Graduate Institute of Medical Informatics Taipei Medical University, Taipei, Taiwan

1. From Biomedical Literature to Electronic Health RecordHealth 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.

2. Biomedical Data for Research and Clinical use • Scale, complexity and timeliness • Massive data and heavy computation • Data ownership problem • Privacy problem • Competition and collaboration among hospitals and research institutes • Grid may be ideal here! Graduate Institute of Medical Informatics

3. Range of Applications Genome Literature text mining + Microarray data mining Transcriptome Proteome Metablome Disease Literature text mining + NHI data mining + EHR data mining Treatment Graduate Institute of Medical Informatics

4. 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-9-CM • Treatment: 20,000 defined in NHI’s (National Health Insurance) medication + procedures Graduate Institute of Medical Informatics

5. 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 Graduate Institute of Medical Informatics

6. NHI Smart Card Graduate Institute of Medical Informatics

7. 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 Graduate Institute of Medical Informatics

8. 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 yearswhileElectronic HealthRecord (EHR) matures Graduate Institute of Medical Informatics

9. Standardized EHR Project Graduate Institute of Medical Informatics

10. 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 Graduate Institute of Medical Informatics

11. To Share, or Not to Share • Medical data are sensitive and “proprietary” • De-identification is not enough • 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 Graduate Institute of Medical Informatics

12. 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 Graduate Institute of Medical Informatics

13. 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 Graduate Institute of Medical Informatics

14. A HealthGrid Can Work • For physicians • Weighing treatment options for individual patient • For patients • Know our options and risks • For health policy maker • Public health policy making Graduate Institute of Medical Informatics

15. Networking Environment Graduate Institute of Medical Informatics

16. Biomedical Literature Mining for Gene and Disease Relationship

17. Range of Applications Genome Literature text mining + Microarray data mining Transcriptome Proteome Metablome Disease Literature text mining + NHI data mining + EHR data mining Treatment Graduate Institute of Medical Informatics

18. Probabilistic Relationship Among Genes and MeSH terms • Medical Literature: 13 million citations collected in Medline • Medical Terms: 341,000 defined in MeSH (Medical Subject Headings) • 18,000 gene names Graduate Institute of Medical Informatics

19. MeSH term: Breast Neoplasms

21. Complex Joint Probability Computation Graduate Institute of Medical Informatics

22. Future Applications • Text mining on literature and free-text 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 Graduate Institute of Medical Informatics

23. Conclusion • Use Grid technology to collaborate hospitals and academic institutes • Build a testbed and demo site of a HealthGrid in Taiwan • Increase international collaboration– working with EGEE • EU project - Supporting and structuring HealthGrid Activities & Research in Europe (SHARE) Graduate Institute of Medical Informatics

24. Welcome to ISGC 2004 in Taiwan! Q & A Thanks you! Graduate Institute of Medical Informatics