A model to predict NAPLEX outcomes and identify students needing additional preparation

Area of Science:

• Pharmacy Education
• Licensure Examination Outcomes
• Predictive Modeling in Health Professions

Background:

• Identifying predictors for North American Pharmacist Licensure Examination (NAPLEX) success is crucial for academic support.
• Existing predictive models lack practical, measurable, and reliable implementation in pharmacy academia.

Purpose of the Study:

• To develop a practical, measurable, and reliable predictive model for North American Pharmacist Licensure Examination (NAPLEX) outcomes.
• To identify key factors that accurately predict student performance on the NAPLEX.

Main Methods:

• A cohort of 2012-2016 pharmacy graduates with available first-attempt NAPLEX scores was analyzed.
• Linear and logistic regression identified independent predictors of poor NAPLEX performance (score ≤82).

Main Results:

• 16.2% of students (70/433) were identified as poor performers.
• Predictors included age >28, Pharmacy College Admission Test score <74, High Risk Drug Knowledge Assessment score <90, third-year Pharmacy Curriculum Outcome Assessment score <349, and <74 in >3 courses.
• Risk stratification into Low, Intermediate-1, Intermediate-2, and High groups showed mean NAPLEX scores of 106.4, 97.4, 87.1, and 75.1, respectively.

Conclusions:

• The developed model serves as a practical tool for identifying at-risk students before NAPLEX examination.
• Four of the five identified predictors demonstrate potential generalizability across different pharmacy schools.