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

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Presentation on theme: "James J. Cimino Columbia University MIE ‘02 Budapest, Hungary August 27, 2002 The Challenge of Reuse of Information."— Presentation transcript:

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

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 Text Numeric SignalStructuredCodedStandard Coded NLP Interpretation Image Blobs Symbols

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

6 Information Reuse InformationResearchOther Clinicians Summary Hospital Administration Government Decision Support

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 21 22 23 24 25 26 27 28 29 76543217654321

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

12 Information Mismatch: Language “Tüdőgyulladás” Pneumonia?

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

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

15 Information Mismatch: Version Patient has hantavirus infection “Virus, NEC” 2001 ICD: - Smallpox - Cowpox - Virus, NEC 2002 ICD: - Smallpox - Cowpox - Hantavirus - 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 Goodpasture’s Syndrome Kidney Disease Hemoptysis Hematuria Finding Lung Kidney Organ has-site Lung Disease is-a has-finding

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 is-a Bacterial Pneumonia Tularemia Pulmonary Tularemia has-causative-agent Francisella tularensis Lung Structure has-finding-site Inflammation associated- morphology

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 24356-8 | URINALYSIS PANEL 5778-6 | COLOR | COLOR | PT | UR | NOM 22705-8 | GLUCOSE | SCNC | PT | UR | QN | TEST STRIP Yellow Red Colorless …

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

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

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

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

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 Plasma Glucose Test Serum Glucose TestFingerstick Glucose TestLab Test Intravascular Glucose TestChem20 Display Lab Display

36 Example of Reuse: Summary Reporting

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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 45748 - Diazepam 5 mg Tablet 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 46888 - Diazepam Tablets 31136 - Diazepam Preparations 24015 - Benzodiazepine Preparations 28107 - Drug Enforcement Administration (DEA) Class IV - Drug with Low Abuse Potential 28129 - Drug Allergy Class: Benzodiazepines 28203 - Tablet

40 Example of Reuse: Merging Data 2478 - Plasma Glucose Measurement 32308 - Intravascular Glucose Test 32101 - Plasma Chemistry Test 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) 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

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 No Growth Medical Logic Module No Growth to Date

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

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

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

51 Example of Reuse: Expert Systems 1600 44 L 1600 Gluc32703 Serum Glucose Tests 32308 Intravascular Glucose Tests 42485 Elevated Abnormal Finding in Body Substance 42486 Decreased Abnormal Finding in Body Substance 42541 Hyperglycemia 3286 Hypoglycemia 32412 Intravascular Specimen 31987 Glucose 42527 Abnormal Level of Blood Glucose 3286 Hypoglycemia

52 Expert System: DXplain

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55 Expert System: Lipid Guideline

56 Lab :1/1/99 Cardiac Enzyme Test Radiology :2/23/99 Chest X Ray Radiology :2/28/96 Head CT Lab :12/28/96 Sickle Cell Test Admission :3/14/96 Stroke Admission :2/14/98 Angina Lab :1/1/99 Blood Type Test Radiology :2/1/97 Knee X Ray Discharge :1/15/99 CHF Medical Record Example of Reuse: Problem-Oriented Views Chest X ray Intravascular CK Test Creatine Kinase Chest X ray 2 View Cardiac Enzyme Congestive Heart Failure Angina Heart Disease Chest Admission :2/14/98 Angina Lab :1/1/99 Cardiac Enzyme Test Radiology :2/23/99 Chest X Ray Discharge :1/15/99 CHF Heart MED

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61 Experience with Information Reuse Summary reporting Merging data Automated decision support Information retrieval Expert systems Problem-oriented views

62 Overview Data types Information reuse Information mismatch Terminology solutions Experience Conclusions

63 Information, Then and Now - Cimino JJ, Int J Biomed Comput. 1994; 34:185-194 Discharge Diagnoses Radiology Reports Physical Exams Discharge Summaries Patient Histories Medication Lists Uncoded, Unstructured Uncoded, Structured Locally Coded Universally Coded Then (1993)

64 Information, Then and Now - Cimino JJ, Int J Biomed Comput. 1994; 34:185-194 Discharge Diagnoses Radiology Reports Physical Exams Discharge Summaries Patient Histories Medication Lists Uncoded, Unstructured Uncoded, Structured Locally Coded Universally Coded Near Future

65 Information, Then and Now - Cimino JJ, Int J Biomed Comput. 1994; 34:185-194 Discharge Diagnoses Radiology Reports Physical Exams Discharge Summaries Patient Histories Medication Lists Uncoded, Unstructured Uncoded, Structured Locally Coded Universally Coded Far Future

66 Current Status Discharge Diagnoses Radiology Reports Physical Exams Discharge Summaries Patient Histories Medication Lists Uncoded, Unstructured Uncoded, Structured Locally Coded Universally Coded

67 Current Status Uncoded, Structured Standard Semantic Terminology Standard Code Set Discharge Diagnoses Radiology Reports Physical Exams Discharge Summaries Patient Histories Medication Lists Uncoded, Unstructured

68 Current Status Discharge Diagnoses Laboratory Reports Problem Lists Text Reports Text Reports Medication Lists Uncoded, Unstructured Uncoded, Structured Standard Semantic Terminology Standard Code Set

69 Conclusions Advanced health care means information reuse Semantic-based terminologies support reuse Terminologies are moving in the right direction


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