Faculty of Computer Science
Concept-Based Electronic Health Records:
Opportunities and Challenges
S. Ebadollahi, S Chang, T. Mahmood, A Coden,
A. Amir M. Tanenblatt
14th Annual ACM International Conference on Multimedia (2006)
Amit Satsangi
[email protected]
CMPUT 605
March 3, 2008
© 2006
Department of Computing Science
Focus
 ECG Video: document is not important; behavior of
sub-organs like valves, ventricles, myocardium is
 ECG –Text Report  sub organs, diagnosis
 Efficient access to the elements of the content of
the data ???
 New Paradigm – Concept based Multimedia Medical
Records
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Department of Computing Science
Problems with the present system
 Electronic Health Records (EHR)
Data—mixed format: HIS for lab reports, ECG’s etc.
RIS for reports generated after reviewing medical
images, and PACS for diagnostic images.
 Different Standards: HL7, DICOM, etc.
 Information extraction regarding a single concept
of interest (Right Atrium) is difficult
 Hence the need for (re)organizing the health
records at the information level
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Department of Computing Science
Concept-Based Records Organization: Advantages
 Goes beyond dealing with data at the document level
 Caters to different categories of users of medical records
– Physicians: Ejection fraction of left ventricle measured while reviewing
the ECG. Ideally system should calculate this using quantification
Algorithms. Should also be able to link it with the diagnosis reports,
textbooks, research papers etc.
– Students: Teaching files with history of medical cases + diagnostic
images + medical journals + textbooks
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Department of Computing Science
Concept-Based Records Organization: Advantages
– Patients: Illustrated version of patient’s disease
– Insurance companies: Prevent misuse of expensive tests (MRI) when not
justified by the results of earlier, less expensive tests (EKG)
 Timely and decision-enabling information extraction
 It entails a better organization of medical records from the
scratch in order to deliver all that is promised …
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Department of Computing Science
Architecture
 Analytic Engines
—domain knowledge
 Heart Chambers in Video
 Parse diagnosis report
 Relationships b’n concepts
—ontologies (UMLS)
 Is a, spatially/temporally/
functionally related to etc.
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Department of Computing Science
Example
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Department of Computing Science
Addendum
 New information may need to be added
 Graph Structure with Nodes as concepts and links are
relationships between these concepts
 Need federation of Ontologies – different concepts of interest
in different domains
 Multimedia content restructuring required – Vision, NLP etc.
 Not a new way of analyzing data, but a novel way of
organizing the medical records
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Department of Computing Science
Case Study: Video Content Restructuring
 Echocardiography – Imaging of the heart in several planes
 Inherent spatio-temporal strcuture
 Feature-extraction tools used to target areas of interest
 Text snippets extracted from diagnosis report
 Undirected graphical models used to learn the spatial
arrangement of cardiac chambers
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Department of Computing Science
Schematic
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Department of Computing Science
Text Analytics for Cancer Pathology Reports
 MedTAS (Medical Text Analysis System) was used
 Several models – conceptually separate pieces of
knowledge
 Pieces of knowledge  Disease description,
evaluation procedures etc.
 4 sub-models: Tumor model, Specimen model,
Lymph-node model and the disease model
CMPUT 605
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Department of Computing Science
Text Analytics for Cancer Pathology Reports
 Models are annotators (can be institution specific)
 MedTAS built on IBMs Ustructured Information
Management Architecture (UIMA) . (Open Source)
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Department of Computing Science
Models
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Department of Computing Science
Potential Avenues
 Three main issues
— Determining the unifying architecture
— Determining the concepts that need to be extracted
— Development of robust Analytic engines
 Testing & Feedback issues when such records in
use
 Seamless Integration with existing data
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© 2006
Department of Computing Science
Thank You For Your Attention!
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© 2006