Abstract
BackgroundCommunity clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.MethodsWe selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.Results1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.ConclusionsFuture research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.
Highlights
Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments
We found that the sensitivity of syndrome definitions based on diagnostic codes in physician claims for identifying syndromes was low, the positive predictive value (PPV) was moderate to high, and the specificity and negative predictive value (NPV) were near-perfect
We found that diagnostic codes in physician claims from community healthcare settings have low sensitivity, moderate to high PPV, and near-perfect specificity and NPV for identifying 5 syndromes
Summary
Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. Syndromic surveillance is used widely by public health departments to detect and monitor unusual disease activity in the population by extracting nonspecific clinical data from information systems in clinical settings [1,2,3,4]. Many syndromic surveillance systems use International Classification of Disease, 9th revision (ICD-9) diagnostic codes in administrative databases to monitor syndrome occurrence [12]. For this purpose, expert panels have generated groupings of ICD-9 codes corresponding to conceptual syndrome definitions [13]. Administrative databases offer great promise for population-based surveillance by providing access to diagnostic information from many sites, including community healthcare settings. Variation in diagnostic coding between physicians and between institutions is expected
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