Non-native English-speaking applicants and the likelihood of physician assistant program matriculation.

PURPOSE: Effective communication is critical in patient care. Multilingual medical providers, including Physician Assistants (PAs) can contribute to improved health care among patients with limited English proficiency; however, this is contingent upon matriculating multilingual providers. In this study, the association between prospective applicants' self-reported English as second language (ESL) status and their likelihood of matriculation into a PA program was investigated. METHODS: Participants included applicants to five admission cycles of the Centralized Application Service for Physician Assistant from 2012 to 2020. Logistic regression was utilized to investigate association between applicant ESL status and odds of program matriculation in both bivariate and multivariable regression models. Models were adjusted for citizenship status, undergraduate grade point average, gender, age, race/ethnicity, number of programs applied to, and patient care hours. RESULTS: In unadjusted and adjusted models, ESL status was associated with a significantly lower odds of matriculation to a PA program across all study years. In adjusted multivariable models, associations were strongest for 2014-2015 where ESL status was associated with a 35% lower odds of matriculation (odds ratio 0.65, 95% confidence interval 0.56, 0.76) when controlling for demographics, citizenship status, patient care experience, and academic achievement. In sensitivity analyses restricting to (a) those with TOEFL scores ≥ 100, and (b) restricting to those ESL applicants without TOEFL scores, we did not observe important changes in our results. CONCLUSIONS: Results indicated that non-native English-speaking applicants have lower odds of PA program matriculation. Decrements in matriculation odds were large magnitude, minimally impacted by adjustment for confounders and persistent across the years. These findings suggest that PA program admission processes may disadvantage non-native English-speaking applicants. While there are potential explanations for the observed findings, they are cause for concern. Matriculating and training PAs who have language concordance with underserved populations are important means of improving patient outcomes.

Military Veteran Matriculation in US Physician Associate/Assistant Programs.

INTRODUCTION: This study aims to determine whether veterans have differential access to physician associate/assistant (PA) education by examining likelihood of matriculation relative to nonveteran peers. We explore associations between veteran status and likelihood of matriculation for change over time and whether effects differ among active duty versus non-active-duty applicants. METHODS: Multivariate logistic regression was used to investigate associations between self-identified military status and likelihood of PA program matriculation in five Centralized Applicant Services for Physician Assistants admissions cycles (2012-2013, 2014-2015, 2016-2017, 2018-2019, 2020-2021). Models controlled for age, sex, race/ethnicity, patient care experience hours, total undergraduate grade point average, and number of applications submitted and applied a Bonferroni correction for alpha inflation. RESULTS: Veteran applicant numbers were small across the study time frame but increased from 2012 (n = 708) to 2020 (n = 978), representing a 38% increase over the lookback period. Despite growth, the proportion of veterans in the matriculant pool has decreased from 4.2% in 2012 to 3.0% in 2020. In unadjusted models, military status was not strongly associated with odds of matriculation. In adjusted models, both veteran and active-duty status were associated with higher odds of matriculation, although this increase was not statistically significant at the 0.005 level for applicants on active-duty. DISCUSSION: Military veterans and active-duty military personnel have higher likelihood of matriculation into US PA programs relative to nonveteran peers. The proportion of veterans in the matriculant pool has decreased over time. This suggests that while PA programs seems to value previous military experience, further efforts to evaluate and address barriers to military veterans in applying for admissions is needed.

Professionalism in Physician Assistant Education as a Predictor of Future Licensing Board Disciplinary Actions.

PURPOSE: The purpose of this study was to evaluate associations between postgraduate disciplinary actions (PGDA) by state licensing boards and physician assistant (PA) school documented professionalism violations (DPV) and academic probation. METHODS: This was a retrospective cohort study comprising PA graduates from 2001 to 2011 at 3 institutions (n = 1364) who were evaluated for the main outcome of PGDA and independent variable of DPV and academic probation. Random-effects multiple logistic regression and accelerated failure time parametric survival analysis were used to investigate the association of PGDA with DPV and academic probation. RESULTS: Postgraduate disciplinary action was statistically significant and positively associated with DPV when unadjusted (odds ratio [OR] = 5.15; 95% CI: 1.62-16.31; P = .01) and when adjusting for age, sex, overall PA program GPA (GPA), and Physician Assistant National Certifying Exam Score (OR = 5.39; 95% CI: 1.54-18.85; P = .01) (fully adjusted). Academic probation increased odds to 8.43 times (95% CI: 2.85-24.92; P < .001) and 9.52 times (95% CI: 2.38-38.01; P < .001) when fully adjusted. CONCLUSION: Students with professionalism violation or academic probation while in the PA school had significant higher odds of receiving licensing board disciplinary action compared with those who did not. Academic probation had a greater magnitude of effect and could represent an intersection of professionalism and academic performance.

Implicit Association Test Alone Is Not Sufficient to Increase Underrepresented Minority Representation in Physician Assistant Programs.

PURPOSE: Physician assistant (PA) program matriculants are consistently less diverse than the US population. This study evaluates whether administration of an Implicit Association Test (IAT) to PA program admission committees is associated with changes in the likelihood of (1) receiving an admission interview, (2) receiving an offer of admission, and (3) matriculation of individuals underrepresented in medicine (URiM). METHODS: Admission committees from 4 PA programs participated in an IAT before the 2019/2020 admissions cycle. Applicant outcome data (n = 5796) were compared with 2018/2019 cycle (n = 6346). Likelihood of URiM students receiving offers to interview, offers of admission, and matriculation were evaluated using random effects multiple logistic regression models. Fully adjusted random effects models included URiM status, year (control vs. intervention), multiplicative interaction terms between URiM and year, applicant age, and undergraduate grade point average (GPA) Secondary analyses examined associations of each race/ethnicity individually. RESULTS: Underrepresented in medicine status, age, and GPA were significantly associated with all admission outcomes ( P < .05). The intervention effect was not statistically significant. In sensitivity analyses examining each individual race rather than URiM status, our results did not importantly differ. CONCLUSION: Findings suggest admission committee member participation in IAT before admissions had no significant impact on the likelihood of admission of URiM students. This may suggest that making individuals aware of their implicit biases is not, in and of itself, sufficient to meaningfully affect the diversity of PA program admission metrics.

PA applicant U.S. citizenship status and likelihood of program matriculation.

BACKGROUND: Barriers to matriculation into Physician Assistant (PA) programs and entry into the PA profession have disproportionate impact on historically marginalized groups. This study evaluates if U.S. citizenship status is associated with likelihood of matriculation in PA Programs. METHODS: Data from five Centralized Applicant Services for Physician Assistants (CASPA) admissions cycles (2012-2021) was evaluated cross-sectionally for the primary outcome of binary matriculation status (yes/no). Bivariate and multivariate logistic regression was utilized to investigate associations between self-identified U.S. citizenship status and likelihood of PA program matriculation. Models controlled for important potential confounders, including age, gender, race/ethnicity, non-native English speaker, patient care experience hours, total undergraduate grade point average (GPA), and number of applications submitted to various programs. RESULTS: Non-U.S. citizen status was statistically associated with persistent lower likelihood of PA program matriculation compared to U.S. citizenship. Odds of matriculation were 41% [OR 0.59 (95% CI: 0.51, 0.68; p <.001)] to 51% [OR 0.49 (95% CI: 0.41, 0.58; p <.001)] lower in unadjusted models. Odds were 32% [OR 0.68 (95% CI: 0.56, 0.83; p <.001)] to 42% OR 0.58 (95% CI: 0.48, 0.71; p <.001) lower when adjusting for important covariates. The lowest likelihood occurred in 2012-2013 with 51% lower odds of matriculation and in 2016-2017 with 42% lower odds when accounting for important covariates. DISCUSSION: PA programs are charged with improving diversity of clinically practicing PAs to improve health outcomes and better reflect patient populations. This analysis shows that non-U.S. citizenship may be a barrier to PA school acceptance. PA schools should raise awareness and create means and accessibility for admissions for this underrepresented group.

Validation of a Novel Statistical Method to Identify Aberrant Patient Logging: A Multi-Institutional Study.

INTRODUCTION: Student patient encounter logging informs the quality of supervised clinical practice experiences (SCPEs). Yet, it is unknown whether logs accurately reflect patient encounters, and the faculty resources necessary to review for potential aberrant logging are significant. The purpose of this study was to identify a statistical method to identify aberrant logging. METHODS: A multi-institutional (n = 6) study examined a statistical method for identifying potentially aberrant logging behavior. An automated statistical Mahalanobis Distance (MD) measurement was used to categorize student logs as aberrant if they were identified as probable multivariate outliers. This approach was validated using a gold standard for aberrant logging behavior with manual review by 4 experienced faculty ("faculty consensus") and then comparing interrater agreement between faculty and MD-based categorization. In secondary analyses, we compared the relative accuracy of MD-based categorization to individual faculty categorizing data from their own program ("own program" categorization). RESULTS: 323 student logging records from 6 physician assistant (PA) programs were included. Compared to "faculty consensus" (the gold standard), MD-based categorization was highly sensitive (0.846, 95% CI: 0.650, 1.000) and specific (0.766, 95% CI: 0.645, 0.887). Additionally, there was no significant difference in sensitivity, specificity, positive predictive value, or negative predictive value between MD-based categorization and "own program" categorization. DISCUSSION: The MD-based method of identifying aberrant and nonaberrant student logging compared favorably to the more traditional, faculty-intensive approach of reviewing individual student logging records. This supports MD-based screening as a less labor-intensive alternative to individual faculty review to identify aberrant logging. Identification of aberrant logging may facilitate early intervention with students to improve clinical exposure logging during their SCPEs.

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

PURPOSE: The Physician Assistant Clinical Knowledge Rating and Assessment Tool (PACKRAT®) is a known predictor of performance on the Physician Assistant National Certifying Exam (PANCE). It is unknown, however, whether these associations (1) vary across programs; (2) differ by PACKRAT metrics (first-year [PACKRAT 1], second-year [PACKRAT 2], and composite score [arithmetic mean of PACKRAT 1 and PACKRAT 2]); or (3) are modified by demographic or socioeconomic variables. METHODS: 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. Likelihood ratio tests were used to evaluate differences in associations between programs and effect modification by 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. Models were adjusted for demographic and socioeconomic variables. The PACKRAT scores were standardized for each year to the national mean and SD. RESULTS: Adjusted 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 [CI]: 19-26) increase in PANCE score. The composite score also strongly predicted decrements in odds of LPP (odds ratio: 0.46; 95% CI: 0.38-0.55). Hierarchical regression models and ROC curves identified significant variability in associations among programs. Effect modification was not observed by any investigated variable. CONCLUSIONS: The composite score had the largest magnitudes of association with PANCE scores and odds of LPP. The significant difference in association identified between programs suggests that the predictive ability of the exam is not uniform. The lack of effect modification by demographic and socioeconomic variables suggests that associations do not significantly differ by these metrics.