Validation of an Algorithm to Identify Ectopic Pregnancy in a Large Integrated Health Care Delivery System (Preprint)

BACKGROUND Surveillance of ectopic pregnancy (EP) using electronic databases is important. There is no published study that assessed the validity of EP case ascertainment using electronic health records. OBJECTIVE We aimed to assess the validity of an enhanced version of a previously validated algorithm, which used a combination of encounters with EP related diagnostic/procedure codes and methotrexate injections. METHODS Medical records of 500 women, aged 15-44 years with membership at Kaiser Permanente Southern and Northern California between 2009-2018 with a potential EP were randomly selected for chart review and true cases were identified. The enhanced algorithm included ICD-10 diagnostic/procedure codes, used telephone appointment visits, and excluded cases with only abdominal EP diagnosis codes. The sensitivity, specificity, positive (PPV) and negative (NPV) predictive values and the overall performance (Youden's index and F-score) of the algorithm were evaluated and compared to the validated algorithm. RESULTS There were 334 true positive and 166 false positive EP cases with available records. True positive and true negative EP cases did not differ significantly according to maternal age, race/ethnicity and smoking status. EP cases with only one encounter and non-tubal EP were more likely to be misclassified. The sensitivity, specificity, PPV, and NPV of the enhanced algorithm for EP were 97.6%, 84.9%, 92.9%, and 94.6%, respectively. The Youden index and F-score were 82.5% and 95.2%, respectively. The sensitivity and NPV were lower at 94.3% and 88.1%, respectively, for the previously published algorithm. The sensitivity of surgical procedure codes from electronic chart abstraction to correctly identify surgical management was 91.9%. The overall accuracy, defined as the percentage of EP cases with correct management (surgical, medical, and unclassified) identified by electronic chart abstraction, was 92.3%. CONCLUSIONS The performance of the enhanced algorithm for EP case ascertainment in the integrated health care databases is adequate to allow for use in future epidemiological studies. Use of this algorithm will likely result in better capture of true EP cases than the previously validated algorithm. CLINICALTRIAL