1. Public Health Data Element Standardization - A Framework for Modeling Data Elements Used for Public Health Case Reporting Case Reporting Standardization Workgroup (CRSWg) Members: Jason Jacobs, BA Catherine Staes, BSN, MPH, PhD Sundak Ganesan, MD John Abellera, MPH (CRSWg Co-Lead) Hwa-Gan Chang, PhD (CRSWg Co-Lead)

2. Overview Background Problems Goal Methods Results Feedback

3. Case Reporting Standardization Workgroup (CRSWg) Project

4. Background University of Utah – Medical Informatics Class Project (Fall 2010) CSTE Position Statements include an unstructured section where the epidemiologist specifies the information they want to be included in a case report Problem: – Leads to unintended ambiguity and unnecessary variation – Often includes info needed for surveillance, not investigation

5. Problems (cont.) - Acute Hepatitis B

6. Problems (cont.) - Hepatitis A

7. Problems (cont.) - Chronic Hepatitis C

8. Problems Pre-coordinated concept Varying time periods of interest Inconsistent labels for the same concept Mismatch between public health requests for yes/no answer and typical health care data storage methods (e.g. Procedure)

9. Goal Evaluate and harmonize data elements present in the 2010 CSTE Position Statements (new / updates). Propose a framework for ongoing development and maintenance of CSTE position statement data elements that are used for Public Health Case Reporting (PHCR)

10. Methods Reviewed 7 CSTE Position Statements – Hepatitis group Hep A Acute Hep B Chronic Hep B Acute Hep C Chronic Hep C – Hansen’s – Cryptosporidiosis

11. Methods (cont.) Listed and harmonized data elements across CSTE Position Statements Grouped data elements based upon EHR modules such as Problem List, Procedures, Medications, Laboratory, etc… Modeled the data elements requested into questions (LOINC) and answers (e.g. SNOMED CT)

12. Methods (cont.) In some situations, the data elements have been mapped to information model (HL7 CDA). – HL7 Information model is the first choice for mapping the data element. Terminology model is the second choice (i.e. do not want to create or use the LOINC codes for HL7 slots) Reviewed current Implementation Guide for HL7 CDA R2 Public Health Case Reports – Used existing Clinical Templates to guide modeling

13. HL7 CDA PHCR Implementation Guide - Clinical Templates

14. Results In 7 Position Statements, we identified – 57 data elements -> 19 concepts that relate to: Risk associated procedure ("Procedures") Actual blood and/or body fluid exposure observation Possible exposure location and type – Others…halfway done Occupation observation Geotemporal History

15. HL7 CDA PHCR Implementation Guide - Clinical Templates

16. Scenario 1: Typical EHR Data Current Proposed (explicit, computable, interoperable) “Risk Associated Procedure”?

17. Scenario 1: History of Procedures Each clinical template has a disease-specific risk associated procedure.

18. Scenario 2: Not usually in EHR Current Problems – Time period of interest is unclear – Answer is numeric, not boolean – LOINC code exists (“55213-3”, “Number of male sexual partners in 6 months before symptom onset”) – Best method for modeling Create new LOINC codes for Public Health reporting needs?

19. Enable structured data request Create interface for epidemiologist to author structured data request – Used to build a query – Standardized across position statements – Example: for Hepatitis C, send information about:

20. Feedback / Summary Are we taking the right approach for standardizing the public health data elements present in CSTE position statements? 1)Map the data elements to EHR module 2)Distribute the information between Information Model (HL7) and Terminology Model (LOINC) 3)Distribute the data element information between the question (data element) and answer list (value set) 4)Reuse these data elements in Case Notification, Syndromic Surveillance, Immunization and ELR. 5)Apply this framework to all the other CSTE position statements and work closely with CSTE position statement authors to express the concepts unambiguously (structured format).