title: A Methodology for Using Workforce Data to Decide Which Specialties and States to Target for Graduate Medical Education Expansion.
abstract: To outline a methodology for allocating graduate medical education (GME) training positions based on data from a workforce projection model.
  
  
  
  Demand for visits is derived from the Medical Expenditure Panel Survey and Census data. Physician supply, retirements, and geographic mobility are estimated using concatenated AMA Masterfiles and ABMS certification data. The number and specialization behaviors of residents are derived from the AAMC's GMETrack survey.
  
  
  
  We show how the methodology could be used to allocate 3,000 new GME slots over 5 years-15,000 total positions-by state and specialty to address workforce shortages in 2026.
  
  
  
  We use the model to identify shortages for 19 types of health care services provided by 35 specialties in 50 states.
  
  
  
  The new GME slots are allocated to nearly all specialties, but nine states and the District of Columbia do not receive any new positions.
  
  
  
  This analysis illustrates an objective, evidence-based methodology for allocating GME positions that could be used as the starting point for discussions about GME expansion or redistribution.
authors.affiliation: Cecil G. Sheps Center for Health Services Research and Department of Family Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
authors.forename: Erin P
authors.initials: EP
authors.lastname: Fraher
authors.affiliation: SMAP Limited, Winchester, UK.
authors.forename: Andy
authors.initials: A
authors.lastname: Knapton
authors.affiliation: Cecil G. Sheps Center for Health Services Research and the Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
authors.forename: George M
authors.identifier: 0000-0002-6169-7847
authors.initials: GM
authors.lastname: Holmes
mesh_terms: D004503:Education, Medical, Graduate / Q000706:statistics & numerical data* / Q000639:trends*; D005544:Forecasting; D005843:Geography; D006801:Humans; D010820:Physicians / Q000600:supply & distribution* / Q000639:trends*; D011365:Professional Practice Location / Q000706:statistics & numerical data* / Q000639:trends*; D013038:Specialization; D014481:United States
keywords: Health policy/politics/law/regulation; health workforce distribution/incomes/training; medicare