Different electronic cohort definitions caused the proportion of identified atrial fibrillation patients to vary from 61% (ICD codes) to 83% (NLP), and oral anticoagulant rates from 50% to 66%.
Observational (n=22,000)
Different electronic cohort definitions for identifying atrial fibrillation in EMRs result in substantially different study samples, threatening the reproducibility of EMR-based research.
Background Electronic medical records ( EMR s) allow identification of disease‐specific patient populations, but varying electronic cohort definitions could result in different populations. We compared the characteristics of an electronic medical record –derived atrial fibrillation ( AF ) patient population using 5 different electronic cohort definitions. Methods and Results Adult patients with at least 1 AF billing code from January 1, 2010, to December 31, 2017, were included. Based on different electronic cohort definitions, we trained 5 different logistic regression models using a labeled training data set (n=786). Each model yielded a predicted probability; patients were classified as having AF if the probability was higher than a specified cut point. Test characteristics were calculated for each model. These models were then applied to the full cohort and resulting characteristics were compared. In the training set, the comprehensive model (including demographics, billing codes, and natural language processing results) performed best, with an area under the curve of 0.89, sensitivity of 0.90, and specificity of 0.87. Among a candidate population (n=22 000), the proportion of patients identified as having AF varied from 61% in the model using diagnosis or procedure International Classification of Diseases ( ICD ) billing codes to 83% in the model using natural language processing of clinical notes. Among identified AF patients, the proportion of patients with a CHA 2 DS 2 ‐ VAS c score ≥2 varied from 69% to 85%; oral anticoagulant treatment rates varied from 50% to 66% depending on the model. Conclusions Different electronic cohort definitions result in substantially different AF study samples. This difference threatens the quality and reproducibility of electronic medical record–based research and quality initiatives.
Shah et al. (Wed,) conducted a observational in Atrial Fibrillation (n=22,000). Electronic cohort definitions vs. Different electronic cohort definitions was evaluated on Proportion of patients identified as having AF. Different electronic cohort definitions caused the proportion of identified atrial fibrillation patients to vary from 61% (ICD codes) to 83% (NLP), and oral anticoagulant rates from 50% to 66%.