Physician assistants and their intent to retire.

OBJECTIVES: To determine predictors of physician assistants (PAs) to retire or to permanently leave clinical practice. The intent was to create a measure of retention and attrition for purposes of forecasting PA supply. STUDY DESIGN: All PAs 55 years or older who were nationally certified in 2011 were surveyed. METHODS: Statistical analysis included descriptive measures utilizing means, standard deviations, range, and proportions for all survey questions. Univariable analysis using χ² test for the categorical variables determined gender differences in participants' intent to retire. A studentized t test analysis for continuous variables was used to compare differences across genders. The estimated time interval until retirement was calculated using reported values from participants and then subtracting their projected retirement age from current age. The same calculation was used for estimating PA career length from date of graduation to retirement. For all analyses, a P value < .05 was considered statistically significant. RESULTS: A total of 12,005 were eligible and surveyed online; 4767 responded (38%). The mean age was 60 years and the years in clinical practice was 25. When asked to predict a retirement date or age, the mean duration of working beyond age 55 years was 12 years (range 5 to 21). Most respondents reported being confident they were on track to retire with an adequate income. The significant differences that emerged were that men were more confident than women in preparing to retire, having enough money for medical expenses, and being able to live comfortably in retirement. Men more than women stated that, if forced to retire, they were more confident in the preparation to do so. CONCLUSIONS: PAs 55 years and older report they are likely to delay retirement from practice until age 67 years, on average. Women were less confident than men in retirement preparation. This age prediction expands career projections and refines forecasting models for the profession. Correlations based on expectation-action chain of events should be developed by periodically measuring how often intent and reality coalesce.