Premium
A Methodology for Using Workforce Data to Decide Which Specialties and States to Target for Graduate Medical Education Expansion
Author(s) -
Fraher Erin P.,
Knapton Andy,
Holmes George M.
Publication year - 2017
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.12649
Subject(s) - workforce , graduate medical education , certification , physician supply , specialty , census , workforce planning , economic shortage , health care , medical education , medicine , family medicine , economics , economic growth , accreditation , population , government (linguistics) , environmental health , linguistics , philosophy , management
Objective To outline a methodology for allocating graduate medical education ( GME ) training positions based on data from a workforce projection model. Data Sources 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 GMET rack survey. Design 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. Extraction Methods We use the model to identify shortages for 19 types of health care services provided by 35 specialties in 50 states. Principal Findings The new GME slots are allocated to nearly all specialties, but nine states and the District of Columbia do not receive any new positions. Conclusions 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.