1 / 69

The Challenge of Reuse of Information

The Challenge of Reuse of Information. James J. Cimino Columbia University MIE ‘02 Budapest, Hungary August 27, 2002. Overview. Data types Information reuse Information mismatch Terminology solutions Experience Conclusions. Overview. Data types Information reuse

amity-salinas
Download Presentation

The Challenge of Reuse of Information

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Challenge of Reuse of Information James J. Cimino Columbia University MIE ‘02 Budapest, Hungary August 27, 2002

  2. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  3. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  4. Data Types Standard Coded Numeric Coded NLP Symbols Text Structured Interpretation Image Signal Blobs

  5. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  6. Information Reuse Decision Support Summary Other Clinicians Information Research Hospital Administration Government

  7. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  8. Information Mismatch • Form • Meaning • Language • Granularity • Semantics • Version

  9. Information Mismatch: Form

  10. Information Mismatch: Form 7 6 5 4 3 2 1 21 22 23 24 25 26 27 28 29

  11. Information Mismatch: Meaning Paget’s Disease of the Breast?!?! “Paget’s Disease” “of the bone”

  12. Information Mismatch: Language Pneumonia? “Tüdőgyulladás”

  13. Information Mismatch: Granularity Does the patient have lung disease? “Goodpasture’s Syndrome”

  14. Information Mismatch: Semantics Should I prescribe “Ampicillin 250mg Caps”? AMP Sens. Test = 1:2

  15. Information Mismatch: Version 2002 ICD: - Smallpox - Cowpox - Hantavirus - Virus, NEC Patient has hantavirus infection 2001 ICD: - Smallpox - Cowpox - Virus, NEC “Virus, NEC”

  16. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  17. Terminology Solutions • Standards • Distribution • Semantic Representation

  18. Terminology Solutions: Standards • Advantages • Less duplication of work • “Plug and play” compatibility • Disadvantages • Cost of adoption • Unresponsive to change • Developers  Users

  19. Terminology Solutions: Distribution • Media • 9-track tape • Floppy disks • CD-ROM • Web • Models • ICD: annual • UMLS: change files • HL7: server

  20. Terminology Solutions: Semantic Representation • Concept oriented • Concept permanence • True is-a hierarchies • Multiple hierarchies (heterarchy) • Semantic relationships • Inheritance

  21. Terminology Solutions: Semantic Representation Lung Disease Kidney Disease is-a has-site Finding Organ Hematuria Hemoptysis has-finding Kidney Lung Goodpasture’s Syndrome

  22. Semantic Representation: Galen • Structured Meta Knowledge from Pen&Pad • Common Reference Terminology • Requires terminology server • Automated classification • Open source terminology

  23. Semantic Representation: Galen Fracture which < hasLocation Bone hasCause Condition> Fracture which < hasLocation (AnatomicalNeck which isDivisionOf Femur) hasCause (Osteoporosis which hasCause PostMenopausalChange)> Can be classified as: Fracture Fracture which hasLocation LongBone. Fracture which hasLocation (AnatomicalNeck which isDivisionOf LongBone). Fracture which hasLocation Thigh. Fracture which hasLocation Hip. Lesion which isCausedBy Osteoporosis. Lesion which isCausedBy PostmenopausalChange.

  24. Semantic Representation:SNOMED-CT • Merger of SNOMED and Read Clinical Terms • Reference terminology • Many domains • Heterarchy • Semantic relations (roles) • Postcoordination • >300,000 concepts

  25. Semantic Representation:SNOMED-CT Bacterial Pneumonia Tularemia is-a has-causative-agent has-finding-site associated- morphology Francisella tularensis Lung Structure Inflammation Pulmonary Tularemia

  26. Semantic Representation: LOINC • Logical Observations, Identifiers, Names and Codes • Codes for observations in HL7 messages • Fully-specified names • Codes for orderable observations • Codes for results

  27. Semantic Representation: LOINC 22705-8 | GLUCOSE | SCNC | PT | UR | QN | TEST STRIP 5778-6 | COLOR | COLOR | PT | UR | NOM Yellow Red Colorless … 24356-8 | URINALYSIS PANEL

  28. Semantic Representation: Drugs • Food and Drug Administration • Veterans Administration • National Library of Medicine • Drug knowledge base vendors • Common model for Clinical Drug • RxNorm

  29. Semantic Representation: Drugs Medications Packages Drug Class International Package Identifiers Chemicals is-a Not-Fully-Specified Drug is-a Ingredient Class is-a Country-Specific Packaged Product is-a is-a is-a Ingredient Composite Clinical Drug Trademark Drug is-a is-a Manufactured Components Composite Trademark Drug Clinical Drug

  30. Semantic Representation: MED • Medical Entities Dictionary • Data dictionary and controlled terminology • Columbia-Presbyterian Medical Center • Heterarchy • Semantic network • Multiple domains • >70,000 concepts

  31. Semantic Representation: MED Medical Entity Substance Laboratory Specimen Event Plasma Specimen Chemical Anatomic Substance Diagnostic Procedure Substance Sampled Plasma Laboratory Test Laboratory Procedure Has Specimen Carbo- hydrate Bioactive Substance CHEM-7 Part of Glucose Substance Measured Plasma Glucose Test

  32. Overview • Data types • Information reuse • Information mismatch • Terminology solutions • Experience • Conclusions

  33. Matching Granularity and Semantics Intravascular Gentamicin Tests Summary Reports is-a Has ingredient Substance Measured Decision Rule Measures Sensitivity Etiology Drug Information Expert System Injectable Gentamicin Serum Gentamicin Level Gentamicin Gentamicin Sensitivity Test Gentamicin Toxicity

  34. Example of Reuse:Summary Reporting • Spreadsheets for trends in lab data • Defined as concepts in the MED • Linked to test classes

  35. Example of Reuse:Summary Reporting Lab Display Lab Test Chem20 Display Intravascular Glucose Test Fingerstick Glucose Test Serum Glucose Test Plasma Glucose Test

  36. Example of Reuse:Summary Reporting

  37. Example of Reuse:Summary Reporting

  38. Example of Reuse: Merging Data • Merger between Presbyterian Hospital and New York Hospital • Separate departmental systems • Common repository • Merger of terms in MED allows cross-institution data aggregation

  39. Example of Reuse: Merging Data 24015 - Benzodiazepine Preparations 28107 - Drug Enforcement Administration (DEA) Class IV - Drug with Low Abuse Potential 28129 - Drug Allergy Class: Benzodiazepines 28203 - Tablet 31136 - Diazepam Preparations 46888 - Diazepam Tablets 28727 - CPMC Drug: Diazepam 5 mg Tab 29952 - CPMC Drug: UD Diazepam 5 mg Tab 34734 - CPMC Drug: UD Diazepam 5mg Tab 35346 - CPMC Drug: UD Diazepam 5 mg Tab. 62523 - Cerner Drug: Diazepam Tab 5 mg 45748 - Diazepam 5 mg Tablet

  40. Example of Reuse: Merging Data 32308 - Intravascular Glucose Test 32101 - Plasma Chemistry Test 1523 - Presbyterian Plasma Glucose Test 1601 - Presbyterian Plasma Glucose Measurement 1652 - Allen Plasma Glucose Measurement 33807 - New CHEM-7 Plasma Glucose Measurement 35454 - CPMC Laboratory Test: Old Plasma Glucose Measurement 35815 - CPMC Laboratory Test: Glucose, Challenge 35816 - CPMC Laboratory Test: Glucose, Fasting 35817 - CPMC Laboratory Test: Glucose, 1hr Post Prandial 35818 - CPMC Laboratory Test: Glucose, 2hr Post Prandial 35819 - CPMC Laboratory Test: Glucose, Random 35821 - CPMC Laboratory Test: Glucose 35831 - CPMC Laboratory Test: Glucose Tolerance, 1hr 35832 - CPMC Laboratory Test: Glucose Tolerance, 2hr 35833 - CPMC Laboratory Test: Glucose Tolerance, 3hr 35834 - CPMC Laboratory Test: Glucose Tolerance, 4hr 35835 - CPMC Laboratory Test: Glucose Tolerance, 5hr 35836 - CPMC Laboratory Test: Glucose Tolerance, 6hr 35836 - CPMC Laboratory Test: Glucose Tolerance, 6hr 35837 - CPMC Laboratory Test: Glucose Tolerance, Fasting 35838 - CPMC Laboratory Test: Glucose, 1/2 Hour 36337 - CPMC Laboratory Test: Glucose, Fasting 2 50005 - NYH Lab Procedure: Glucose, Plasma 50078 - NYH Lab Procedure: Glucose, 0 H 50079 - NYH Lab Procedure: Glucose, 2 PP 50080 - NYH Lab Procedure: Glucose, 0.5 H 50081 - NYH Lab Procedure: Glucose, 1 H 50082 - NYH Lab Procedure: Glucose, 2 H 50084 - NYH Lab Procedure: Glucose, 3 H 50107 - NYH Lab Procedure: Glucose, 1.5 H 50108 - NYH Lab Procedure: Glucose, 4 H 50109 - NYH Lab Procedure: Glucose, 5 H 50110 - NYH Lab Procedure: Glucose, 6 H 50111 - NYH Lab Procedure: Ogtt,Gest Screen,(50g) 2478 - Plasma Glucose Measurement

  41. Example of Reuse:Automated Decision Support • Data stored in repository reviewed in real time • Arden Syntax rules triggered by data • Generation of alerts and reminders • High-level concepts in rules map to low-level concepts in database

  42. Automated Decision Support: Tuberculosis • Monitors for delayed culture results • Sends message if result not equal to the code “No growth” • One day, dozens of alerts about positive results but no organism was reported • What happened?

  43. How the Lab Fooled the Alert • Alert looked for results = “No Growth” • Lab started reporting “No Growth to Date” • “No Growth to Date” “No Growth” • Solution: Use the controlled terminology to map all No-Growth-like lab terms into a single class, and have the alert logic refer to the class.

  44. Automated Decision Support: Tuberculosis Medical Logic Module No Growth to Date No Growth

  45. How We Outsmarted the Lab “No Growth” Results No Growth after 24 Hours No Growth after 48 Hours No Growth after ... No Growth after 72 Hours Medical Logic Module No Growth to Date No Growth

  46. Example of Reuse:Information Retrieval 4 5 2 Automated Translation Get Information From EMR Resource Terminology 6 1 Querying Understand Information Needs 3 7 Resource Selection Presentation

  47. Example of Reuse: Expert Systems • Expert system has high-level concepts • Database has quantitative results • Semantic mismatch • Translation through semantic net traversal

More Related