Can Diagnostic Codes in Health Care Claims Data Identify Confirmed Chlamydial and Gonococcal Infections? A Retrospective Cohort Study, 2003 to 2017.

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 deidentified medical (inpatient and outpatient) claims and laboratory test results. Among males and females aged 15 to 39 years during the period 2003-2017, we identified chlamydia and gonorrhea test results and corresponding diagnosis codes. Using test results as the criterion 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 8056 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 International Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification diagnosis codes to identify chlamydial and gonococcal infections substantially underestimates the burden of these diseases and inaccurately classifies laboratory-confirmed infections.