Data driven decision-making in a DPT program: In search of excellence in physical therapy education.
The purpose of our study is to determine the association between first time score on the National Physical Therapy Examination (NPTE) and several predictor variables including admission data and first year DPT course performance. Our goal is to create a framework for making data-driven decisions in admissions and curriculum design as part of our continued program assessment.
Internal review of a DPT program can be an overwhelming initiative, but is important, particularly for the purposes of identifying “markers” of the first measure of professional success, i.e. NPTE score on the first attempt. Cook et al. found that the only program characteristic associated with three year NPTE pass rate was mean undergraduate GPA.1 Mohr and colleagues reported that accreditation status, number and type of doctorally prepared faculty and years of professional academic preparation were the best predictors of licensure pass rate.2 GPA, reported in various forms (eg, mean undergraduate, core course science, first year professional) have been found to be one of the most consistent variables associated with success on the NPTE.1,3 GPA is commonly used as a quantitative data point used in the physical therapy program admission criteria.4 However, this data point alone falls short in the comprehensive understanding of program excellence.
A dataset was created containing 16 variables including GRE scores, undergraduate GPAs and predictors related to performance within the first year of the DPT Program, including first term GPA, and course grades for 12 first year courses. Predictor variables were tested for association to first-time NPTE test score in a simple linear regression; we report here on data from a single graduate cohort, however analysis will be extended across 5 DPT cohorts. Significance was assessed via p-value on the primary predictor variable (course grade or admission criterion).
Several courses were found to yield significant association to the first-time pass score at the P<0.05 level. Interestingly, the courses with weakest association (P<0.05) were all laboratory-based classes, while the lecture-based classes all showed stronger association, either at P<0.01 (PT Exam and Intervention Skills, Neuroscience), or P<0.001 (Gross Anatomy, Kinesiology, Pathophysiology I, Musculoskeletal Dysfunction I + II). <span style="line-height:1.6">Separately, we cross-correlated course performance in pairwise comparisons across the curriculum. There was modest between-course correlation: p = 0.47±0.19, meaning that student performance in one course is moderately predictive of performance in another course.3</span>
Conclusions/Relevance to the conference theme: The Pursuit of Excellence in Physical Therapy Education
Outcome assessment is critical to programmatic and student success. In our pursuit of excellence in physical therapy education, we strive to make the best decisions related to the admission of students to the program, in-program requirements, and program curriculum.
1. Cook C, Engelhard C, Landry MD, McCallum C. Modifiable variables in physical therapy education programs associated with first-time and three-year National Physical Therapy Examination pass rates in the United States. J Educ Eval Health Prof. 2015;12:44. doi:10.3352/jeehp.2015.12.44.
2. Mohr T, Ingram D, Hayes S, Zuru D. Educational Program Characteristics and Pass Rates on the National Physical Therapy Examination. J Phys Ther Educ. 2005; 19(1):60-66.
3. Dockter M. An analysis of physical therapy preadmission factors on academic success and success on the national licensing examination. J Phys Ther Educ. 2001;19(2):52–56.
4. Jewell DV., Riddle DL. A method for predicting a student’s risk for academic probation in a professional program in allied health. J Allied Health. 2005;34(1):17–23.