Controlled Terminologies in Patient Care and Research: An Informatics Perspective James J. Cimino, M.D. Department of Biomedical Informatics Columbia University

Overview Motivation for data encoding: reuse Challenges to encoding with controlled terminologies Approach at Columbia/NY Presbyterian Hospital Desiderata for controlled terminologies Successful data reuse at Columbia/NYPH

Problems We Are Trying to Solve Collecting data from disparate sources Aggregating like data Sharing data Reusing data –Patient care –Administrative functions –Research –Automated decision support

Information Form and Reuse

Information Form and Reuse

Patient Care Data Research Data ? Finds what is mentioned but not what is discussed (ambiguity, redundancy, false positives, false negatives) Text Processing Text Images

Patient Care Data Research Data Text Images Natural Language Processing Feature Extraction Controlled terminology; distinguishes what is discussed from what is mentioned (concept oriented)

Patient Care Data Research Data Text Images Encoded Data Controlled Terminologies Gender Causes of Death Reuse Symbolic Manipulation Knowledge Networks Data Mining Knowledge Patient Care

Case Presentation The patient is a 50 year old female who presents to the emergency room with the chief complaint of cough and chest pain. The patient reports that she has had a productive cough for three days but that chest pain developed one hour ago. She reports that she was treated in the past for tuberculosis while she was pregnant, and that she is allergic to Bufferin. Physical examination reveals a well-developed, well-nourished female in moderate respiratory distress. Vital signs showed a pulse of 90, a respiratory rate of 22, an oral temperature of 101.3, and a blood pressure of 150/100. Examination reveals rales and rhonchi in the left upper chest. Labs:Chem7 (serum): Glucose 100 Chem7 (plasma): Glucose 150 CBC: Hgb 15, Hct 45, WBC 11,000 A fingerstick blood sugar was 80 Urinalysis showed protein of 1+ and glucose of 0 Chest X-ray: Left upper lobe infiltrate, left ventricular hypertrophy The patient is started on antibiotics and aspirin and is admitted to the hospital. A medical student reviewing the case is concerned about patients with pneumonia and myocardial infarction. She decides to do a literature search. The ER physician is wondering if this patient could be heralding an epidemic.

Reuse of Clinical Data a)To what bed should the patient be admitted? b)What were all the results of the patient's blood glucose tests (including serum, plasma and fingerstick)? c)Does the patient have a history of tuberculosis? d)Is the patient allergic to any ordered medications? e)How often are patient with the diagnosis of myocardial infarction started on beta blockers? f)Can the patient’s data be used by an expert system? g)Can the patient’s data be used to search health literature? h)Does the patient represent an index case in an epidemic? i)Does the patient meet the criteria for a clinical trial of patients over the age of 50 with elevated blood pressure?

To what bed should the patient be admitted? “Patient is an 50 year old female…” Admission Discharge Transfer System “Put the patient in Room 5, Bed B…” Electronic Medical Record

To what bed should the patient be admitted? But: how does the computer know the patient is female? The record could say: “female” “Female” “FEMALE” “F” “Woman” “Girl”

Coding the Data: Gender Data element - gender Controlled terminology: Male, Female, Unknown Representation: M,F,U; 0,1,2 What about other values?

What’s the Gender?

What are the blood glucose test results?

420 ICD9-CM Tuberculosis Codes (plus 69 hierarchical codes) 010.PRIMARY TB INFECTION* 010.0PRIMARY TB COMPLEX* PRIM TB COMPLEX-UNSPEC PRIM TB COMPLEX-NO EXAM PRIM TB COMPLEX-EXM UNKN PRIM TB COMPLEX-MICRO DX PRIM TB COMPLEX-CULT DX PRIM TB COMPLEX-HISTO DX PRIM TB COMPLEX-OTH TEST 010.1PRIMARY TB PLEURISY* 010.8PRIM PROGRESSIVE TB NEC* 010.9PRIMARY TB INFECTION NOS* 011.PULMONARY TUBERCULOSIS* 012.OTHER RESPIRATORY TB* 013.CNS TUBERCULOSIS* 014.INTESTINAL TB* 015.TB OF BONE AND JOINT* 016.GENITOURINARY TB* 017.TUBERCULOSIS NEC* 018.MILIARY TUBERCULOSIS* Does the patient have a history of tuberculosis?

Thirteen TB codes not under 01x. 137.LATE EFFECT TUBERCULOSIS* 137.0LATE EFFECT TB, RESP/NOS 137.1LATE EFFECT CNS TB 137.2LATE EFFECT GU TB 137.3LATE EFF BONE & JOINT TB 137.4LATE EFFECT TB NEC 647.INFECTIVE DIS IN PREG* 647.3TUBERCULOSIS IN PREG* TB IN PREG-UNSPECIFIED TUBERCULOSIS-DELIVERED TUBERCULOSIS-DELIV W P/P TUBERCULOSIS-ANTEPARTUM TUBERCULOSIS-POSTPARTUM Does the patient have a history of tuberculosis?

New York Presbyterian Hospital Clinical Information Systems Architecture Clinical Database Medical Entities Dictionary Database Monitor Medical Logic Modules Database Interface Research Administrative Alerts & Reminders Results Review... Radiology Laboratory Discharge Summaries Reformatter

Medical Entities Dictionary: A Central Terminology Repository

K#1 = 4.2 K#1 = 3.3 K#2 = 3.2 K#1 = 3.0 Communicating Terminology Changes K#1 K#2 K#3 = 2.6 K#3

Patient Care Data Research Data Text Images Encoded Data Controlled Terminologies Gender Causes of Death Reuse Symbolic Manipulation Quality Control Desiderata Knowledge Networks Data Mining Knowledge Patient Care

Terminology Desiderata Concept orientation Concept permanence Nonsemantic identifiers Polyhierarchy Reject “Not Elsewhere Classified” Formal definitions Cimino JJ. Desiderata for controlled medical vocabularies in the Twenty-First Century. Methods of Information in Medicine; 1998;37(4-5):

Polyhierarchy disease cholerameningitis infectious diseaselung disease tuberculosis tuberculosis in pregnancy infectious disease in pregnancy

K#1 = 4.2 K#1 = 3.3 K#2 = 3.2 K#1 = 3.0 Communication with Hierarchies K#1 K#2 K#3 = 2.6 K#3

K#1 = 4.2 K#1 = 3.3 K#2 = 3.2 K#1 = 3.0 Communication with Hierarchies K#1 K#2 K K#3 K#3 = 2.6

Reject “Not Elsewhere Classified” The “Will Rogers Phenomenon”: During the Great Dust Bowl Era, when Oakies moved to California, the IQ in both states increased DiagnosisICD9-CM Code ICD9-CM Name Hepatitis A070.1Hepatitis A Hepatitis B070.3Hepatitis B Hepatitis C070.5Hepatitis NEC Hepatitis E070.5Hepatitis NEC 1996 DiagnosisICD9-CM Code ICD9-CM Name Hepatitis A070.1Hepatitis A Hepatitis B070.3Hepatitis B Hepatitis C070.4Hepatitis C Hepatitis E070.5Hepatitis NEC

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

MED Data Model MED CodeSlot CodeValue , "Serum Glucose Measurement" "mg/dl" "50" "110" "2345-7" "SMAC" "Glucose" "Serum Glucose Tests“ "CPMC Lab Test " SlotSlot Name 4SUBCLASS-OF 6PRINT-NAME 8PART-OF 16SUBSTANCE-MEASURED 18UNITS 39LOW-NORMAL-VALUE 40HIGH-NORMAL-VALUE 212LOINC-CODE Concept Oriented Concept Permanence Nonsemantic Identifier Polyhier- archy Formal Definitions

Using the MED MED QueryMED Translation Table Interface Engine WebCIS Decision Support

The MED and Messaging Ancillary System Local Codes MED Codes Clinical Data Repository Other Subscribers Interface Engine Translation Table

Using the MED Translation –What is the display name for …? –What is the ICD9 Code for …? –What is the aggregation class for …? Translation Tables Class-based questions –Is Piroxicam a nonsteroidal antiinflammatory drug? –What are all the antibiotics? Knowledge queries –What are the pharmaceutic ingredients of…?

What’s in the MED? Sunquest lab terms Cerner lab terms Digimedix drugs Cerner Drugs Sunquest Radiology ICD9-based problem list terms Eclipsys order catalogue Other applications Knowledge terms

The MED Today “Concept”-based (102,071) Multiple hierarchy (152,508) Synonyms (883,095) Translations (436,005) Semantic links (395,854) Attributes (2,030,184)

What are the blood glucose test results?

Using the MED for Summary Reporting Plasma Glucose Test Serum Glucose TestFingerstick Glucose Test Lab Test Intravascular Glucose Test Chem20 Display Lab Display What are the blood glucose test results?

DOP Summary What are the blood glucose test results?

WebCIS Summary What are the blood glucose test results?

Eclipsys Summary What are the blood glucose test results?

Adapting to Changing Requirements Labs ordered as panels of tests HCFA will only reimburse for tests Clinicians have to order tests separately But: they want to review them as panels Changing the architecture: –Order tests separately –Group them for display –2 FTEs –4 months of work Solution: 5 minute change in the MED

Lab Tests and Procedures in the MED Chem7 SMAC Lab Procedures CBC Lab Tests Glucose Sodium Hematocrit

Lab Tests and Procedures in the MED Lab Tests Glucose Sodium Chem7 SMAC Lab Procedures CBC Hematocrit Orderable Tests

1)Check the drugs’ allergy codes, or… 2)Infer the allergy codes from the MED, or… 3)Use formal definitions in the MED to check ingredients Bufferin Enteric-Coated Aspirin Aspirin Preparations Aspirin has-ingredient Allergy: Bufferin Ordered Medications: Enteric-Coated Aspirin If ingredient of allergic drug equals ingredient of ordered drug, then send alert Is the patient allergic to any ordered medications?

Tuberculosis Infection Primary TB Pleurisy Primary TB Complex Primary TB (010) Pulmonary TB (011) Other Resp TB (012) Primary TB Pleurisy No Exam Primary TB Pleurisy Uspec Late Effect TB (137) TB in Preg (647.3) Infective Disease in Pregnancy (647) Primary TB Complex No Exam Primary TB Complex Uspec Does the patient have a history of tuberculosis?

How often are patient with the diagnosis of myocardial infarction started on beta blockers?

select patient_id, time = primary_time from visit2004_diagnosis where diagnosis_code = 2618 and b.primary_time between '01/01/2000' and '01/01/2005' and b.comp_code = How often are patient with the diagnosis of myocardial infarction started on beta blockers?

Potassium Hypokalemia Serum Potassium Test Serum Specimen Serum Abnormalities of Serum Potassium Can the patient’s data be used by an expert system?

Gentamicin Injectable Gentamicin Gentamicn Sensitivity Test Serum Gentamicin Level Gentamicin Toxicity Etiology Measures Sensitivity Substance Measured Has ingredient Drug Information Expert System PubMed Can the patient’s data be used to search health literature? Lab Manual

Patient Care Data Research Data Text Images Encoded Data Controlled Terminologies Gender Causes of Death Reuse Symbolic Manipulation Quality Control Desiderata Knowledge Networks Data Mining Knowledge Patient Care Reuse of Clinical Data

a)To what bed should the patient be admitted? b)What were all the results of the patient's blood glucose tests (including serum, plasma and fingerstick)? c)Does the patient have a history of tuberculosis? d)Is the patient allergic to any ordered medications? e)How often are patient with the diagnosis of myocardial infarction started on beta blockers? f)Can the patient’s data be used by an expert system? g)Can the patient’s data be used to search health literature? h)Does the patient represent an index case in an epidemic? i)Does the patient meet the criteria for a clinical trial of patients over the age of 50 with elevated blood pressure?

Terminology is key to data integration and reuse High-quality terminology supports high-quality data integration and reuse “Desiderata” facilitate high quality Columbia/NYPH Medical Entities Dictionary  Serves as a repository for institutional and standard terminologies  Uses multihierarchy semantic network  Supports sophisticated data integration  Supports sophisticated data reuse Conclusions

Questions ?