Using electronic health record data to identify incident uterine fibroids and endometriosis within a large, urban academic medical center: a validation study
Abstract
Electronic health records (EHRs) present opportunities to study uterine fibroids and endometriosis within diverse populations. When using EHR data, it is important to validate outcome classification via diagnosis codes. We performed a validation study of 3 approaches ([1] International Classification of Diseases-10 (ICD-10) code alone, [2] ICD-10 code + diagnostic procedure, and [3] ICD-10 code + all diagnostic information) to identify incident uterine fibroids and endometriosis patients among n = 750 NYU Langone Health 2016-2023. Chart review was used to determine the true diagnosis status. When using a binary classification system (incident vs nonincident patient), Approaches 2 and 3 had higher positive predictive values (PPVs) for uterine fibroids (0.86 and 0.87 vs 0.78) and for endometriosis (0.70 and 0.73 vs 0.66), but Approach 1 outperformed the other 2 in negative predictive values (NPVs) for both outcomes. When using a 3-level classification system (incident vs prevalent vs disease-free patients), PPV for prevalent patients was low for all approaches, while PPV/NPV of disease-free patients was generally above 0.8. Using ICD-10 codes alone yielded higher NPVs but resulted in lower PPVs compared with the other approaches. Continued validation of uterine fibroids/endometriosis EHR studies is warranted to increase research into these understudied gynecologic conditions.
