Challenges in Creating Person-Level Data for Chronic Hepatitis Surveillance

Brief Summary
Chronic hepatitis B (HBV) and C (HCV) are major public health problems affecting millions of people in the United States. In New York City, laboratories and clinicians are required to report positive HBV and HCV tests, which we automatically import into our surveillance database; we receive over 90,000 reports of each disease annually. Because patients with chronic hepatitis may be tested frequently, there are often multiple reports of positive tests per patient. To handle this large volume, we have automated our matching process for identifying which reports belong to the same patient. Managing and reporting hepatitis surveillance data is complex because patient-level information must be pulled and summarized from these multiple reports. Therefore, we use a variety of methods to structure datasets for analysis and reporting in a standardized way. First, our surveillance database creates one single “event” of disease per patient, which includes demographic information taken from the earliest report for that disease. For diagnosis date (the date we use for structuring all our datasets), we use the specimen date of the earliest positive test. Second, customized SAS code is used to create tables summarizing multiple laboratory test results for each patient. Four test types are reportable for HCV (two types of antibody tests, RNA, and genotype): we create four variables to capture whether a positive result was ever reported for each test type to determine whether the patient met the case definition and also received recommended follow up testing. For HBV, we calculate case definition status (two positive tests greater than six months apart) by subtracting the date of the earliest positive test from the date of the most recent positive test. Finally, for summary data published in our Hepatitis Surveillance Report, we analyze and report patients newly reported that calendar year, rather than all patients who had a positive test reported that year. Although these are decisions we have made in order to maintain and present our data uniformly, other health departments have their own methods for data management. Therefore, comparing chronic hepatitis data across jurisdictions is challenging. Agreement on national standards for data management could improve comparability of published surveillance data.