Project Acronym:
Contract Number:
Starting Date:
Ending Date:
Deliverable Number:
Title of Deliverable:
Work-Package of the Deliverable:
Deliverable Type:
Distribution:
Contractual Date of Delivery to the CEC:
Actual Date of Delivery to the CEC:
Author(s):
INCA
CIP 621006
01/01/2014
30/06/2016
D5.4
Socio Economic Impact Assessment
Planning for Sustainability
Report
PU
30/04/2016
20/06/2016
Kenus Informatica
Contact point: Lars . Berger @ kenus . es
1
1
1
1
1
11
Other Contributors: All other INCA Partners
Abstract:
INCA Pilot results are analyzed with respect to their impact and effectiveness. In
4 out of 5 pilots the collected data clearly shows that INCA Care Pathways have a
positive effects on Patient Satisfaction and Quality of Life. Further, generally
there are savings brought about with the usage of the tool.
When plotting results in the cost-effectiveness plane, INCA treatment, turns out
to be dominant and should be preferred over control group treatment/treatment
as usual.
Project Co-ordinator
Company Name:
IDI EIKON
Name of representative:
Miguel Alborg
Address:
C/
Benjamín
Franklin,
27
Parque Tecnológico de Valencia
46980 – Paterna, SPAIN
Phone Number
+34 96 112 40 00
Fax Number:
+34 96 112 40 54
E-mail:
[email protected]
Project WEB site address: http://www.in3ca.eu
ICT PSP
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COPYRIGHTS
© 2016 The INCA Consortium, consisting of:











Investigación y Desarrollo Informático, Spain
Ayuntamiento Quart de Poblet, Spain
Interfusion Services, Cyprus
Kenus Informática, Spain
Especializada y Primaria L’Horta Manises (Hospital de Manises), Spain
Dimos Geroskipou, Cyprus
Ventspils Pilsetas Domes Socialais Dienests, Latvia
Ziemelkurzemes Regionala Slimnica Sia, Latvia
Hrvatski Zavod Za Zdravstveno Osiguranje, Croatia
Grad Rijeka, Croatia
Fundación para la Formación e Investigación Sanitaria de la Región
de Murcia, Spain
All rights reserved.
This document may not be copied, reproduced, or modified in whole or in
part for any purpose without written permission from the INCA Consortium.
In presence of such written permission, or when the circulation of the
document is termed as “public”, an acknowledgement of the authors and of
all applicable portions of the copyright notice must be clearly referenced.
This document may change without prior advice.
For further information related to this Deliverable or to the INCA project
please visit the project Web site http://www.in3ca.eu or contact the Project
Coordinator, email to: [email protected].
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DOCUMENT HISTORY
Version
0.1
Issue Date
28/10/2014
0.2
0.3
0.4
29/03/2016
21/05/2016
21/06/2016
1.0
22/06/2016
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Stage Content and changes
Draft
Document draft created (L. T. Berger)
Restructuring (L. T. Berger)
Draft
Draft
Unification of partner input (L.T. Berger)
Draft
Update according to pilot partner input
(L.T. Berger)
Final
Final revision (J. Farinos)
ICT PSP
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EXECUTIVE SUMMARY
The main question for us here is, whether the changes brought about with
the introduction of INCA are cost-effective or not, and we use the costeffectiveness plane to answer this question.
In 4 out of 5 pilots the collected data clearly shows that INCA Care
Pathways have a positive effects on Patient Satisfaction and Quality of Life.
Further, generally there are savings brought about with the usage of the
INCA/ADSUM+ software tool.
When plotting results in the cost-effectiveness plane, INCA treatment,
turns out to be dominant and should be preferred over control group
treatment/treatment as usual.
For the Ventspils and the Rijeka pilot we did not have all data to plot results
in the cost-effectiveness plane. However, also in Ventspils INCA had
sufficient positive effects to be continued after the official EU project ends.
This makes it a total of 4 out of 5 pilots that will continue after EU funding
ends.
Finally, in Appendix I we look at the MAFEIP tool that has recently been
provided by the European Innovation Partnership on Active and Healthy
Ageing (EIP-AHA), and outline the difficulties we encounter in directly
mapping INCA pilot outputs to MAFEIP tool inputs.
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TABLE OF CONTENTS
1 Context ....................................................................................................... 6 1.1 IN3CA – A General Introduction.......................................................... 6 1.2 Work Package 5 Overview ................................................................. 6 1.3 Introduction to Cost Effectiveness ....................................................... 7 2 Manises/Quart Pilot CUA ................................................................................ 9 3 Murcia Pilot CUA ......................................................................................... 12 4 Cyprus Pilot CUA......................................................................................... 14 5 Croatia Pilot CUA ........................................................................................ 16 6 Ventspils/Latvia Pilot CUA ............................................................................ 18 7 Conclusions................................................................................................ 19 8 Annex I ..................................................................................................... 20 8.1 Introduction to EIP-AHA and MAFEIP ................................................. 20 8.2 MAFEIP Structure and Parameters .................................................... 21 8.3 Matching INCA Results to MAFEIP Input Parameters ............................ 22 Page 5 of 23
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1 CONTEXT
1.1
IN3CA – A General Introduction
The European project INCA (www.in3ca.eu) deploys a multi-channel,
patient centred, integrated socio-sanitary care platform. Social services,
medical organizations, patients, and private care givers are able to interact
with each other through any device capable of running an Internet browser.
Serving content from the Cloud allows access anywhere at any time.
INCA’s has started pragmatic deployment in five pilot sites across Europe.
Pilots run for at least one year (optimally one and a half year), followed by
an evaluation to validate the implementation of the model and its impact as
well as its market replication potential in other countries. INCA pilots
impact more than 125000 users and directly engage with 1550 active users.
1.2
Work Package 5 Overview
An overview of all WP5 deliverables is given in Table 1—1. D5.1 Market
Trends Overview, is public and, hence, mainly reviews publically available
information related to the integrated care market and its savings potential
(http://www.in3ca.eu/?wpfb_dl=104). Additionally, statistics, predecessor
and companion projects are taken into account. Information that is
strategically linked to the INCA objective of sustainability is instead treated
in the consortium internal (confidential) deliverables D5.2 and D5.3. D5.2
on sustainability strategy specifically analyses INCA from the point of view
of Return on Investment of the INCA End Customers. As such it specifically
reflects the opinion of the INCA Pilot responsible in Latvia, Spain, Croatia
and Cyprus. D5.3 explains how the private INCA consortium members plan
to build a sustainable business on INCA and finally this deliverable D5.4
investigates if INCA is a good idea for patients/society.
Table 1—1: INCA WP5 Deliverable Overview.
Deliverable Title
D5.1 Market Trends Overview
D5.2 Sustainability Strategies (public
and private)
D5.3 Business Plan Production
D5.4 Socio-Economic Impact Assessment
Page 6 of 23
Month
M12
M18
Nature
report
report
Dissemination
public
confidential
M21
M28
report
report
confidential
public
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Introduction to Cost Effectiveness
In D5.2 we have looked at the extra costs produced by INCA, on the one
hand due to product costs (e.g. license, customization and maintenance
fees) and on the other hand due to adoption cost as personal has to be
reorganized and trained to use the new tool and the care pathways
implemented with it.
Further, we have predicted cost reductions to be brought about with INCA
due to the fact that we expected hospital visits and the length of stays to be
reduced while we also expected the shift of some of the workload to less
expensive primary care centres.
The outcome was that 4 of the 5 INCA Pilots are sustainable and will be
continued after the INCA project ends.
Two things are worth noting:
1) The above cost/sustainability analysis was based on a prediction.
2) There was no mentioning of the benefits (i.e. the effects) of INCA for
the patients.
In the meantime, in WP4 we have collected the relevant data to address
these two points with detailed results already presented in the public
deliverable
D4.4
on
“Pilots:
Trials
Testing
&
Validation”
(http://www.in3ca.eu/?wpfb_dl=147).
The main question for us here is, whether the changes brought about with
the introduction of INCA are cost-effective or not, and we use the costeffectiveness plane like in Petrou20111, Black19902 to answer this question.
For convenience, this plane is reproduced from Petrou20111 in Figure 1-1.
1
Petrou, S. and Gray, A.; Economic evaluation alongside randomised
controlledrials: design, conduct, analysis, and reporting. BMJ; 342: d1548, doi:
10.1136/bmj.d1548
2
Black W.C., The CE Plane: a graphic representation of cost-effectiveness. Med
Decis Making 1990; 10:212-4
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Figure 1-1: Cost-effectiveness plane. The x-axis shows the difference in effectiveness
between the treatments and the y-axis shows the difference in cost, source [1].
“In the south east quadrant of the figure the new intervention is less costly
and more effective and (assuming there is no uncertainty surrounding the
cost effectiveness ratio) should be adopted; equally, if the new intervention
is less effective and more costly (the north west quadrant), it can readily be
rejected. More controversially, new interventions may turn out to be more
effective but also more costly (north east quadrant) or less effective but
also less costly (south west quadrant): in either case, a trade-off then exists
between effect and cost: additional health benefit can be obtained but at
higher cost, or costs can be saved but only by giving up health benefit” 1.
In this line, in D5.4 we now take a top level view and calculate the cost
difference per patient per year assuming standard treatment and assuming
INCA-Care pathway treatment.
Further, we look at the effectiveness difference when assuming standard
treatment and assuming INCA-Care pathway treatment. In this respect, it is
interesting to note that the introduction of a software platform like
INCA/ADSUM+ can help to streamline processes, make key performance
indicators easier accessible, help to take strategic/management decisions,
etc. ... However, one should not forget that a big part also depends on the
clinical decisions, i.e. the quality of the case management pathways
designed and brought to life with the help of INCA. Hence, we focus here on
two metrics that measure the combined effectiveness of INCA –software
plus the novel care pathway management implemented through INCA.
Before jumping right into INCA details, consider that health economics in
general uses different measures of evaluation, i.e.:
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Cost-minimisation analysis (CMA)
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Comparison of costs of alternatives that have the
same health outcome
Allows comparison within a clinical indication
Cost-effectiveness analysis (CEA)
Comparison of costs and disease-specific health
outcomes (e.g. fife-years saved, patients cured,
events avoided)
Allows comparison within a clinical indication
Cost-utility analysis (CUA)
Comparison of costs and generic health outcomes
(e.g. quality-adjusted life years)
Allows comparison across clinical indications
Cost-benefit analysis (CBA)
Comparison of costs and health outcomes valued in
monetary terms
(e.g. willingness to pay)
Allows comparison to other sectors of the economy
Figure 1-2: Definition and forms of economic evaluation. Source: Kobelt20133, Figure 1.4.
In INCA we have different pilots addressing different chronic diseases. To establish
comparability between the pilots, we directly discarded CMA and CEA. We further,
stayed clear of the controversial issue of putting a monetary value on a human
life/on human health and, hence, also discarded the CBA. Instead, we selected
“cost-utility analysis (CUA) to demonstrate the effectiveness of INCA
implementations in terms of generic health outcomes. Specifically, we selected the
generic metrics Patient Satisfaction and Quality of Life on the basis of the
EUROQOL5D thermometer patient self-assessment, which were collected and
presented in D4.4 in detail.
2 MANISES/QUART PILOT - COST UTILITY ANALYSIS
Before INCA, Manises hospital already saw the need to change its care
delivery model and when INCA came across with its software platform
ADSUM+ we saw it very appropriate. Besides, when checking out solutions
offered by competing providers, it turns out that INCA/ADSUM+ is very
competitive not only technologically, but also from a price point of view,
what confirms the suitability of the direction taken.
In the INCA pilot, Quart de Poblet Social Workers have joined the Manises
Hospital Multi-Disciplinary group to share a common integrated care
pathway when attending the needs of HF chronic patients from Quart de
Poblet, working in partnership with Manises Hospital.
It turned out that Manises/Quart are saving 98.166€ annually through the
introduction of INCA and the new care pathway models to their 273
patients. Broken down per patient this is an annual cost reduction of 360€.
3
G. Kobelt, Health Economics: An Introduction to Economic Evaluation, 3rd Ed,
Office of Health Economics, United Kingdom 2013.
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Further, the generic health outcomes achieved are displayed in Table 2—1.
Table 2—1: Generic health outcome indicators – Quart/Manises Pilot
Pilot
Manises/Quart:
Heart Failure
Utility metric
INCA Group
Control Group
delta Eff.
delta Cost in €
ICER in €
Patient Satisfaction (PS)
79
61
17
-360
-21
Quality of Life (QoL)
82
71
11
-360
-33
Note that for the sake of being able to plot all results in a common costeffectiveness plane, the “Patient satisfaction” metric, that in D4.4 was given
on a scale from 0 to 5 has been rescaled (i.e. multiplied by 20) to fit to a
scale from 0 to 100. Figure 2-1 plots the results in the cost-effectiveness
plane.
Figure 2-1: Quart/Manises results in cost-effectiveness plane.
It can be seen that the new treatment, in our case the INCA-Care Pathways
for chronic heart failure patients living in Quart and Manises, is more
effective and less costly, both seen in terms of Quality of Life (QoL) as well
as in terms of Patient Satisfaction (PS).
Further, the slope of the line from any point on the figure to the origin is the
incremental cost-effectiveness-ratio (ICER), defined as:
ICER = (difference_in_cost/difference_in_effect) = delat_Cost/delta_Eff
It is frequently the case that the ICER is positive, i.e. the new treatment is
more costly and also more effective, which leads to the difficult decision
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with respect to willingness to pay. However, with INCA we are in the
special situation that the ICER is negative, and we gain two things, a
reduction in cost paired with an increment in benefit, here the decision is
very easy, INCA should be implemented and rolled out as it is clearly the
“dominating treatment”.
Summarizing, it can be noted that the cost utility analysis for the
Quart/Manises pilot reveal that INCA is cost effective in the case of Heart
Failure. Considering that INCA can be rolled out over other pathologies
such as COPD, Stroke, Asthma, Diabetes..., the positive effects will scale,
bearing in mind that initial kick-off problems have already been overcome
through the HF pilot.
Due to this positive experience, the INCA service will continue after the EU
Project ends.
INCA, named Agenda ECA at Manises Hospital, is now a strategic
corporate service at the organization’s portfolio and a unique value
preposition in front of Valencia Region Health Ministry.
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3 MURCIA PILOT - COST UTILITY ANALYSIS
To demonstrate the impact of INCA, Diabetes and Heart Failure patients
have been chosen for running the pilot with the objective to improve their
care by:



Doing an appropriate stratification, establishing clinical pathways
agreed between all the stakeholders of the chain of care;
Reconstructing (if needed) the entire history of the patient, backed
by the INCA tool that allows visibility (clinical and social) according
to the permits granted to each role and
Monitoring performance and tracking patients evolution, with the
INCA tool
Considering the cost perspective, it turned out that Murcia
567224€ annually through the introduction of INCA and the
pathway models to their 4397 patients. Broken down per patient
annual cost reduction of 129€. Further, the generic health
achieved are displayed in Table 3.1
is saving
new care
this is an
outcomes
Table 3—1: Generic health outcome indicators – Murcia Pilots
Pilot
Utility metric
INCA Group
Control Group
delta Eff.
delta Cost in €
ICER in €
Murcia Region:
Heart Failure
Patient Satisfaction (PS)
77
62
15
-56
-4
Quality of Life (QoL)
80
72
8
-56
-7
Murcia Region:
Diabetes
Patient Satisfaction (PS)
77
61
15
-56
-4
Quality of Life (QoL)
82
71
11
-56
-5
Figure 3 - 1 plots the results in the cost-effectiveness plane.
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Figure 3-1: Murcia results on heart failure (HF) and diabetes (DI) in cost-effectiveness plane.
It can be seen that the new treatment, in our case the INCA-Care Pathways
for chronic heart failure (HF) and diabetes (DI) patients is more effective
and less costly, both seen in terms of Quality of Life (QoL) as well as in
terms of Patient Satisfaction (PS).
Similarly, to what we already observed in the case of Manises, the ICER is
negative.
All in all it can be concluded that the new treatments with INCA are
“dominant”, meaning, there is no reason for not selecting INCA including
the new chare pathways implemented with INCA over the control group’s
treatment as usual. As such the Murcia INCA Pilot is to be continued after
the EU INCA project ends with expenses fully carried by SMS-Murcia’s own
budget. Further, the new Regional Government shows great commitment
with service continuation and clearly sees INCA as strategic.
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4 CYPRUS PILOT - COST UTILITY ANALYSIS
Before INCA there were no pre-existent systems in the Geroskipou social
care centre. Thus all the medical data was paper based and data loss and
data duplication was a frequent problem. A doctor visited the social care
centre every week to examine and monitor the health condition of around
60-65 patients per visit (250 per month) and advised the social caregivers
of what physical exercise, medical treatment and special diet the patients
should follow.
INCA provides the opportunity for Geroskipou Municipality to use a digital
tool to monitor elder patients’ evolution suffering from cardio-vascular
diseases, while at the same time being more efficient and effective. Hence,
the expectations of Geroskipou Municipality were:

INCA will eliminate the information in the form of hard copies,
helping to convert all the patient data into electronic form.

The proposed development can increase the efficiency and the
responsiveness of the municipality resulting in time savings, generate
revenues and in the long run (in 5 years period) generate new full
time jobs.

INCA will help to increase digital literacy of all patients of the area
that until now have little or no ICT knowledge.
Summing INCA costs and savings over a 10 year amortisation period (i.e.
assuming that the scrap value of INCA after 10 years is 0 and a new
system has to bought) it turned out that INCA will delivery annual savings
of 42830€. Braking this down over the 200 patients, we obtain a cost saving
of 214€ per patient per year. Further, the generic health outcomes achieved
are displayed in Table 4—1.
Table 4—1: Generic health outcome indicators – Geroskipou/Cyprus Pilot
Pilot
Geroskipou:
CVD
Utility metric
INCA Group
Control Group
delta Eff.
delta Cost in €
ICER in €
Patient Satisfaction (PS)
78
66
12
-214
-18
Quality of Life (QoL)
78
69
9
-214
-24
Further, this data was plotted in the cost-effectiveness plane of
Note that for the sake of being able to plot all results in a common costeffectiveness plane, the “Patient satisfaction” metric, that in D4.4 was given
on a scale from 0 to 5 has been rescaled (i.e. multiplied by 20) to fit to a
scale from 0 to 100. Figure 2-1 plots the results in the cost-effectiveness
plane.
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Figure 4-1: Geroskipou/Cyprus results in cost-effectiveness plane.
It can be seen that the new treatment, in our case the INCA-Care Pathways
for chronic vascular diseases patients, is more effective and less costly,
both seen in terms of Quality of Life (QoL) as well as in terms of Patient
Satisfaction (PS). This is also reflected in the negative incremental costeffectiveness-ratios (ICERs).
It is concluded that, that the new treatment, i.e. INCA, is clearly
dominant and there is no reason for not adopting it. In fact, Geroskipou
plans to implement INCA as a core solution in the new medical centre
currently being build to serve the residents of the whole Paphos District. As
such, the sustainability of INCA is assured beyond the official INCA-EU
project.
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5 CROATIA PILOT - COST UTILITY ANALYSIS
In the City of Rijeka the proportion of the population over 60 years is
around 27%. With increasing age, the number of the population suffering
from mental health disorders will increase to over 50%. In such
circumstances, it was realised that the co-ordination of health and social
services would be beneficial. In any case, before the introduction of INCA,
coordination within Health Care (Primary, Secondary, Tertiary), as well as
between Social Care and Health Care was clearly insufficient.
Rijeka has used INCA’s Care Manager Interface to create one Care
Program: Health and Social Care for the patients/care users with Mental
Health diseases or other Mental Health disorders. The main goal was to
improve accessibility of Health and Social Services by using INCA for
coordination of the providers of Social and Health Services.
Neither Quality of Life (QoL) nor Patient Satisfaction (PS), nor costs were
measured in the case of Rijeka. However, initial pilot results indicate that
the implementation of socio-sanitary care pathways makes economic and
qualitative sense.
To demonstrate the effectiveness of INCA we cite the results from D4.4.
Table 5—1: Rijeka Pilot KPIs (source D4.4)
KPI*
Before INCA Pilot (October INCA Pilot M12 (December 2014) 2015) MHDs Mortality Rate 1,311
To be measured at M30 MHDs Admission Rate 1,84 admissions per pat/year
1,80 admissions per pat/year
MHDs Re‐Admission Rate 1 % of patients is re‐admitted
after 30 days 1% of patients is re‐admitted
MHDs Re‐Admission Rate 8% of patients is re‐admitted
after 6 months 7,6 % of patients is re‐
admitted MHDs Re‐Admission Rate 13 % of patients is re‐
after 1 year admitted 13,4 % of patients is re‐
admitted MHDs Stays (total days spent 29 average stay in days per 26 average stay in days per and average length) pat/year pat/year MHDs Visits to GP (PCP) 23,66 per pat/year
31,33 per pat/year MHDs Visits to Psychiatrists 11,11 per pat/year
12,13 per pat/year Health Visitors / Community 13,8 per pat/year
Nurses Visits to MHDs 15,4 per pat/year Patient’s Health Auto‐
assessment (EUROQOL‐5D) Not measured
Not measured Patient’s Satisfaction Not measured
Not measured Provider’s Satisfaction 3,20/5 – Average/Good 3.90/5 –Good Page 16 of 23
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It can be seen that the provider satisfaction increased from 3,2 as
measured before INCA to 3,9 measured with INCA. Further, it can be seen
that the number of number of hospital stays due to mental health disorder
(MHD) decreased by from 29 days per patient per year to 26
days/patient/per year, while patients more frequently visited their GP and
were also more frequently visited themselves by their community nurse.
Seen as a whole, INCA has been perceived as generally effective and
beneficial and has served the Croatian Health Insurance Fund to take
qualified decision in a foreseen public procurement process, which is
actively promoted by the Croatian Government that sees “Integrated Care”
as one of their focal points in for a sustainable society.
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6 VENTSPILS/LATVIA PILOT - COST UTILITY ANALYSIS
Since 2010, Latvia is running an e-Health program for more efficient use of
information and communication technology tools. This e-Health program
provides for cooperation in the exchange of data between national-level
database and business applications, but it does not provide a platform for
cooperation between patients, home care providers, family doctors and
specialists. This is where INCA comes in providing an integrated virtual
platform to engage both.
Although the effects in terms of Patient Satisfaction and Quality of Life have
been measured as indicated in Table 6—1, the cost/cost savings of INCA
have not been assessed.
Table 6—1: Generic health outcome indicators – Ventspils/Latvia Pilot
Pilot
Ventspils
Northern
Kurzeme:
Hypertension
Utility metric
INCA Group
Control Group
delta Eff.
delta Cost in €
ICER in €
Patient Satisfaction (PS)
84
70
14
not calculated
not calculated
Quality of Life (QoL)
82
64
18
not calculated
not calculated
In general, the way the health system is set up and financed Latvia,
hospitals are interested to provide the service for the patients in person.
More visits to the hospital mean more financial compensation for the
hospital, which is why INCA in its present form cannot provide savings.
Nevertheless, the Latvian pilot has measured high impact on patient
satisfaction (20% increase) and Patient Quality of Life (28% increase).
This positive outcome is the reason why Ventspils is committed to sustain
INCA beyond the official EU project. For this, the municipality will provide
its own recourses to fund work with the pilot patients. Further, the created
database will be integrated in the upcoming National eHealth system.
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7 CONCLUSIONS
We have analysed the cost-effectiveness of the software tool
INCA/ADSUM+ in conjunction with the care path ways that were
established with it. In the Manises/Quart-, the Murcia Region- and the
Geroskipou-pilot, INCA turned out as the clear Dominant Treatment when it
comes to Patient Satisfaction or the patients’ self-assessed Quality of Life.
Dominant treatment means that INCA is more effective and less costly than
the control group treatment.
For the Ventspils and the Rijeka pilot we did not have all data to plot results
in the cost-effectiveness plane. However, also in Ventspils INCA had
sufficient positive effects to be continued after the official EU project ends.
This makes it a total of 4 out of 5 pilots that will continue after EU funding
ends.
Further, the private partners of the INCA consortium have worked out a
memorandum of understanding (MoU) that lays out the foundation for a
joint commercial exploitation of INCA.
Economic evaluation of INCA can and will be used as a key sales argument
and, hence, the INCA consortium will continue the impact evaluation task.
As a very interesting building block in this respect we see the MAFEIP tool
provided by the European Innovation Partnership on Active and Healthy
Ageing (EIP-AHA), which is described in more detail in Annex I. In fact, we
already mapped some of the data collected in the pilots to the inputs of the
tool and will continue to fine-tune our INCA data collection and mapping to
be more aligned with the MAFEIP input parameters, to obtain further
interesting effectiveness and impact results and of cause INCA sales
arguments.
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8 ANNEX I
8.1
Introduction to EIP-AHA and MAFEIP
The European Innovation Partnership on Active and Healthy Ageing (EIPAHA), funded by the European Commission, is a partnership of over 500
institutional and industrial stakeholders, addressing the challenges brought
about by an aging population in Europe. The so called Triple Win objectives
with respect to the dimensions quality of life; sustainability of health and
care systems; and innovation and growth are detailed in Figure 8-14:
Figure 8-1: Triple Win dimensions in the EIP on AHA initial Monitoring
Framework, source [4].
The stakeholders - the INCA Consortium being one of them - are interested
in comparing EIP-AHA efforts among others in terms of cost-effectiveness,
which is the reason why the Monitoring and Assessment Framework for the
European Innovation Partnership on Active and Healthy Ageing (MAFEIP)
has been developed, with a more detailed description in the following.
4
C. Boehler and F. Abadie, Monitoring and Assessment Framework for the European Innovation
Partnership on Active and Healthy Aging (MAFEIP) Conceptual description of the Monitoring and
Assessment Framework for EIP on AHA. 2015 – 44pp, doi:10.2791/290381.
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MAFEIP Structure and Parameters
The Monitoring and Assessment Framework for the European Innovation
Partnership on Active and Healthy Ageing (MAFEIP) is making use of a web
based statistical simulation tool, accessible under http://mafeippre.jrc.es/overview/. However, log-in with a valid European Commission
Authentication Service (ECAS) ID is required. Related documents and a top
level description are accessible (even without ECAS ID) under
http://mafeip-pre.jrc.es/. For convenience, we repeat here the main aspects
that play a role in our use of the tool.
The statistical simulation tool implements a Markov-model with states and
transition probabilities displayed in Figure 8-2.
Figure 8-2: States and transition probabilities of the MAFEIP
Markov-Model, source [http://mafeip-pre.jrc.es/].
As can be seen in Figure 8-2, a trial participant can be in three different
states, referred to as “Baseline health”, “Deteriorated health” and “Dead”.
Each state is associate with a metric called Health Related Quality of Life
(HRQoL), and a second metric called resource use (cost).
Further, the numbers in Figure 8-2 represent the transition probabilities
between of either remaining in one state or transiting to another state.
This, paired with life expectancy data, which the tool is able to directly
obtain from the Human Mortality Database5 per country and gender,
enables to calculate a.) the overall average HRQoL (Effectiveness, E), as
well as the overall Resource Use (Costs, C).
5
Web link to The Human Mortality Database (HMD), http://www.mortality.org/
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The tool is comparative, meaning that it needs a treatment group, for which
we will use the sub-index t, and a control group with standard treatment,
for which we will use sub-index c. Running the tool for both groups allows to
decide which treatment is more cost-effective.
8.3
Matching INCA Results to MAFEIP Input Parameters
In the attempt to use the tool several obstacles occurred that require
significant more and more specific trial data than we collected with the
INCA pilots. For example, one of the parameters needed are the transition
probabilities between states.
Figure 8-3: Screen shot of the MAFEIP input window on state transition probabilities.
Figure 8-4: Screen shot of the MAFEIP input window on state utilities HRQoL.
Forcing our chronic patients into two states is already problematic, as in
many cases after an incident they never fully recover. E.g. their health
related quality of life (HRQoL) is deteriorating on a downhill line over time
with ditches when they get admitted to the hospital and more stable/higher
HRQoL when they are at home.
Besides the two state restriction, none of the INCA pilots gathered
transition statistics between the two states, and finally, we assess health
related quality of life usually not during a crisis situation, i.e. while a chronic
patient receives emergency treatment in a hospital equivalent to the
deteriorated state but usually only during the baseline health state.
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Another obstacle is that we did not have full access to the mortality
statistics of our trial groups that are significantly much higher (e.g. 10 time
higher) than the probabilities of a non-chronic patient with the same age.
This means that the MAFEIP tool that predicts social impact till the life end,
is assuming that our patients life much longer than they actually (and
unfortunately) do.
To obtain the above parameters in the retro-perspective is pure guess work.
We nevertheless, did some experiments to familiarize ourselves with the
MAFEIP tool and its capacity to generate outputs and an example costeffectiveness plane screenshot generate with the tool is presented in Figure
8-5.
Figure 8-5: Screen shot of the MAFEIP cost-effectiveness plane.
From our experiments it can be concluded that the MAFEIP tool is very
powerful to analyse cost effectiveness and socio economic impact,
particularly as in as second step it allows to perform sensitivity analysis.
However, pilot design and data collection has to be carefully tailored to
obtain the input parameters to feed the model.
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