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Integrated Information Means...

Integrating Clinical Systems by Integrating Controlled Vocabularies James J. Cimino, MD Center for Medical Informatics Columbia University New York, New York, USA. Integrated Information Means. ...collecting patient information ...links to financial systems ...automated decision support

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Integrated Information Means...

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  1. Integrating Clinical Systemsby Integrating Controlled VocabulariesJames J. Cimino, MDCenter for Medical InformaticsColumbia UniversityNew York, New York, USA

  2. Integrated Information Means... • ...collecting patient information • ...links to financial systems • ...automated decision support • ...library at the bedside

  3. The Columbia Computing Environment • Stand-alone clinical systems • Several billing systems • Clinical alert system • Local- and wide-area networks • On-line educational resources

  4. Federation of Systems

  5. Central Patient Database

  6. Central Controlled Vocabulary

  7. Advantages of Central Vocabulary • Resource for system developers • Single update point • Brings vocabularies together

  8. Issues • Understand the vocabulary • Integrate the terms • Maintenance

  9. Central Vocabulary Design • Semantic network of concepts • Content from: • Unified Medical Language System (UMLS) • Ancillary systems • Standard controlled vocabularies • Browsing and editing tools

  10. Medical Entity Laboratory Specimen Substance Event Anatomic Substance Plasma Specimen Diagnostic Procedure Chemical Substance Sampled Carbo- hydrate Bioactive Substance Laboratory Procedure Laboratory Test Plasma Has Specimen Plasma Glucose CHEM-7 Glucose Substance Measured Part of Medical Entities Dictionary

  11. Vocabulary Sources • Clinical laboratories • Pharmacy • Cardiology • Discharge coding • Radiology • Primary Care

  12. Current Size • 41,000 concepts • 146 slots • 51,500 parent/child links • 40,000 other semantic links • 240,000 strings

  13. Vocabulary Browser/Editors • Knowledge Engineering Environment (KEE) - 386 and 370 • PC-MUMPS • RS/6000 and X-Windows

  14. Editor Functions • Lexical and graphic browsing • Addition and deletion functions • Inheritance • Automatic classification

  15. mumps editor - take a photo!!!

  16. X-browser - get a stock photo!!!

  17. Success Stories • Repairing vocabularies • Database extension • Confidential data display • Summary reporting • Medline Button • Medical Logic Modules

  18. Repairing Vocabularies • Radiology • Laboratory • Pharmacy

  19. Laboratory Test Plasma Glucose SMAC20 Glucose Chem-7 Glucose Fasting Glucose Stat Serum Glucose Laboratory Test Glucose Test Serum Glucose Blood Glucose Serum Glucose Fasting Glucose Chem-7 Glucose Plasma Glucose SMAC20 Glucose Stat Serum Glucose Autoclassifying the Laboratory

  20. Autoclassify the Pharmacy: Before Drug Allergy Salicylate Allergy Opiate Allergy Nonsteroidal Anti-inflamm. Analgesic Bayer Aspirin Empirin #3

  21. Autoclassify the Pharmacy: After Drug Allergy Salicylate Allergy Opiate Allergy Nonsteroidal Anti-inflamm. Analgesic Aspirin Drugs Codeine Drugs Bayer Aspirin Empirin #3

  22. Results of Autoclassification • 971 new classes • 334 drugs classified by type • 289 drugs into two or more types • 173 drugs into allergy classes

  23. Database Extension • Information model for new applications • Merging the new with the old • Adding organization to the model

  24. Summary reporting - stock photo!!!!

  25. Confidential Data Display • Need to display sensitive data (HIV) • Need an extra level of security • Step 1: create a new class in the MED • Step 2: have the application check for class membership

  26. Medline Button - stock photo 1 !!!

  27. Medline Button - stock photo 2 !!!

  28. Medline Button - stock photo 3 !!!

  29. Medline Button - stock photo 4 !!!

  30. Medline Button - stock photo 5 !!!

  31. MLM Alert - stock photo 1 !!!

  32. MLM Alert - stock photo 2 !!!

  33. Medical Logic Modules • Clinical alerts • Data interpretation • Finding research patients • Monitoring hospital resources

  34. Current Challenges • Editing environment • Expansion of automated updates • Vocabulary content

  35. Conclusions • Integrating vocabularies helps • Complex vocabulary model pays off • Automated maintenance works

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