Predicting success in pharmaceutical calculations

Abstract Introduction Understanding preadmission predictors of success in pharmacy calculations, an important aspect of pharmacy practice, could impact admissions selection and advising practices. The objective of this study was to determine which student specific preadmission variables best predict success in a pharmaceutical calculations course. Methods Preadmission data from 388 students who completed a one semester pharmaceutical calculations course between 2013 and 2016 were evaluated. This retrospective analysis was performed to determine which of the independent preadmission variables were positively correlated to the pharmaceutical calculations course grade. Fifteen preadmission variables, including demographics, grade point average (GPA), Pharmacy College Admission Test (PCAT) score, prior degrees, and number of pre-professional credit hours completed, were evaluated. Descriptive statistics were used for baseline characteristics and relative importance analysis was used to examine association between the dependent and independent variables. Results The relative importance analysis revealed eight of the fifteen preadmission variables were significantly correlated with final grades in pharmaceutical calculations. Overall, 26.1% of the variance was explained by these variables. GPA (cumulative and science specific) and PCAT (quantitative and verbal) were the strongest indicators. Conclusions Preadmission GPA and PCAT scores were the best predictors of success in a pharmaceutical calculations course. About one quarter of the variance was explained by the identified predictive variables, therefore other factors, not evaluated in this study, likely influence the success in pharmaceutical calculations and should be investigated to determine a more dependable set of predictors.