Lost in translation: Exposure misclassification when relying on days supply in pharmacy claims data.

摘要

Administrative pharmacy claims data are frequently utilized in pharmacoepidemiology. Days supply values are the most commonly used to estimate drug exposure. This research investigated the potential for exposure misclassification when relying on days supply values to quantify drug adherence and estimate drug effectiveness. With scheduled long-dose intervals, osteoporosis drugs provided a unique case example to examine the potential for misclassified days supply values. Using Ontario administrative claims data, three independent, yet related studies were completed. First, a cross-sectional study of all osteoporosis medications dispensed in Ontario identified potential inaccuracies in days supply values, particularly in long-term care (LTC), where only 59% of days supply values matched pre-defined expected values. In comparison, 90% of community prescriptions matched the expected. Next, two cohort studies were completed to investigate the potential impact of the noted variation in days supply reporting on measures of medication adherence (Study Two) and drug effectiveness (Study Three). To adjust for misclassification, dose-specific cleaning algorithms were developed based on the identification of logical typos and refill patterns, resulting in two values that could be compared; the observed and cleaned days supply. Measures of compliance and persistence were used to identify patient adherence, and were calculated using the observed and cleaned days supply. Results in Study Two identified that data cleaning significantly increased estimates of drug adherence, particularly among LTC residents, where mean compliance increased from 59% to 83% and proportion persisting with therapy increased from 62% to 78%. In the third study, Cox proportional hazard models were used to estimate the relationship between compliance and hip fractures. Results identified important differences in effect estimates following data cleaning, particularly in LTC, where a significant 35% (HRobserved=0.99 to HRcleaned=0.65) change in hazard ratio estimates was observed for the effect of high compliance on fracture risk. Overall, results identified larger differences in LTC settings where exposure was most likely to be misclassified; however, important differences were identified when all patients were combined. Cumulatively, the findings of this thesis have important methodological implications for pharmacoepidemiologic research, and will inform best practices when using days supply values.