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From Biomedical Literature to
Electronic Health Record
Health Grid for Research and Clinical Decisions
Graduate Institute of
Medical Informatics
Taipei Medical University, Taipei, Taiwan
Yu-Chuan (Jack) Li, M.D., Ph.D.
Arbiter Lin, M.D., M.S.
Biomedical Data for Research and
Clinical use

Scale, complexity and timeliness

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
Massive data and heavy computation
Data ownership problem
Privacy problem
Competition and collaboration
among hospitals and research
institutes
Grid may be ideal here!
Taipei Medical University
Graduate Institute of Medical
Informatics
Range of Applications
Genome
Transcriptome
Proteome
Literature text
mining
+ Microarray
data mining
Metablome
Disease
Treatment
Taipei Medical University
Graduate Institute of Medical
Informatics
Literature text
mining
+ NHI data
mining
+ EHR data
mining
Scale and Complexity




Human Genome: 18,000 defined in
Gene Ontology, total 25,000?
Human Proteome: not well defined,
total 50,000~75,000?
Disease: 11,000 defined in ICD-9CM
Treatment: 20,000 defined in NHI’s
(National Health Insurance) medication +
procedures
Taipei Medical University
Graduate Institute of Medical
Informatics
National Health Insurance



Bureau of Nation Health Insurance
National Health Insurance for all people
in Taiwan since 1995
NHI Smart Card issued to all 23 million
people in Taiwan since 2004.01
Taipei Medical University
Graduate Institute of Medical
Informatics
NHI Smart Card
Taipei Medical University
Graduate Institute of Medical
Informatics
Scale and Complexity (cont.)



National Health Insurance DB:
5TB@500GB/yr
600 hospitals and 17,000 clinics
connected in real-time to the NHI
for the health smart card
authentication
But the bandwidth is mostly
512KB/64KB in ADSL
Taipei Medical University
Graduate Institute of Medical
Informatics
Size of Medical Data in Taiwan






Outpatient : 300 million visits / yr
Inpatient : 2.8 million-days / yr
1.5 billion prescription / yr
~ 900TB image data per year
~ 30TB text/coded data per year
Growing exponentially in the next 5 years
while Electronic Health Record (EHR)
matures
Taipei Medical University
Graduate Institute of Medical
Informatics
Standardized EHR Project
Taipei Medical University
Graduate Institute of Medical
Informatics
MIEC Project

National Medical Information
Exchange Center




prototype in 1997
Hospitals treat health and medical
data as their own property
Not willing to share with other
hospitals
Concern about privacy, legal and
business issues
Taipei Medical University
Graduate Institute of Medical
Informatics
To Share, or Not to Share


Medical data are sensitive and
“proprietary”
De-identification is not enough

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Practice patterns, medication consumption
patterns, outcome variations, case-mix
index…etc. are still sensitive information
Share only the results of aggregated
computation, not individual hospital
Privacy enhancing technologies
Multiparty private computation
Taipei Medical University
Graduate Institute of Medical
Informatics
Scenario: Carpal Tunnel Syndrome

A physician of rehabilitation may
want to know:


Percentage of different treatment on
CTS in whole Taiwan:
 Surgical Operation
 Rehabilitation
 Acupuncture
Outcome of each treatment options
for a patient with specific age/sex
Taipei Medical University
Graduate Institute of Medical
Informatics
Scenario: A 58 year-old female


Lab Data: cholesterol 480mg/dl
A doctor may want to know:




Treatment options at these age/sex/lab
Medication usage… etc.
Outcome of each treatment options in
Taiwan
The percentage of people who
eventually get Coronary Artery Disease
Taipei Medical University
Graduate Institute of Medical
Informatics
A Health Grid Can Work

For physicians


For patients

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Weighing treatment options for
individual patient
Know our options and risks
For health policy maker

Public health policy making
Taipei Medical University
Graduate Institute of Medical
Informatics
Networking Environment
Giga
台北醫學大學
附設醫院
100M
台北醫學大學
台灣大學
Giga
10M
Taipei Medical University
Graduate Institute of Medical
Informatics
Biomedical Literature Mining for
Gene and Disease Relationship
Range of Applications
Genome
Transcriptome
Proteome
Literature text
mining
+ Microarray
data mining
Metablome
Disease
Treatment
Taipei Medical University
Graduate Institute of Medical
Informatics
Literature text
mining
+ NHI data
mining
+ EHR data
mining
Probabilistic Relationship Among
Genes and MeSH terms
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Medical Literature: 13 million
citations collected in Medline
Medical Terms: 341,000 defined in
MeSH (Medical Subject Headings)
18,000 gene names
Taipei Medical University
Graduate Institute of Medical
Informatics
MeSH term: Breast Neoplasms
Complex Joint Probability Computation
Taipei Medical University
Graduate Institute of Medical
Informatics
Future Applications

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
Text mining on literature and freetext data from EHR
Data mining on coded/numerical
data from EHR or NHI DB or
Gene/Protein chips
Support medical decision making
and public health policy making
Taipei Medical University
Graduate Institute of Medical
Informatics
Conclusion




Use Grid technology to collaborate
hospitals and academic institutes
Build a testbed and demo site of a
Health Grid in Taiwan
Increase international
collaboration – working with EGEE
EU project - Supporting and
structuring HealthGrid Activities &
Research in Europe (SHARE)
Taipei Medical University
Graduate Institute of Medical
Informatics
Q&A
Welcome to ISGC 2004 in Taiwan!
Thanks you!
Taipei Medical University
Graduate Institute of Medical
Informatics