LAUSR

BACKGROUND Because most sources of administrative claims data do not contain laboratory result data, researchers rely on diagnosis codes to identify cases of disease. The validity of using diagnosis codes to identify chlamydial and gonococcal infections in administrative claims data remains largely uninvestigated. METHODS We conducted a retrospective cohort analysis using OptumLabs® Data Warehouse, which includes de-identified medical (inpatient and outpatient) claims and laboratory test results. Among males and females aged 15-39 years during 2003-2017, we identified chlamydia and gonorrhea test results and corresponding diagnosis codes. Using test results as the gold standard, we calculated the sensitivity and specificity of chlamydia and gonorrhea diagnosis codes to identify laboratory confirmed infections. RESULTS We identified 9.7 million chlamydia and gonorrhea test results among 3.1 million enrollees. Of the 176,241 positive chlamydia test results, only 11,515 had a corresponding diagnosis code, for a sensitivity of 6.5 (95% confidence interval [CI]: 6.4-6.7) and a specificity of 99.5 (95% CI: 99.5-99.5). Corresponding diagnosis codes were identified for 8,056 of the 31,766 positive gonorrhea test results for a sensitivity of 25.4 (95% CI: 24.9-25.8) and a specificity of 99.7 (95% CI: 99.7-99.7). CONCLUSIONS Our findings indicate that using only ICD-CM diagnosis codes to identify chlamydial and gonococcal infections substantially underestimates the burden of these diseases and inaccurately classifies laboratory confirmed infections.