(B-229) Validation of Diagnostic Codes for Identifying Chlamydial Infections from TriNetX Electronic Health Record Data in the United States

Background: There are limited data on the accuracy of diagnostic codes for chlamydial infections recorded in the US electronic health records (EHR). TriNetX is a growing global federated database that provides web-based, real-time, secure access to patient-level EHRs. Although TriNetX EHR database has been used to study some infectious diseases, its suitability for studying chlamydial infections remains unknown.

Objectives: To determine the validity of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes of chlamydial infections in the TriNetX USA Network.

Methods: A retrospective cohort study was conducted using the TriNetX USA Network, covering ~166.5 million US patients from over 80 healthcare organizations as of January 2025. The study population included patients aged 14 to 44 years, identified between 1 January 2016 and 31 October 2024. Patients must have ≥1 ICD-10-CM diagnosis code for chlamydial infections caused by various Chlamydia species (including C. trachomatis, C. psittaci, and C. pneumoniae) OR a known Nucleic Acid Amplification Test (NAAT) result. Patients with an ICD diagnosis but without NAAT results were excluded. The index date was the date of the first-recorded diagnosis code, or the date of the first-recorded NAAT result in the absence of diagnosis code for chlamydia. All eligible patients were categorized into four mutually exclusive groups based on the presence of ICD diagnosis code (yes or no) and NAAT results (positive or negative): true positive cases, false positive cases, false negative cases, and true negative cases. To validate chlamydia ICD codes, positive predictive value (PPV), negative predictive value (NPV), sensitivity (Se) and specificity (Sp) were calculated based on NAAT results. The corresponding 95% confidence intervals (CI) were calculated using the exact binomial method. Furthermore, the PPV, NPV, Se and Sp were also estimated for Chlamydia trachomatis (CT) infections associated with the genital urinary tract.

Results: The preliminary results included 4,889,630 eligible patients. The PPV for chlamydia ICD codes was 83.60% (95% CI: 83.41%, 83.79%); NPV was high (95.25%, 95% CI: 95.23%, 95.27%); Se was 38.73% (95% CI: 38.56%, 38.90%) and Sp was 99.39% (95% CI: 99.38%, 99.39%). The PPV, NPV and Sp were similar when analysis restricted for CT infections associated with the genital urinary tract, while Se decreased to 9.56% (95%: 9.46%, 9.66%).

Conclusions: The study indicates that diagnostic codes can accurately identify chlamydia cases in the TriNetX USA Network. However, the low sensitivities suggest that most chlamydia cases, particularly cases of CT infections, could be missed without laboratory test results.