The Random Effects Warfarin Days' Supply (REWarDS) Model: Development and Validation of a Novel Method for Estimating Exposure to Warfarin Using Administrative Data. Issue 6 (6th January 2022) - Salmasi, Shahrzad; Högg, Tanja; Safari, Abdollah; De Vera, Mary A; Lynd, Larry D; Koehoorn, Mieke; Barry, Arden R; Andrade, Jason G; Loewen, Peter
Abstract: Warfarin's complex dosing is a significant barrier to measurement of its exposure in observational studies using population databases. Using population-based administrative data (1996–2019) from British Columbia, Canada, we developed a method based on statistical modeling (Random Effects Warfarin Days' Supply (REWarDS)) that involves fitting a random-effects linear regression model to patients' cumulative dosage over time for estimation of warfarin exposure. Model parameters included a minimal universally available set of variables from prescription records for estimation of patients' individualized average daily doses of warfarin. REWarDS estimates were validated against a reference standard (manual calculation of the daily dose using the free-text administration instructions entered by the dispensing pharmacist) and compared with alternative methods (fixed window, fixed tablet, defined daily dose, and reverse wait time distribution) using Pearson's correlation coefficient ( r ), the intraclass correlation coefficient, and the root mean squared error. REWarDS-estimated days' supply showed strong correlation and agreement with the reference standard ( r  = 0.90 (95% confidence interval (CI): 0.90, 0.90); intraclass correlation coefficient = 0.95 (95% CI: 0.94, 0.95); root mean squared error = 8.24 days) and performed better than all of the alternative methods. REWarDS-estimated days' supply was valid and more accurate than estimates from all other available methods. REWarDS is expected to confer optimal precision in studies measuring warfarin exposure using administrative data.