The Promise of Pathology Informatics

1. The Promise of Pathology Informatics James J. Cimino, M.D. Department of Medical Informatics Columbia University

2. Questions You WouldLike Answered • How can we link patient record information to pathology specimens to support clinical research? • If we can do this, what will be possible?

3. The Question I ThinkYou Need to Answer • How can pathology information be represented to support data reuse?

4. What is “Data Reuse”? In contrast to the primary use of health data (“show it to the doctor”)… …any secondary use of the data for tasks ranging from direct patient care, to financial purposes, to research

5. My Goal for this Talk • Expand upon the notion of data reuse • Discuss representational issues needed for reuse • Propose a challenge

6. First Admission: August, 1983 In August, 1983, a 50 year old male presented to the St. Vincent’s Hospital (NY) emergency room with a scalp laceration due to a falling paint can. The wound was cleaned and sutured, and the patient was give a follow up appointment for surgery clinic. Two weeks later, the patient was seen at the scheduled clinic visit and was found to have delayed healing of one portion of the wound. After several weekly visits, the poorly-healing area was excised and the wound was closed. The patient had a good result and was discharged from further follow up.

7. Second Admission - March, 1984 The patient was brought to the emergency room for recent increasing lethargy. Laboratory evaluation was remarkable only for a calcium of 17 mg/dl. The patient was treated aggressively with hydration and diuretics, but expired shortly after admission. A diagnostic report was received.

8. Prologue as Epilogue The pathology report from the wound revision the previous September included the following phrase: “Metastatic adenocarcinoma of uncertain origin is noted at the tissue margins”

9. What Happened? • The primary use of the data was to produce a report • An information system could have managed that report • High-quality data representation could have supported the reuse of the data by a decision support system

10. Pathology Information Today • Narrative reports • Structured reports • Coded data (ICD9-CM vs. SNOMED vs. Local Codes)

11. Potential for Reuse of Pathology Information • Direct use by care providers • Billing • Quality assurance/Case management • Clinical research (including Outcomes) • Automated decision support • Integration with other information systems

12. Data Monitor Repository Research Database Example:Retrospective Clinical Research Pathology System Financial System Laboratory System Pharmacy System

13. Decision Support KB Data Monitor Repository Research Database Example:Prospective Clinical Research Pathology System Financial System Laboratory System Pharmacy System

14. Example:Prospective Clinical Research • Data monitor checks eligibility criteria • Alert sent to subject recruiter • Example: Biphosphonate Study

15. Example:Automated Decision Support • Data monitor checks for triggering conditions • Medical Logic Modules decide if warning conditions are present • Message sent to appropriate channel • Example: Tuberculosis culture result

16. Caveats: TB Example • 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?

17. 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.

18. “No Growth” Results No Growth after 24 Hours No Growth after 48 Hours No Growth after ... No Growth after 72 Hours How we Outsmarted the Lab No Growth to Date No Growth

19. Example:Linking to On-line Resources • Clinician reviewing reports will have information needs • On-line information sources can satisfy that need • Data from report can be used to automate the query

30. Linking Text Reports to On-line Information Sources • Natural Language Processing • Data representation to support reuse • Codification of information needs

46. How does CPMC Support Data Reuse? • Natural Language Processing • High-quality controlled terminology ( “codes”)

47. High-Quality Terminology • Concept oriented - with concept permanence • Multiple synonyms • Multiple hierarchies • Semantic network of interconcept relations • Integration of low-level (clinical) terminology with high-level (aggregation) terminology

48. Laboratory Test Drug Serum Gentamicin Test Aminoglycoside Antibiotic Measures Measures Has Ingredient Medical Entities Dictionary Chemical Gentamicin Random Gentamicin Level Main-MeSH: Supplementary-MeSH: "Gentamicin/bl" Measures: Gentamicin Injectable Gentamicin Trade-Name: Garamycin" Has-Ingredient: Gentamicin

49. Pathology Informatics“Grand Challenges” • Representing the concepts in reports • Represent the relationships among concepts in reports • Representing the concepts for aggregation and retrieval • Integration of the concepts

50. What Will Be Possible • Data retrieval • Data mining • Improvements in report quality • Improved reuse of data… …including patient care