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Home Research Research Library Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions 2019 Author(s) Phillips, Julie P, Peterson, Lars E, Fang, Bo, Kovar-Gough, Iris, and Phillips, Robert L Topic(s) Education & Training, Role of Primary Care, and What Family Physicians Do Keyword(s) Graduate Medical Education, Imprinting Of Training, Practice Organization / Ownership, Shortage Areas, and Visiting Scholar/Fellow Volume Academic Medicine Source Academic Medicine Purpose: Educational debt is increasing and may affect physicians’ career choices. High debt may influence family medicine residents’ initial practice setting and fellowship training decisions, adversely affecting the distribution of primary care physicians. The purpose of this study was to determine whether debt was associated with graduating family medicine residents’ practice and fellowship intentions. Method: The authors completed a cross-sectional secondary analysis of 2014 and 2015 American Board of Family Medicine (ABFM) examination registration questionnaire data and ABFM administrative data. They used multivariate logistic regression to determine whether educational debt was associated with graduating residents’ practice (ownership and type) and fellowship intentions. Results: Most residents (89.7%; 3,368) intended to pursue an employed position, but this intention was not associated with their debt. Residents with high debt ($150,000-$249,999) had lower odds of intending to work for a government organization (odds ratio [OR] 0.57; confidence interval [CI] 0.41-0.79). Those with high or very high debt (> $250,000) had lower odds of choosing academic practice (OR 0.55, CI 0.36-0.85 and OR 0.62, CI 0.40-0.96, respectively) or a geriatrics fellowship (OR 0.36, CI 0.20-0.67 and OR 0.29, CI 0.15-0.55, respectively). Conclusions: High educational debt may contribute to national shortages of academic primary care physicians and geriatricians. Existing National Health Service Corps loan repayment opportunities may not offer adequate incentives to primary care physicians with high debt. The medical community should advocate for policies that better align financial incentives with workforce needs. ABFM Research Read all 2023 The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters Go to The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters 2017 Preserving Primary Care Robustness Despite Increasing Health System Integration Go to Preserving Primary Care Robustness Despite Increasing Health System Integration 2021 What Family Medicine Can Learn From Other Specialties Go to What Family Medicine Can Learn From Other Specialties 2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research
Author(s) Phillips, Julie P, Peterson, Lars E, Fang, Bo, Kovar-Gough, Iris, and Phillips, Robert L Topic(s) Education & Training, Role of Primary Care, and What Family Physicians Do Keyword(s) Graduate Medical Education, Imprinting Of Training, Practice Organization / Ownership, Shortage Areas, and Visiting Scholar/Fellow Volume Academic Medicine Source Academic Medicine
ABFM Research Read all 2023 The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters Go to The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters 2017 Preserving Primary Care Robustness Despite Increasing Health System Integration Go to Preserving Primary Care Robustness Despite Increasing Health System Integration 2021 What Family Medicine Can Learn From Other Specialties Go to What Family Medicine Can Learn From Other Specialties 2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research
2023 The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters Go to The Decline in Family Medicine in-Training Examination Scores: What We Know and Why It Matters
2017 Preserving Primary Care Robustness Despite Increasing Health System Integration Go to Preserving Primary Care Robustness Despite Increasing Health System Integration
2021 What Family Medicine Can Learn From Other Specialties Go to What Family Medicine Can Learn From Other Specialties
2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research