Development and Validation of an Algorithm to Identify Endometrial Adenocarcinoma in US Administrative Claims Data

Abstract

Background Endometrial adenocarcinoma is the most prevalent type of endometrial cancer. Diagnostic codes to identify endometrial adenocarcinoma in administrative databases, however, have not been validated. Objective To develop and validate an algorithm for identifying the occurrence of endometrial adenocarcinoma in a health insurance claims database. Methods To identify potential cases among women in the HealthCore Integrated Research Database (HIRD), published literature and medical consultation were used to develop an algorithm. The algorithm criteria were at least one inpatient diagnosis or at least two outpatient diagnoses of uterine cancer (International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) 182.xx) between 1 January 2010 and 31 August 2014. Among women fulfilling these criteria, we obtained medical records and two clinical experts reviewed and adjudicated case status to determine a diagnosis. We then estimated the positive predictive value (PPV) of the algorithm. Results The PPV estimate was 90.8% (95% CI 86.9–93.6), based on 330 potential cases of endometrial adenocarcinoma. Women who fulfilled the algorithm but who, after review of medical records, were found not to have endometrial adenocarcinoma, had diagnoses such as uterine sarcoma, rhabdomyosarcoma of the uterus, endometrial stromal sarcoma, ovarian cancer, fallopian tube cancer, endometrial hyperplasia, leiomyosarcoma, or colon cancer. Conclusions An algorithm comprising one inpatient or two outpatient ICD-9-CM diagnosis codes for endometrial adenocarcinoma had a high PPV. The results indicate that claims databases can be used to reliably identify cases of endometrial adenocarcinoma in studies seeking a high PPV.