A Modeling Exercise to Identify Predictors of Student Readiness for Advanced Pharmacy Practice Experiences

Abstract

Objective. To model the relationship of common pharmacy education assessment data including student demographics, pre-pharmacy performance, core didactic performance, and external testing measures to identify predictors of student readiness for advanced pharmacy practice experiences (APPEs). Methods. The associations between 23 predictive covariates from 226 graduating students from 2015-2018 (5786 observations) and APPE readiness as measured by midpoint core APPE scores were modeled. Multiple linear and Poisson regression models with backward selection were used. A selection criterion of p >.10 was used for covariate elimination from the model. Three models were evaluated: average of all midpoint core APPE rotation scores; average of midpoint acute care pharmacy practice and ambulatory care APPE rotation scores; and number of midpoint core clerkship failing scores. Results. The average age of the population at admission was 25.4±4.5 years, 47% were female, and 75.2% had prior degrees. Across the three prediction models, knowledge-retention covariates were the strongest predictors. Total score on the Pharmacy Curriculum Outcomes Assessment was a modest yet consistent predictor across the models. All other significant predictors were unique to the various models. Conclusion. This four-year, population-based modeling study of the relationship of common pharmacy education assessment data to APPE midpoint scores shows a modest correlation with knowledge-based measures. There is a need for greater innovation in this area of research.

Keywords: APPE readiness; advanced pharmacy practice experiences; modeling.