A Framework for Modeling Data Elements Used for Public Health Case Reporting

1. Jason Jacobs, BA1, Catherine Staes, BSN, MPH, PhD1, Rita Altamore, MD, MPH2, SundakGanesan, MD3 A Framework for Modeling Data Elements Used forPublic Health Case Reporting CRSWg • 1 Department of Biomedical Informatics, University of Utah, Salt Lake City, UT • 2 Washington State Department of Health, Olympia, WA • 3 Northrop Grumman Consultant to CDC, Atlanta, GA • Background • CSTE publishes Position Statements (PS) that specify reporting rules and case report content for nationally notifiable diseases • In the PS, disease-specific data elements to be included in case reports are unstructured, and sometimes ambiguous or redundant • CRSWg identified a need for standardization of data elements • Automated public health (PH) case reporting requires a standardized specification for information to be provided in the case report Recommended approach for gathering information to support investigation and surveillance • Discussion • Recommended Next Steps • Restructure content in Section VI-C using the proposed model, with input from local, state, and federal epidemiologists • Address "What time period of interest related to risk of transmission?" should be used to query for information • Harmonize current social history questions and address "What level of specificity is most useful for the public health investigator for assessing potential exposures and transmission risks?" • Request LOINC codes for well-established questions needed for investigation but not typically found in an EHR • Conclusions • The strategy will: • Help epidemiologists create, validate, and maintain computable specifications for case report content • Help implementers map CSTE data elements and query an EHR • Avoid need to create LOINC codes for each disease-specific data element • This disease-specific information can supplement a generic case report and is not required to initiate reporting Harmonize and Model Data Elements Disease Time period Harmonized concepts (e.g. dialysis, tattoo) Concepts NOT Typically in an EHR Concepts Typically in an EHR • Standardize the concepts • Create standard representations for concepts nottypically captured in an EHR, e.g. “History of tattoos” • Map to typical EHR modules, such as: • Problem List • Medications • Procedures • Map to LOINC • Determine which concepts are represented by existing LOINC codes • “Number of male sexual partners in 6 months before symptom onset” • Request clinical LOINC codes for concepts that are: • Unlikely to change in meaning • Not typically found in the EHR • Not already present in LOINC Map to standard vocabulary For example, map to existing LOINC, ICD, or SNOMED terms • Objective • Propose framework for ongoing development and maintenance of data elements requested in PH case reports Assess the time period of interest to be used to query for relevant information Restructure Content of Section VI-C Example from Acute Hepatitis C Position Statement Current Epidemiological Risk Factors During the 2 weeks to 6 months prior to the onset of symptoms did the patient: Undergo hemodialysis Receive blood or blood products Product Date Receive a tattoo or body piercing The number of female sex partners Revised Exposure period: 2 weeks to 6 months Time period of interest related to risk of transmission: Past 8 months Information to extract from EHR if present during the time period of interest: Procedures Renal dialysis Blood or blood product administration Information to ask as questions concerning the time period of interest: History of tattoos History of body piercing Number of female sex partners • Methods • Reviewed 10 Position Statements(5 hepatitides, coccidioidomycosis, cryptosporidiosis, babesiosis, Lyme disease, Hansen’s disease) • Harmonized data elements and mapped them to concepts found in an EHR • Evaluated the clinical statement model used in HL7 Public Health Case ReportingCDA R2 IG as an approach to handle the requested information • Explored options for representing the data elements requested using a terminology model (question/answer) vs. an information model (HL7 CDA), allowing for flexibility in expressing the time period of interest Time Period of Interest Related to Risk of Transmission Exposure Period Diagnosis 6 months 2 weeks Onset ? Acknowledgements Contact Information • Findings • Some data items in the Position Statements that represent risk factors for disease acquisition and transmission are not typically gathered by clinicians during patient care. • A PH investigator may gather evidence within a wider window than the traditional exposure period, for example, about dialysis within 7 months of acute onset of hepatitis B, not 6 months. • In 10 Position Statements, we found 106 unique data elements for procedures and exposures that could be reduced to about 40 unique concepts that better match EHR data elements. • NLM Training Grant No. NL5T15LM007124 • CDC Center of Excellence in Public Health Informatics P01HK000069-03 Jason Jacobsjason.jacobs@utah.edu