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Chronic Hepatitis B Surveillance in Santa Clara County

Chronic Hepatitis B Surveillance in Santa Clara County. An evaluation to understand meaning and usefulness of surveillance data. Sara H. Cody, MD Deputy Health Officer. Background and Impetus. Chronic Hepatitis B is a high volume disease Majority of reports are from commercial labs

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Chronic Hepatitis B Surveillance in Santa Clara County

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  1. Chronic Hepatitis B Surveillance in Santa Clara County An evaluation to understand meaning and usefulness of surveillance data Sara H. Cody, MD Deputy Health Officer

  2. Background and Impetus • Chronic Hepatitis B is a high volume disease • Majority of reports are from commercial labs • Fall 2011: several concerning reports • Quest reporting “screening” rather than “confirmatory” results • Lab Corp reporting out of state pts

  3. Garbage in, garbage out?

  4. Hepatitis B data flow Hospital or Commercial Lab Provider Laboratory Report CMR SCCPHD via fax Clerks check faxes , date stamp Verify county of residence OOJ Compiled all data rec’d during 1st quarter of 2012 (Jan-Mar ) SCC resident Non-IgM IgM PHN review , sort into Probable, confirmed or perinatal Data entry into CalREDIE Clerk 4

  5. Magnitude of the problem

  6. Magnitude of the problem 1 – 1 ½ inches of Hep B lab reports/wk received over the fax

  7. Our questions • How accurate are the data we send off to CDPH? • What proportion were not true cases (mis-classified)? • What proportion were out of jurisdiction? • What proportion had incomplete data? • How meaningful are the data?

  8. CDPH intern to the rescue • How complete are the data? • Calculated completeness of lab reports* according to Title 17 • Surveyed physicians of patients with unknown addresses; calculated prevalence of in-county patients • Evaluated HBsAg lab results for confirmatory report

  9. CDPH intern to the rescue • How accurate are the case classifications? • Calculated sensitivity and positive predictive value of HBV classification • What is the burden of reporting for county staff? • Surveyed SCCPHD Staff • Identified inefficiencies of the surveillance system

  10. Findings

  11. Quest reports the majority of our chronic hepatitis B cases

  12. Title 17 requires labs to report certain variables

  13. Patient variables that labs actually report: • Name 99% • Age 99% • Gender 99% • Address 35% (Quest reported < 1%) • Phone 72% (Quest reported 68%)

  14. Provider variables that labs actually report: • Phone 63% (Kaiser and ARUP 0%)

  15. Only 35% of reports have pt address, but most reports with no patient address ARE in jurisdiction Address (1) Santa Clara County resident (105) Patients from Quest (334) Received responses (113) No Address (333) Sample (123) Out of jurisdiction (8) Prevalence of in-county patients in sample = 92.9% (95% CI = 86.53% - 96.89%) 15

  16. The majority of lab reports are likely unconfirmed HBsAg

  17. How accurate are the case classifications that we report? • Confirmed: case meets either of the laboratory criteria for diagnosis • Probable: a person with a singleHBsAg, HBV DNA, or HBeAg positive lab result and does not meet acute hepatitis B case definition

  18. How accurate are the case classifications that we report? Percentage of cases misclassified: 56.79%

  19. What is the burden of reporting? • 3 staff handle chronic Hep B reports • 70 hrs/wk allotted to chronic Hep B surveillance; takes 83 hrs to do the work • 20 hrs identifying patients that met the case def • 10 hrs collecting info on cases or potential cases • 50 hrs entering or modifying cases in CalREDIE • 3 hrs analyzing data on cases • Main finding: not enough time to do the work

  20. In summary • Lots of misclassification • Lots of missing information (Quest and ARUP biggest offenders) • Despite missing address info, most cases were SCC residents • Burden of surveillance system significant

  21. The bigger questions • Value of data: cost of data • Will ELR reduce the cost of Hep B surveillance? • Data for action? • What are our public health surveillance goals? • identify acute cases, investigate potential novel sources • identify pregnant women with chronic hep B • characterize population with chronic hep B • measure success of interventions and programs • Is population based surveillance the answer?

  22. Acknowledgements • SCCPHD • Shilpa Jani • Aileen Arellano • Laura Tang • Debra Duran • CDPH • Myra Martinez • Daryl Kong • Kathleen Winter • Kathy Harriman

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