Metrics included: PAEA End of Rotation exams, PACKRAT scores, academic performance in clinical medicine didactic courses, cumulative grade point average, and select demographic and admissions attributes (age, sex, and first generation to attend college). The purpose of this multi-institutional study was to examine the relationship between PANCE scores and student performance metrics/attributes from PA program graduates from 2017-2019.Ī multiple linear regression was calculated to predict PANCE score indicators based on student attributes and performance metrics from 3 PA programs. Given the 2019 Physician Assistant National Certifying Exam (PANCE) blueprint update from the National Commission on the Certification of Physician Assistants, it is imperative that programs conduct analyses of student performance metrics and PANCE scores. The lack of effect modification by demographic and socioeconomic variables suggests that associations do not significantly differ by these metrics. The significant difference in association identified between programs suggests that the predictive ability of the exam is not uniform. The composite score had the largest magnitudes of association with PANCE scores and odds of LPP. Effect modification was not observed by any investigated variable. Hierarchical regression models and ROC curves identified significant variability in associations among programs. The composite score also strongly predicted decrements in odds of LPP (odds ratio: 0.46 95% CI: 0.38-0.55). The PACKRAT scores were standardized for each year to the national mean and SD.Īdjusted HRMs across 5 programs (n = 1014) found the composite score to have the strongest association, with a 10-percentile-point increase associated with a 22-point (95% confidence interval : 19-26) increase in PANCE score. Models were adjusted for demographic and socioeconomic variables. Receiver operating characteristic (ROC) curves were used to examine the sensitivity, specificity, positive predictive values, and negative predictive values for various PACKRAT metrics/cut points. Likelihood ratio tests were used to evaluate differences in associations between programs and effect modification by demographic and socioeconomic variables. Linear and logistic hierarchical regression models (HRMs) were used to evaluate associations between PACKRAT metrics and (1) continuous PANCE scores and (2) odds of low PANCE performance (LPP), respectively. ![]() It is unknown, however, whether these associations (1) vary across programs (2) differ by PACKRAT metrics (first-year, second-year, and composite score ) or (3) are modified by demographic or socioeconomic variables. ![]() The Physician Assistant Clinical Knowledge Rating and Assessment Tool (PACKRAT®) is a known predictor of performance on the Physician Assistant National Certifying Exam (PANCE).
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