology
systems
8
2014
Harispe S, Sánchez D, Ranwez
S, Janaqi S, Montmain J
France
Illustrate terminology systems theory
9
2015
El-Sappagh S, Elmogy M, Riad
AM
Saudi Arabia
Design considerations
10
2013
Sollie A, Sijmons RH, Lindhout D,
van der Ploeg AT, Rubio Gozalbo
ME, Smit GP, Verheijen F,
Waterham HR, van Weely S,
Wijburg FA, Wijburg R, Visser G
Netherlands
Compare to or map to other terminology
systems
12
2015
Lopetegui M, Mauro A
Chile
Design considerations
13
2015
Konstantinidis ST, Kummervold
PE, Luque LF, Vognild LK
Norway
Planned standard for electronic health
records
14
2014
Haroske G, Schrader T
Germany
Compare to or map to other terminology
systems
16
2013
Martínez S, Sánchez D, Valls A
Spain
Prove merit
17
2013
Lamy JB, Tsopra R, Venot A,
Duclos C
France
Compare to or map to other terminology
systems
18
2015
Kenya
Prove merit
19
2013
Oluoch T, de Keizer N, Langat P,
Alaska I, Ochieng K, Okeyo N,
Kwaro D, Cornet R
Lee D, Cornet R, Lau F, de Keizer
N
A comparative analysis of the density
of the SNOMED CT conceptual
content for semantic harmonization.
A framework for unifying ontologybased semantic similarity measures:
A study in the biomedical domain.
A fuzzy-ontology oriented case-based
reasoning framework for semantic
diabetes diagnosis.
A new coding system for metabolic
disorders demonstrates gaps in the
international disease classifications
ICD-10 and SNOMED-CT, which can
be barriers to genotype-phenotype
data sharing.
A Novel Approach to Create a
Machine Readable Concept Model for
Validating SNOMED CT Concept
Post-coordination.
A Proposed Framework to Enrich
Norwegian EHR System with Healthtrusted Information for Patients and
Professionals.
A reference model based interface
terminology for generic observations
in Anatomic Pathology Structured
Reports.
A semantic framework to protect the
privacy of electronic health records
with non-numerical attributes.
A semi-automatic semantic method
for mapping SNOMED CT concepts to
VCM Icons.
A structured approach to recording
AIDS-defining illnesses in Kenya: A
SNOMED CT based solution.
A survey of SNOMED CT
implementations.
Canada
Other
20
2015
Ochs C, Geller J, Perl Y, Chen Y,
Agrawal A, Case JT, Hripcsak G
United States
Terminology auditing
21
2013
United States
Compare to or map to other terminology
systems
22
2013
Wang Y, Lin Z, Liu Z, Harris S,
Kelly R, Zhang J, Ge W, Chen M,
Borlak J, Tong W
Handler J
A tribal abstraction network for
SNOMED CT target hierarchies
without attribute relationships.
A unifying ontology to integrate
histological and clinical observations
for drug-induced liver injury.
Abandoning ICD-10.
United States
23
2015
Halper M, Gu H, Perl Y, Ochs C
United States
24
2014
Hendel RC, Bozkurt B, Fonarow
GC, Jacobs JP, Lichtman JH,
Smith EE, Tcheng JE, Wang TY,
Weintraub WS
Abstraction networks for
terminologies: Supporting
management of "big knowledge".
ACC/AHA 2013 methodology for
developing clinical data standards: A
report of the american college of
cardiology/American heart association
task force on clinical data standards.
Description of SNOMED CT and other
standards
Description of SNOMED CT and other
standards
Palacios D, Lopez Guerra JL,
Tortajada S, Casitas E, PerezGonzalez A, Gonzalez Otal R,
Martinez A, Moreno A, Parra
Calderon CL, Ortiz Gordillo MJ
He Z, Geller J, Chen Y
United States
Page 167 of 176
As an example
31/03/2016
ASSESS CT – D1.3
ID
Year
Authors
Title
Country
Usage Category
25
2014
Liljeqvist HT, Muscatello D, Sara
G, Dinh M, Lawrence GL
Australia
Prospective interrater agreement
26
2013
Levy B
United States
27
2015
Miñarro-Giménez JA, Hellrich J,
Schulz S
Austria
Description of SNOMED CT and other
standards
Translation
28
2013
Edlund W, Schenk C, Jain A,
Miller M, Lerner A
United States
Retrieve or analyse patient data
31
2013
Kottke TE, Baechler CJ
United States
Compare to or map to other terminology
systems
32
2015
United States
Design considerations
33
2015
Japan
As an example
35
2014
United States
Terminology auditing
37
2015
Campbell WS, Pedersen J,
McClay JC, Rao P, Bastola D,
Campbell JR
Tsuji S, Fukuda A, Yagahara A,
Nishimoto N, Homma K,
Ogasawara K
Mortensen JM, Musen MA, Noy
NF
Fung KW, Xu J
United States
Compare to or map to other terminology
systems
38
2013
Saez C, Breso A, Vicente J,
Robles M, Garcia-Gomez JM
Spain
Retrieve or analyse patient data
39
2014
Richesson RL
United States
Description of SNOMED CT and other
standards
40
2015
Kimia AA, Savova G, Landschaft
A, Harper MB
United States
Other
42
2014
El-Sappagh SH, El-Masri S,
Elmogy M, Riad AM, Saddik B
Saudi Arabia
As an example
43
2013
Mabotuwana T, Lee MC, CohenSolal EV
United States
Retrieve or analyse patient data
44
2015
United States
Research
45
2014
Abhyankar S, Goodwin RM,
Sontag M, Yusuf C, Ojodu J,
McDonald CJ
Sohn S, Liu H
United States
Retrieve or analyse patient data
46
2013
Aso S, Perez-Rey D, AlonsoCalvo R, Rico-Diez A, Bucur A,
Claerhout B, Maojo V
Spain
Research
47
2014
Kahn CE
United States
Compare to or map to other terminology
systems
51
2015
Peek N, Morales RM, Peleg M
United Kingdom
Other
52
2013
France
Translation
53
2015
United States
Research
56
2015
Merabti T, Soualmia LF, Grosjean
J, Letord C, Darmoni SJ
Ramoni RB, Walji MF, Kim S,
Tokede O, McClellan L, Simmons
K, Skourtes E, Yansane A, White
JM, Kalenderian E
Zakharchenko A, Geller J
United States
Compare to or map to other terminology
systems
57
2014
Allones JL, Martinez D, Taboada
M
Spain
Design considerations
58
2013
United States
Prospective content coverage
59
2015
Garvin JH, Elkin PL, Shen S,
Brown S, Trusko B, Wang E,
Hoke L, Quiaoit Y, Lajoie J,
Weiner MG, Graham P, Speroff T
Koopman B, Karimi S, Nguyen A,
McGuire R, Muscatello D, Kemp
M, Truran D, Zhang M, Thackway
S
Accuracy of automatic syndromic
classification of coded emergency
department diagnoses in identifying
mental health-related presentations
for public health surveillance.
Achieve compliance with SNOMED
CT.
Acquisition of Character Translation
Rules for Supporting SNOMED CT
Localizations.
Adherence to AAN guideline
recommendations that may prolong
survival in ALS.
An algorithm that identifies coronary
and heart failure events in the
electronic health record.
An alternative database approach for
management of SNOMED CT and
improved patient data queries.
[An analysis of existing terminology
towards constructing ontology in the
field of the radiological technology].
An empirically derived taxonomy of
errors in SNOMED CT.
An exploration of the properties of the
CORE problem list subset and how it
facilitates the implementation of
SNOMED CT.
An HL7-CDA wrapper for facilitating
semantic interoperability to rule-based
Clinical Decision Support Systems.
An informatics framework for the
standardized collection and analysis
of medication data in networked
research.
An Introduction to Natural Language
Processing: How You Can Get More
From Those Electronic Notes You Are
Generating.
An ontological case base engineering
methodology for diabetes
management systems-level quality
improvement.
An ontology-based similarity measure
for biomedical data-application to
radiology reports.
An update on the use of health
information technology in newborn
screening.
Analysis of medication and indication
occurrences in clinical notes.
Analyzing SNOMED CT and HL7
terminology binding for semantic
interoperability on post-genomic
clinical trials.
Annotation of figures from the
biomedical imaging literature: A
comparative analysis of radlex and
other standardized vocabularies.
Artificial Intelligence in Medicine AIME
2013.
Assisting the translation of SNOMED
CT into French.
Attitudes toward and beliefs about the
use of a dental diagnostic
terminology: A survey of dental care
providers in a dental practice.
Auditing of SNOMED CT's
Hierarchical Structure using the
National Drug File - Reference
Terminology.
Automated mapping of clinical terms
into SNOMED-CT. An application to
codify procedures in pathology.
Automated quality measurement in
Department of the Veterans Affairs
discharge instructions for patients with
congestive heart failure.
Automatic classification of diseases
from free-text death certificates for
real-time surveillance.
Australia
Retrieve or analyse patient data
60
2013
Zuccon G, Wagholikar AS,
Nguyen AN, Butt L, Chu K, Martin
S, Greenslade J
Australia
Retrieve or analyse patient data
61
2015
Koopman B, Zuccon G, Nguyen
A, Bergheim A, Grayson N
Australia
Retrieve or analyse patient data
62
2015
Schlegel DR, Crowner C, Elkin PL
Automatic Classification of Free-Text
Radiology Reports to Identify Limb
Fractures using Machine Learning
and the SNOMED CT Ontology.
Automatic ICD-10 classification of
cancers from free-text death
certificates.
Automatically Expanding the
Synonym Set of SNOMED CT using
Wikipedia.
United States
Description of SNOMED CT and other
standards
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ID
Year
Authors
Title
Country
Usage Category
63
2015
Kim TY
2015
Berges I, Bermudez J,
Illarramendi A
Spain
Compare to or map to other terminology
systems
Terminology auditing
65
2013
Elkin PL, Brown SH, Wright G
United States
Research
68
2015
France
Compare to or map to other terminology
systems
70
2015
Australia
71
2013
Declerck G, Hussain S, Daniel C,
Yuksel M, Laleci GB,
Twagirumukiza M, Jaulent MC
Karimi S, Metke-Jimenez A,
Kemp M, Wang C
Mitchell RJ, Bambach MR,
Muscatello D, McKenzie K,
Balogh ZJ
Australia
Compare to or map to other terminology
systems
Retrieve or analyse patient data
72
2013
Young AA, Prince JL
New Zealand
As an example
73
2015
Ibrahim A, Bucur A, Perez-Rey D,
Alonso E, de Hoog M, Dekker A,
Marshall MS
Automating lexical cross-mapping of
ICNP to SNOMED CT.
Binding SNOMED CT terms to
archetype elements. Establishing a
baseline of results.
Biomedical informatics: we are what
we publish.
Bridging data models and
terminologies to support adverse drug
event reporting using EHR data.
Cadec: A corpus of adverse drug
event annotations.
Can SNOMED CT as implemented in
New South Wales, Australia be used
for road trauma injury surveillance in
emergency departments?
Cardiovascular magnetic resonance:
Deeper insights through
bioengineering.
Case Study for Integration of an
Oncology Clinical Site in a Semantic
Interoperability Solution based on HL7
v3 and SNOMED-CT: Data
Transformation Needs.
United States
64
Netherlands
As an example
74
2014
Tanno LK, Calderon MA,
Goldberg BJ, Akdis CA,
Papadopoulos NG, Demoly P
France
Compare to or map to other terminology
systems
75
2014
He Z, Geller J, Elhanan G
United States
Compare to or map to other terminology
systems
77
2013
Dos Reis JC, Pruski C, Da
Silveira M, Reynaud-Delaître C
France
Description of SNOMED CT and other
standards
78
2013
Australia
As an example
79
2011
Butt L, Zuccon G, Nguyen A,
Bergheim A, Grayson N
Sampalli T, Shepherd M, Duffy J
Canada
Clinical Practice
80
2015
Gøeg KR, Cornet R, Andersen
SK
Denmark
Planned standard for electronic health
records
81
2015
Fritz JV, McVige J, Mechtler L
United States
82
2015
Dhakal S, Burrer SL, Winston CA,
Dey A, Ajani U, Groseclose SL
Planned standard for electronic health
records
Compare to or map to other terminology
systems
83
2013
84
2014
McDonald CJ, Vreeman DJ,
Abhyankar S
Plaza L
85
2013
Yasini M, Ebrahiminia V, Duclos
C, Venot A, Lamy JB
86
2014
88
2015
89
2014
Lopez J, Palacios-Alonso D,
Tortajada S, Moreno A, Casitas
E, Garcia-Gomez JM, Gonzalez
Otal R, Perez-Gonzalez A,
Martinez A, Parra Calderon CL,
Rivin E, Leal S, Ortiz Gordillo MJ
Tanno LK, Calderon MA,
Goldberg BJ, Gayraud J, Bircher
AJ, Casale T, Li J, SanchezBorges M, Rosenwasser LJ,
Pawankar R, Papadopoulos NG,
Demoly P
Gøeg KR, Chen R, Højen AR,
Elberg P
Categorization of allergic disorders in
the new World Health Organization
International Classification of
Diseases.
Categorizing the Relationships
between Structurally Congruent
Concepts from Pairs of Terminologies
for Semantic Harmonization.
Characterizing semantic mappings
adaptation via biomedical KOS
evolution: a case study investigating
SNOMED CT and ICD.
Classification of cancer-related death
certificates using machine learning.
Clinical vocabulary as a boundary
object in multidisciplinary care
management of multiple chemical
sensitivity, a complex and chronic
condition.
Clustering clinical models from local
electronic health records based on
semantic similarity.
Coding in behavioral neurology and
neuropsychiatry.
Coding of Electronic Laboratory
Reports for Biosurveillance, Selected
United States Hospitals, 2011.
Comment on "time to integrate clinical
and research informatics".
Comparing different knowledge
sources for the automatic
summarization of biomedical
literature.
Comparing the use of SNOMED CT
and ICD10 for coding clinical
conditions to implement laboratory
guidelines.
Computerized decision support
system and naive bayes models for
predicting the risk of relapse in breast
cancer.
90
2013
Hong Y, Kahn CE Jr
91
2014
92
2015
93
2014
Chalasani S, Jain P, Dhumal P,
Moghimi H, Wickramasinghe N
Zhou X, Zheng A, Yin J, Chen R,
Zhao X, Xu W, Cheng W, Xia T,
Lin S
Agrawal A, Elhanan G
94
2013
Tapuria A, Kalra D, Kobayashi S
95
2014
Fung KW, Richesson R,
United States
United States
Retrieve or analyse patient data
Spain
Compare to or map to other terminology
systems
France
Prove merit
Spain
Clinical Practice
Constructing a classification of
hypersensitivity/allergic diseases for
ICD-11 by crowdsourcing the allergist
community.
Brazil
As an example
Content analysis of physical
examination templates in electronic
health records using SNOMED CT.
Content analysis of reporting
templates and free-text radiology
reports.
Content architecture applications in
healthcare.
Context-Sensitive Spelling Correction
of Consumer-Generated Content on
Health Care.
Contrasting lexical similarity and
formal definitions in SNOMED CT:
consistency and implications.
Contribution of Clinical Archetypes,
and the Challenges, towards
Achieving Semantic Interoperability
for EHRs.
Coverage of rare disease names in
Denmark
Research
United States
Prospective content coverage
United States
As an example
China
As an example
United States
Terminology auditing
United Kingdom
Prospective content coverage
United States
Compare to or map to other terminology
Page 169 of 176
31/03/2016
ASSESS CT – D1.3
ID
Year
Authors
Title
Bodenreider O
standard terminologies and
implications for patients, providers,
and research.
Cross-domain targeted ontology
subsets for annotation: the case of
SNOMED CORE and RxNorm.
Crowdsourcing the verification of
relationships in biomedical ontologies.
Cue-based assertion classification for
Swedish clinical text-Developing a
lexicon for pyConTextSwe.
Current National Approach to
Healthcare ICT Standardization:
Focus on Progress in New Zealand.
Current state of medical device
nomenclature and taxonomy systems
in the UK: spotlight on GMDN and
SNOMED CT.
[Data coding in the Israeli healthcare
system - do choices provide the
answers to our system's needs?].
Data quality and clinical audit.
Decoding laboratory test names: A
major challenge to appropriate patient
care.
97
2014
López-García P, Lependu P,
Musen M, Illarramendi A
98
2013
99
2014
100
2015
Mortensen JM, Musen MA, Noy
NF
Velupillai S, Skeppstedt M, Kvist
M, Mowery D, Chapman BE,
Dalianis H, Chapman WW
Park YT, Atalag K
101
2013
White J, Carolan-Rees G
104
2013
Zelingher J, Ash N
105
106
2014
2013
Verma R
Passiment E, Meisel JL,
Fontanesi J, Fritsma G, Aleryani
S, Marques M
109
2013
110
2013
Gordon CL, Pouch S, Cowell LG,
Boland MR, Platt HL, Goldfain A,
Weng C
Maheronnaghsh R, Nezareh S,
Sayyah MK, Rahimi-Movaghar V
111
2013
112
2014
113
2013
Wei W-Q, Cronin RM, Xu H,
Lasko TA, Bastarache L, Denny
JC
Gobbel GT, Reeves R,
Jayaramaraja S, Giuse D, Speroff
T, Brown SH, Elkin PL, Matheny
ME
Greibe K
114
2014
Song TM, Park HA, Jin DL
116
2013
Lerner A, Schenk C, Miller M,
Jain A, Tatsuoka C
121
2014
Cohen DA, Takei H, Rivera AL
122
2014
Karlsson D, Nyström M, Cornet R
125
2014
Dewenter H, Heitmann KU,
Treinat L, Thun S
129
2015
Spencer A, Horridge K, Downs D
130
2014
Hulse NC, Long J, Xu X, Tao C
131
2015
132
2013
Alonso-Calvo R, Perez-Rey D,
Paraiso-Medina S, Claerhout B,
Hennebert P, Bucur A
Barrett N, Weber-Jahnke JH, Thai
V
135
2015
McInnes BT, Pedersen T
136
2013
137
2014
Goss FR, Zhou L, Plasek JM,
Broverman C, Robinson G,
Middleton B, Rocha RA
Lingren T, Deleger L, Molnar K,
Zhai H, Meinzen-Derr J, Kaiser M,
Stoutenborough L, Li Q, Solti I
138
2015
140
2015
142
2015
Pradhan S, Elhadad N, South BR,
Martinez D, Christensen L, Vogel
A, Suominen H, Chapman WW,
Savova G
Manohar N, Adam TJ, Pakhomov
SV, Melton GB, Zhang R
Dhombres F, Winnenburg R,
Case JT, Bodenreider O
Country
Usage Category
systems
Spain
Prospective content coverage
United States
Terminology auditing
Sweden
Translation
South Korea
Planned standard for electronic health
records
United Kingdom
Compare to or map to other terminology
systems
Israel
Planned standard for electronic health
records
United Kingdom
United States
As an example
Clinical Practice
Design and evaluation of a bacterial
clinical infectious diseases ontology.
United States
Compare to or map to other terminology
systems
Developing SNOMED-CT for decision
making and data gathering: a
software prototype for low back pain.
Development and evaluation of an
ensemble resource linking
medications to their indications.
Development and evaluation of
RapTAT: A machine learning system
for concept mapping of phrases from
medical narratives.
Development of a SNOMED CT
based national medication decision
support system.
Development of health information
search engine based on metadata
and ontology.
Diagnostic testing and medication
utilization in Alzheimer's disease in a
large de-identified database.
Discordant malignancy findings on
autopsy at a tertiary care hospital: A
continuing opportunity for quality
improvement.
Does SNOMED CT post-coordination
scale?
Effective ways for the transmission of
infection prevention data according to
German legal specifications via the
medical terminology SNOMED CT
used with HL7 CDA templates.
Empowering clinical data collection at
the point of care.
Enabling locally-developed content for
access through the infobutton by
means of automated concept
annotation.
Enabling semantic interoperability in
multi-centric clinical trials on breast
cancer.
Engineering natural language
processing solutions for structured
information from clinical text:
extracting sentinel events from
palliative care consult letters.
Evaluating semantic similarity and
relatedness over the semantic
grouping of clinical term pairs.
Evaluating standard terminologies for
encoding allergy information.
Iran
Clinical Practice
United States
Clinical Practice
United States
Retrieve or analyse patient data
Denmark
Clinical Practice
South Korea
Prove merit
United States
Retrieve or analyse patient data
United States
Retrieve or analyse patient data
Sweden
Design considerations
Germany
Prove merit
United Kingdom
Design considerations
United States
Retrieve or analyse patient data
Spain
Retrieve or analyse patient data
Canada
Retrieve or analyse patient data
United States
Illustrate terminology systems theory
United States
Compare to or map to other terminology
systems
Evaluating the impact of preannotation on annotation speed and
potential bias: natural language
processing gold standard
development for clinical named entity
recognition in clinical trial
announcements.
Evaluating the state of the art in
disorder recognition and normalization
of the clinical narrative.
United States
Compare to or map to other terminology
systems
United States
Retrieve or analyse patient data
Evaluation of Herbal and Dietary
Supplement Resource Term
Coverage.
Extending the coverage of
phenotypes in SNOMED CT through
post-coordination.
United States
Prospective content coverage
United States
Planned standard for electronic health
records
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ID
Year
Authors
Title
Country
Usage Category
143
2013
Jindal P, Roth D
Other
2014
Australia
Retrieve or analyse patient data
145
2013
Northey LC, Bhardwaj G, Curran
S, McGirr J
Dinh D, Tamine L, Boubekeur F
Algeria
Other
147
2015
Extraction of events and temporal
expressions from clinical narratives.
Eye trauma epidemiology in regional
Australia.
Factors affecting the effectiveness of
biomedical document indexing and
retrieval based on terminologies.
Food entries in a large allergy data
repository.
United States
144
United States
Prospective content coverage
148
2015
Formalizing biomedical concepts from
textual definitions.
Germany
Illustrate terminology systems theory
149
2014
Bousquet C, Sadou E, Souvignet
J, Jaulent MC, Declerck G
France
Compare to or map to other terminology
systems
150
2015
Varghese J, Dugas M
Germany
Prospective content coverage
151
2015
Italy
Compare to or map to other terminology
systems
152
2014
Global classification and coding of
hypersensitivity diseases - An EAACI
- WAO survey, strategic paper and
review.
Brazil
Compare to or map to other terminology
systems
153
2015
Autorino R, Gambacorta MA,
Tagliaferri L, Campitelli M,
Meldolesi E, Gatta R, Frascino V,
Dinapoli N, Nardangeli A,
Mattiucci GC, Damiani A,
Valentini V
Demoly P, Tanno LK, Akdis CA,
Lau S, Calderon MA, Santos AF,
Sanchez-Borges M, Rosenwasser
LJ, Pawankar R, Papadopoulos
NG
Haas JP
Formalizing MedDRA to support
semantic reasoning on adverse drug
reaction terms.
Frequency analysis of medical
concepts in clinical trials and their
coverage in MeSH and SNOMED-CT.
From datasets to predictive models in
cervical cancer: An ontology to mine
data for large data-base.
United States
Description of SNOMED CT and other
standards
154
2015
Harris MR, Langford LH, Miller H,
Hook M, Dykes PC, Matney SA
United States
Other
155
2015
Schulz S, Martínez-Costa C
Austria
Compare to or map to other terminology
systems
156
2014
Madden A
United Kingdom
Other
157
2013
Ash N, Levy I
Israel
Other
158
2015
Richesson RL, Chute CG
United States
Other
160
2014
Akyurek AO
Turkey
As an example
161
2014
Austria
Compare to or map to other terminology
systems
162
2013
Rodrigues JM, Schulz S, Rector
A, Spackman K, Millar J,
Campbell J, Ustün B, Chute CG,
Solbrig H, Della Mea V, Persson
KB
Agrawal A, Perl Y, Chen Y,
Elhanan G, Liu M
Glossary of terms for information
technology and pearls of wisdom for
implementation and use.
Harmonizing and extending standards
from a domain-specific and bottom-up
approach: an example from
development through use in clinical
applications.
Harmonizing SNOMED CT with
BioTopLite: An Exercise in Principled
Ontology Alignment.
Health informatics and the importance
of coding.
[Health Information Technology where are we heading?].
Health information technology data
standards get down to business:
Maturation within domains and the
emergence of interoperability.
Hospital and laboratory information
management systems, Hastane ve
laboratuvar bilgi yonetim sistemleri.
[Turkish, English]
ICD-11 and SNOMED CT Common
Ontology: circulatory system.
United States
Terminology auditing
164
2013
Agrawal A, Perl Y, Elhanan G
United States
Terminology auditing
165
2013
Henriksson A, Conway M, Duneld
M, Chapman WW
Sweden
Terminology auditing
166
2015
United States
As an example
169
2013
As an example
2015
Australia
Retrieve or analyse patient data
171
2013
Implementation and management of a
biomedical observation dictionary in a
large healthcare information system.
Implementing an event tool in Cerner
FirstNet to identify the physiotherapy
service in the emergency department
and determine its impact on patient
care.
Implementing an interface terminology
for structured clinical documentation.
France
170
Tilkemeier PL, Mahmarian JJ,
Wolinsky DG, Denton EA
Vandenbussche P-Y, Cormont S,
Andre C, Daniel C, Delahousse J,
Charlet J, Lepage E
Alkhouri H, Murray M, Maka K,
Joyce S, Haydon R, McCarthy S
Identifying inconsistencies in
SNOMED CT problem lists using
structural indicators.
Identifying problematic concepts in
SNOMED CT using a lexical
approach.
Identifying synonymy between
SNOMED clinical terms of varying
length using distributional analysis of
electronic health records.
ImageGuideTM Update.
United States
Clinical Practice
172
2014
Hungary
Illustrate terminology systems theory
173
2014
Martínez-Costa C, Kalra D,
Schulz S
Austria
Description of SNOMED CT and other
standards
174
2013
Azcarate MC, Vazquez JM, Lopez
MM
Spain
Compare to or map to other terminology
systems
175
2013
Postorino M, Limido A, Teatini U,
Implementing reusable software
components for SNOMED CT
diagram and expression concept
representations.
Improving EHR semantic
interoperability: future vision and
challenges.
Improving image retrieval
effectiveness via query expansion
using mesh hierarchical structure.
[In Process Citation].
Italy
Translation
Plasek JM, Goss FR, Lai KH, Lau
JJ, Seger DL, Blumenthal KG,
Wickner PG, Slight SP, Chang
FY, Topaz M, Bates DW, Zhou L
Petrova A, Ma Y, Tsatsaronis G,
Kissa M, Distel F, Baader F,
Schroeder M
Rosenbloom ST, Miller RA,
Adams P, Madani S, Khan N,
Shultz EK
Bánfai B, Porció R, Kovács T
Page 171 of 176
31/03/2016
ASSESS CT – D1.3
ID
Year
Authors
Amuso S, Torino C, Di Iorio BR,
Martorano C, Marino C, Morosetti
M, Santoro A
Oluoch T, de Keizer N, Kwaro D,
Wattoyi I, Okeyo N, Cornet R
176
2013
177
2013
Galanter W, Falck S, Burns M,
Laragh M, Lambert BL
178
2014
Liaw ST, Taggart J, Yu H, de
Lusignan S, Kuziemsky C, Hayen
A
179
2014
Kim TY, Hardiker N, Coenen A
180
2013
Marcos M, Maldonado JA,
Martínez-Salvador B, Boscá D,
Robles M
181
2015
Dentler K, Cornet R
182
2015
183
2014
185
2014
Sulaiman IM, Sheikh Ahmad MK,
Bouzekri K, Ismail D
Jurkovich MW, Ophaug M,
Salberg S, Monsen K
Conn J
186
2013
Griffon N, Charlet J, Darmoni S
187
2015
Bresó A, Sáez C, Vicente J,
Larrinaga F, Robles M, GarcíaGómez JM
188
2013
Ba M, Diallo G
189
2015
Cartagena FP, Schaeffer M, Rifai
D, Doroshenko V, Goldberg HS
190
2014
Afzal Z, Schuemie MJ,
Sturkenboom MCJM, Kors JA
191
2014
192
2014
Lee D, de Keizer N, Lau F, Cornet
R
Pan X, Cimino JJ
193
2014
194
2013
196
2015
197
2014
198
2014
Rudniy A, Song M, Geller J
199
2015
200
2014
Hopkins H, Thomas NV, Crump
JA, Gonzalez IJ, Guerin PJ,
Newton PN, Schellenberg D, Bell
D, Reyburn H
Jamoulle M, Cardillo E, Roumier
J, Warnier M, Vander Stichele R
201
2013
202
2014
Balkanyi L, Schulz S, Cornet R,
Bodenreider O
Højen AR, Sundvall E, Gøeg KR
203
2013
Winnenburg R, Bodenreider O
204
2015
Tao S, Cui L, Zhu W, Sun M,
Bodenreider O, Zhang GQ
205
2015
Marco-Ruiz L, Maldonado JA,
Karlsen R, Bellika JG
206
2015
Zhu W, Zhang GQ, Tao S, Sun M,
Cui L
Edeler B, Majeed RW, Ahlbrandt
J, Stöhr MR, Stommel F, Brenck
F, Thun S, Röhrig R
Schulz S, Bernhardt-Melischnig J,
Kreuzthaler M, Daumke P,
Boeker M
Bouamrane MM, Tao C, Sarkar
IN
Zhang GQ, Zhu W, Sun M, Tao S,
Bodenreider O, Cui L
Title
Country
Usage Category
Inconsistencies between recorded
opportunistic infections and WHO HIV
staging in western Kenya.
Indication-based prescribing prevents
wrong-patient medication errors in
computerized provider order entry
(CPOE).
Kenya
As an example
United States
Clinical Practice
Integrating electronic health record
information to support integrated care:
practical application of ontologies to
improve the accuracy of diabetes
disease registers.
Inter-terminology mapping of nursing
problems.
Australia
Prove merit
United States
Compare to or map to other terminology
systems
Interoperability of clinical decisionsupport systems and electronic health
records using archetypes: a case
study in clinical trial eligibility.
Intra-axiom redundancies in
SNOMED CT.
Introducing SNOMED CT to
cardiology, from Malaysia.
Investigation of The Omaha System
for dentistry.
IT experts push translator systems to
convert doc-speak into ICD-10 codes.
Knowledge representation and
management: towards an integration
of a semantic web in daily health
practice.
Knowledge-Based Personal Health
System to empower outpatients of
diabetes mellitus by means of P4
Medicine.
Large-scale biomedical ontology
matching with ServOMap.
Leveraging the NLM map from
SNOMED CT to ICD-10-CM to
facilitate adoption of ICD-10-CM.
Linguistic variability and clinical
terminology in a large dutch general
practitioners database.
Literature review of SNOMED CT use.
Spain
Description of SNOMED CT and other
standards
Netherlands
Terminology auditing
Malaysia
United States
Planned standard for electronic health
records
As an example
United States
Other
France
Compare to or map to other terminology
systems
Spain
Design considerations
France
United States
Compare to or map to other terminology
systems
Clinical Practice
Netherlands
Prospective content coverage
Canada
Other
Locating relevant patient information
in electronic health record data using
representations of clinical concepts
and database structures.
LOINC in Prehospital Emergency
Medicine in Germany - Experience of
the `DIRK´-Project.
Machine vs. human translation of
SNOMED CT terms.
United States
Compare to or map to other terminology
systems
Germany
As an example
Austria
Translation
Managing interoperability and
complexity in health systems.
MaPLE: A MapReduce Pipeline for
Lattice-based Evaluation and Its
Application to SNOMED CT.
Mapping biological entities using the
longest approximately common prefix
method.
Mapping fever aetiologies in malariaendemic areas: An interactive, openaccess, on-line map.
United Kingdom
Other
South Korea
Terminology auditing
United Kingdom
Design considerations
Belgium
As an example
Mapping French terms in a Belgian
guideline on heart failure to
international classifications and
nomenclatures: the devil is in the
detail.
Medical concept representation: the
years beyond 2000.
Methods and Applications for
Visualization of SNOMED CT
Concept Sets.
Metrics for assessing the quality of
value sets in clinical quality measures.
Mining Relation Reversals in the
Evolution of SNOMED CT Using
MapReduce.
Multidisciplinary Modelling of
Symptoms and Signs with Archetypes
and SNOMED-CT for Clinical
Decision Support.
NEO: Systematic Non-Lattice
Embedding of Ontologies for
Comparing the Subsumption
Sweden
Compare to or map to other terminology
systems
Denmark
Other
United States
Description of SNOMED CT and other
standards
United States
Terminology auditing
Norway
Terminology auditing
United States
Design considerations
United States
Terminology auditing
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ASSESS CT – D1.3
ID
Year
Authors
207
2014
208
2013
Adamusiak T, Shimoyama N,
Shimoyama M
Mills R
209
2014
Martínez-Costa C, Schulz S
210
2013
Soguero-Ruiz C, Lechuga-Suárez
L, Mora-Jiménez I, Ramos-López
J, Barquero-Pérez Ó, GarcíaAlberola A, Rojo-Álvarez JL
211
2013
Demir OM, Ahmed Z, Logan RPH
212
2014
214
2013
Bronnert J, Daube J, Jopp G,
Peterson K, Rihanek T,
Scichilone R, Tucker V
Freeman C, Atkinson K, Hart D,
Bowles L, Gutteridge C
215
2014
216
2013
217
2015
218
2015
219
2013
Bansal A, McGregor DH, Anand
O, Singh M, Rao D, Cherian R,
Wani SB, Rastogi A, Singh V,
House J, Jones PG, Sharma P
220
2014
221
2015
Griffon N, Merabti T, Cormont S,
Tariel-Laurent S, Massari P,
Lepage E, Chniti A, Daniel C,
Darmoni SJ
Quesada-Martínez M, FernándezBreis JT, Stevens R, Mikroyannidi
E
222
2013
Hagen MS, Jopling JK, Buchman
TG, Lee EK
223
2014
Sutherland M, Nathanson LA,
Horng S
224
2013
Ranallo PA, Adam TJ, Nelson KJ,
Krueger RF, LaVenture M, Chute
CG
225
2015
Lamy JB, Venot A, Duclos C
226
2015
Gu H, Chen Y, He Z, Halper M,
Chen L
227
2015
Højen AR, Gøeg KR, Elberg PB
228
2014
230
2014
231
2015
Horridge M, Parsia B, Noy NF,
Musenm MA
Zhou L, Lu Y, Vitale CJ, Mar PL,
Chang F, Dhopeshwarkar N,
Rocha RA
Wang H-Q, Zhou T-S, Zhang Y-F,
Chen L, Li J-S
232
2014
Safari L, Patrick JD
233
2015
Monsen KA, Finn RS, Fleming
TE, Garner EJ, LaValla AJ,
Riemer JG
234
2014
Ashley C, Feinberg Z
235
2013
Abbas Z, Magrey MN
Somers EC, Marder W, Cagnoli
P, Lewis EE, DeGuire P, Gordon
C, Helmick CG, Wang L, Wing JJ,
Dhar JP, Leisen J, Shaltis D,
McCune WJ
Vreeman DJ, Richoz C
Komenda M, Schwarz D,
Svancara J, Vaitsis C, Zary N,
Dusek L
Gaywood I, Pande I
Title
Relationship in SNOMED CT and in
FMA Using MapReduce.
Next generation phenotyping using
the unified medical language system.
Often mismatched shoes of
healthcare.
Ontology content patterns as bridge
for the semantic representation of
clinical information.
Ontology for heart rate turbulence
domain from the conceptual model of
SNOMED-CT.
Country
Usage Category
United States
Design considerations
Austria
Compare to or map to other terminology
systems
Description of SNOMED CT and other
standards
Spain
United Kingdom
Design considerations
Optimising the use of faecal
calprotectin for early diagnosis of IBD
in primary care.
Optimizing data representation
through the use of SNOMED CT.
United States
Retrieve or analyse patient data
United Kingdom
Description of SNOMED CT and other
standards
Patient safety and clinical efficiency
gains following implementation of an
integrated health information system
in east London.
Population-based incidence and
prevalence of systemic lupus
erythematosus: The Michigan lupus
epidemiology and surveillance
program.
Possibilities and Implications of Using
the ICF and Other Vocabulary
Standards in Electronic Health
Records.
Practical use of medical terminology
in curriculum mapping.
United States
Research
United States
Research
Czech Republic
Illustrate terminology systems theory
United Kingdom
Description of SNOMED CT and other
standards
Preparing for electronic health
records: Standardizing terminology.
Presence or absence of intestinal
metaplasia but not its burden is
associated with prevalent high-grade
dysplasia and cancer in Barrett's
esophagus.
Preservation of information in
terminology transcoding.
United States
Prospective content coverage
France
Retrieve or analyse patient data
Spain
Compare to or map to other terminology
systems
Prioritising lexical patterns to increase
axiomatisation in biomedical
ontologies. The role of localisation
and modularity.
Priority queuing models for hospital
intensive care units and impacts to
severe case patients.
Proof of concept application to extract
structured chief complaints using an
ontology based method.
Psychological assessment
instruments: a coverage analysis
using SNOMED CT, LOINC and QS
terminology.
PyMedTermino: an open-source
generic API for advanced terminology
services.
Quality Assurance of UMLS Semantic
Type Assignments Using SNOMED
CT Hierarchies.
Re-use of SNOMED CT subset in
development of the Danish national
standard for home care nursing
problems.
Reasoning based quality assurance of
medical ontologies: a case study.
Representation of information about
family relatives as structured data in
electronic health records.
Research and Development of
Semantics-based Sharable Clinical
Pathway Systems.
Restricted natural language based
querying of clinical databases.
Rigor in electronic health record
knowledge representation: lessons
learned from a SNOMED CT clinical
content encoding exercise.
Risk factors for progression of
barrett's esophagus among the
veterans of veterans integrated
service network 2.
Risk of cardiovascular disease among
patients with psoriatic arthritis
compared to ankylosing spondylitis
(retrospective cohort study).
United States
Compare to or map to other terminology
systems
United States
Research
United States
Clinical Practice
France
Prospective content coverage
United States
Compare to or map to other terminology
systems
Denmark
Terminology auditing
United States
Design considerations
United States
China
Compare to or map to other terminology
systems
Retrieve or analyse patient data
Australia
Design considerations
United States
Compare to or map to other terminology
systems
Compare to or map to other terminology
systems
United States
United States
As an example
United States
Clinical Practice
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ASSESS CT – D1.3
ID
Year
Authors
Title
Country
Usage Category
236
2013
Ochs C, Perl Y, Geller J, Halper
M, Gu H, Chen Y, Elhanan G
United States
Illustrate terminology systems theory
237
2015
Ochs C, Geller J, Perl Y, Chen Y,
Xu J, Min H, Case JT, Wei Z
Portugal
Terminology auditing
238
2015
Oliveira R, Costa Braga A, Theias
Manso R, Ferreira M
United States
As an example
239
2014
He Z, Morrey CP, Perl Y, Elhanan
G, Chen L, Chen Y, Geller J
Scalability of abstraction-networkbased quality assurance to large
SNOMED hierarchies.
Scalable quality assurance for large
SNOMED CT hierarchies using
subject-based subtaxonomies.
Schistosoma in histopathological
specimens in an European context:
Series of 7 portuguese cases.
Sculpting the UMLS Refined
Semantic Network.
Austria
Compare to or map to other terminology
systems
240
2015
Semantic Alignment between ICD-11
and SNOMED CT.
United States
Compare to or map to other terminology
systems
241
2014
Prospective content coverage
2015
France
Clinical Practice
243
2015
Semantic analysis of SNOMED CT for
a post-coordinated database of
histopathology findings.
Semantic enrichment of clinical
models towards semantic
interoperability. The heart failure
summary use case.
Semantic interoperability platform for
healthcare information exchange.
Austria
242
Rodrigues JM, Robinson D, Della
Mea V, Campbell J, Rector A,
Schulz S, Brear H, Üstün B,
Spackman K, Chute CG, Millar J,
Solbrig H, Brand Persson K
Campbell WS, Campbell JR,
West WW, McClay JC, Hinrichs
SH
Martínez-Costa C, Cornet R,
Karlsson D, Schulz S, Kalra D
United States
Compare to or map to other terminology
systems
244
2013
Sweden
Compare to or map to other terminology
systems
245
2014
Karlsson D, Gøeg KR, Örman H,
Højen AR
Spain
Prospective interrater agreement
246
2015
Paraiso-Medina S, Perez-Rey D,
Bucur A, Claerhout B, AlonsoCalvo R
Taiwan
Retrieve or analyse patient data
247
2013
Hsieh SL, Chang WY, Chen CH,
Weng YC
Austria
As an example
248
2013
Denmark
Description of SNOMED CT and other
standards
250
2014
2015
Spain
Description of SNOMED CT and other
standards
Translation
252
2013
Spain
Illustrate terminology systems theory
253
2015
SNOMED CT adoption in Denmark-why is it so hard?
SNOMED CT in a language isolate:
an algorithm for a semiautomatic
translation.
SNOMED CT module-driven clinical
archetype management.
SORTA: a system for ontology-based
re-coding and technical annotation of
biomedical phenotype data.
Denmark
251
Rodrigues JM, Schulz S, Rector
A, Spackman K, Üstün B, Chute
CG, Della Mea V, Millar J,
Persson KB
Højen AR, Elberg PB, Andersen
SK
Perez-de-Viñaspre O, Oronoz M
Semantic interoperation and
electronic health records: context
sensitive mapping from SNOMED CT
to ICD-10.
Semantic Krippendorff's α for
measuring inter-rater agreement in
SNOMED CT coding studies.
Semantic Normalization and Query
Abstraction Based on SNOMED-CT
and HL7: Supporting Multicentric
Clinical Trials.
Semantic similarity measures in the
biomedical domain by leveraging a
web search engine.
Sharing ontology between ICD 11 and
SNOMED CT will enable seamless reuse and semantic interoperability.
Netherlands
As an example
254
2014
Italy
As an example
255
2013
United States
Compare to or map to other terminology
systems
256
2014
Gaywood I, Pande I, Cheetham E
United Kingdom
Design considerations
257
2013
Ury AG
United States
As an example
258
2015
Wei D, Helen Gu H, Perl Y,
Halper M, Ochs C, Elhanan G,
Chen Y
Standardized data collection (SDC)
for rectal cancer: Towards
personalized medicine.
Standardizing documentation for
postoperative nausea and vomiting in
the electronic health record.
Standardizing terminology for
musculoskeletal disorders.
Storing and interpreting genomic
information in widely deployed
electronic health record systems.
Structural measures to track the
evolution of SNOMED CT hierarchies.
United States
Terminology auditing
259
2014
Ohno-Machado L
United States
As an example
260
2015
Paterson GI, Christie S, Bonney
W, Thibault-Halman G
Canada
Research
262
2014
Rafiei M, Pieczkiewicz D, Khairat
S, Westra BL, Adam T
United States
Prove merit
263
2014
Kleensang A, Maertens A,
Rosenberg M, Fitzpatrick S, Lamb
J, Auerbach S, Brennan R,
Crofton KM, Gordon B, Fornace
Jr AJ, Gaido K, Gerhold D, Haw
R, Henney A, Ma'Ayan A,
McBride M, Monti S, Ochs MF,
Pandey A, Sharan R, Stierum R,
Structuring text and standardizing
data for clinical and population health
applications.
Synoptic operative reports for spinal
cord injury patients as a tool for data
quality.
Systemized Nomenclature of
Medicine Clinical Terms for the
structured expression of perioperative
medication management
recommendations.
t4 workshop report.
United States
As an example
Aime X, Traore L, Chniti A, Sadou
E, Ouagne D, Charlet J, Jaulent
M-C, Darmoni S, Griffon N,
Amardeilh F, Bascarane L,
Lepage E, Daniel C
Campbell JR, Brear H, Scichilone
R, White S, Giannangelo K,
Carlsen B, Solbrig H, Fung KW
Allones JL, Taboada M, Martinez
D, Lozano R, Sobrido MJ
Pang C, Sollie A, Sijtsma A,
Hendriksen D, Charbon B, de
Haan M, de Boer T, Kelpin F,
Jetten J, van der Velde JK, Smidt
N, Sijmons R, Hillege H, Swertz
MA
Meldolesi E, Van Soest J,
Damiani A, Dekker A,
Gambacorta MA, Valentini V
DeBlieck C, LaFlamme AF,
Rivard MJ, Monsen KA
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ID
Year
Authors
Tugendreich S, Willett C,
Wittwehr C, Xia J, Patton GW,
Arvidson K, Bouhifd M, Hogberg
HT, Luechtefeld T, Smirnova L,
Zhao L, Adeleye Y, Kanehisa M,
Carmichael P, Andersen ME,
Hartung T
Meystre SM, Ferrández O,
Friedlin FJ, South BR, Shen S,
Samore MH
Windle T, McClay JC, Windle JR
Title
Country
Usage Category
Text de-identification for privacy
protection: A study of its impact on
clinical text information content.
The impact of domain knowledge on
structured data collection and
templated note design.
The impact of using the Bethesda
System for reporting thyroid cytology
diagnostic criteria on the follicular
lesion of undetermined significance
category.
The influence of similarity between
concepts in evolving biomedical
ontologies for mapping adaptation.
The ligurian human immunodeficiency
virus clinical network: a web tool to
manage patients with human
immunodeficiency virus in primary
care and multicenter clinical trials.
United States
Research
United States
Research
United States
Retrieve or analyse patient data
Luxembourg
Design considerations
Italy
As an example
The NLM value set authority center.
United States
Description of SNOMED CT and other
standards
The readiness of SNOMED problem
list concepts for meaningful use of
electronic health records.
The role of taxonomies in social
media and the semantic web for
health education. A study of
SNOMED CT terms in YouTube
health video tags.
The use of big data in transfusion
medicine.
Three myths of ICD-10-CM/PCS.
United States
Terminology auditing
Greece
Prospective content coverage
United Kingdom
Retrieve or analyse patient data
United States
Towards Converting Clinical Phrases
into SNOMED CT Expressions.
Transfer learning based clinical
concept extraction on data from
multiple sources.
U-path: An undirected path-based
measure of semantic similarity.
UCbase 2.0: ultraconserved
sequences database (2014 update).
United States
Compare to or map to other terminology
systems
Retrieve or analyse patient data
China
As an example
United States
Illustrate terminology systems theory
Italy
Research
Understanding semantic mapping
evolution by observing changes in
biomedical ontologies.
Usability of HL7 and SNOMED CT
Standards in Java Persistence API
Environment.
User-directed coordination in
SNOMED CT.
France
Illustrate terminology systems theory
Hungary
Description of SNOMED CT and other
standards
Netherlands
Design considerations
Using Semantic Web technology to
support icd-11 textual definitions
authoring.
Using Standardized Lexicons for
Report Template Validation with
LexMap, a Web-based Application.
Using the wisdom of the crowds to
find critical errors in biomedical
ontologies: a study of SNOMED CT.
Utility-preserving privacy protection of
textual healthcare documents.
Validating an ontology-based
algorithm to identify patients with type
2 diabetes mellitus in electronic health
records.
Visualizing sets of SNOMED CT
concepts to support consistent
terminology implementation and reuse
of clinical data.
Water, water, everywhere, and not a
drop to drink.
United States
Compare to or map to other terminology
systems
United States
Prospective content coverage
United States
Terminology auditing
Spain
Research
Iran
Retrieve or analyse patient data
Denmark
Research
United States
Other
264
2014
268
2013
271
2014
Lee B, Smola B, Roh MH,
Hughes DT, Miller BS, Jing X
273
2014
274
2013
275
2013
277
2013
Dos Reis JC, Dinh D, Pruski C,
Da Silveira M, Reynaud-Delaître
C
Fraccaro P, Pupella V, Gazzarata
R, Dentone C, Cenderello G, De
Leo P, Bozzano F, Casalino
Finocchio G, De Maria A,
Fenoglio D, Filaci G, Guerra M, Di
Biagio A, Mantia E, Orofino G,
Ferrea G, Viscoli C, Giacomini M
Bodenreider O, Nguyen D,
Chiang P, Chuang P, Madden M,
Winnenburg R, McClure R,
Emrick S, D'Souza I
Agrawal A, He Z, Perl Y, Wei D,
Halper M, Elhanan G, Chen Y
278
2013
Konstantinidis S, FernandezLuque L, Bamidis P, Karlsen R
279
2015
Pendry K
281
2014
Bowman S
283
2013
Kate RJ
284
2014
Lv X, Guan Y, Deng B
285
2014
286
2014
287
2014
McInnes BT, Pedersen T, Liu Y,
Melton GB, Pakhomov SV
Lomonaco V, Martoglia R,
Mandreoli F, Anderlucci L,
Emmett W, Bicciato S, Taccioli C
dos Reis JC, Pruski C, Da Silveira
M, Reynaud-Delaître C
289
2014
Antal G, Végh AZ, Bilicki V
291
2013
Cornet R, Nyström M, Karlsson D
293
2013
Jiang G, Solbrig HR, Chute CG
294
2015
Hostetter J, Wang K, Siegel E,
Durack J, Morrison JJ
295
2015
296
2014
Mortensen JM, Minty EP,
Januszyk M, Sweeney TE, Rector
AL, Noy NF, Musen MA
Sanchez D, Batet M, Viejo A
297
2014
Rahimi A, Liaw ST, Taggart J,
Ray P, Yu H
299
2013
Randorff Højen A, Sundvall E,
Rosenbeck Gøeg K
300
2014
Carnahan D
301
2013
Denecke K, Brooks E
Web science in medicine and
healthcare.
Germany
As an example
302
2014
What's in a class? Lessons learnt
from the ICD - SNOMED CT
harmonisation.
Austria
Compare to or map to other terminology
systems
303
2014
Schulz S, Rodrigues JM, Rector
A, Spackman K, Campbell J,
Ustün B, Chute CG, Solbrig H,
Della Mea V, Millar J, Brand
Persson K
Stearns M, Fuller J
What's the difference? SNOMED CT
and ICD systems are suited for
different purposes.
United States
Description of SNOMED CT and other
standards
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ASSESS CT – D1.3
ID
Year
Authors
Title
Country
Usage Category
304
2014
Chasin R, Rumshisky A, Uzuner
O, Szolovits P
Word sense disambiguation in the
clinical domain: a comparison of
knowledge-rich and knowledge-poor
unsupervised methods.
United States
Illustrate terminology systems theory
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