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Considerations Around Predicting Physician Assistant National Certifying Exam Scores From PACKRAT®: A Multiprogram

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  • 1Trenton Honda, PhD, PA-C, is a division chief and associate professor in the Division of Physician Assistant Studies at the University of Utah, Salt Lake City, Utah. Carey Barry, MHS, PA-C, is an assistant clinical professor in the Northeastern University Physician Assistant Program, Boston, Massachusetts. Shalon R. Buchs, MHS, PA-C, is an associate director and an assistant professor in the School of Physician Assistant Studies at the University of Florida, Gainesville, Florida. Breann L. Garbas, DHSc, PA-C, is an assistant professor in the School of Physician Assistant Studies at the University of Florida, Gainesville, Florida. Susan T. Hibbard, PhD, is the director of assessment and evaluation and an assistant professor in the Division of Physician Assistant Studies at Duke University School of Medicine, Durham, North Carolina. Alison McLellan, MMS, PA-C, is the director of academic education and an assistant professor in the School of Physician Assistant Studies at Pacific University, Hillsboro, Oregon. Theresa Riethle, MS, PA-C, is a program director and an associate professor in the Physician Assistant Studies Program at Bay Path University, Longmeadow, Massachusetts. Lori E. Swanchak, PhD, PA-C, is an interim dean for the College of Health and Human Services at Marywood University, Scranton, Pennsylvania.

The Journal of Physician Assistant Education : the Official Journal of the Physician Assistant Education Association
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Summary

The Physician Assistant Clinical Knowledge Rating and Assessment Tool (PACKRAT®) composite score strongly predicts Physician Assistant National Certifying Exam (PANCE) performance. However, its predictive accuracy varies significantly across different PA programs.

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Area of Science:

  • Medical Education
  • Health Professions Education
  • Assessment and Evaluation

Background:

  • The Physician Assistant Clinical Knowledge Rating and Assessment Tool (PACKRAT®) is a validated predictor of Physician Assistant National Certifying Exam (PANCE) success.
  • Previous research has not fully explored variations in PACKRAT®'s predictive utility across different educational programs or demographic factors.

Purpose of the Study:

  • To investigate whether the association between PACKRAT® metrics and PANCE performance varies across programs.
  • To determine if PACKRAT® metrics differ in their prediction of PANCE scores based on first-year, second-year, or composite scores.
  • To examine if demographic or socioeconomic variables modify the relationship between PACKRAT® and PANCE outcomes.

Main Methods:

  • Hierarchical regression models (linear and logistic) were employed to analyze associations between PACKRAT® scores and PANCE scores/low PANCE performance.
  • Likelihood ratio tests assessed inter-program variability and effect modification by demographic/socioeconomic factors.
  • Receiver operating characteristic (ROC) curves evaluated the diagnostic accuracy of various PACKRAT® metrics and cut points.

Main Results:

  • The PACKRAT® composite score demonstrated the strongest association with higher PANCE scores and lower odds of low PANCE performance.
  • Significant variability in the predictive associations of PACKRAT® metrics was observed among the five programs studied.
  • No significant effect modification was found for any demographic or socioeconomic variables.

Conclusions:

  • The PACKRAT® composite score is a robust predictor of PANCE success, but its predictive power is not uniform across all physician assistant programs.
  • Program-specific factors appear to influence the PACKRAT®-PANCE relationship, highlighting the need for program-specific validation.
  • Demographic and socioeconomic variables do not significantly alter the predictive validity of the PACKRAT® in this cohort.