title: Predicting In-State Workforce Retention After Graduate Medical Education Training.
abstract: BACKGROUND
  There is a paucity of literature when it comes to identifying predictors of in-state retention of graduate medical education (GME) graduates, such as the demographic and educational characteristics of these physicians.
  
  
  OBJECTIVE
  The purpose was to use demographic and educational predictors to identify graduates from a single Michigan GME sponsoring institution, who are also likely to practice medicine in Michigan post-GME training.
  
  
  METHODS
  We included all residents and fellows who graduated between 2000 and 2014 from 1 of 18 GME programs at a Michigan-based sponsoring institution. Predictor variables identified by logistic regression with cross-validation were used to create a scoring tool to determine the likelihood of a GME graduate to practice medicine in the same state post-GME training.
  
  
  RESULTS
  A 6-variable model, which included 714 observations, was identified. The predictor variables were birth state, program type (primary care versus non-primary care), undergraduate degree location, medical school location, state in which GME training was completed, and marital status. The positive likelihood ratio (+LR) for the scoring tool was 5.31, while the negative likelihood ratio (-LR) was 0.46, with an accuracy of 74%.
  
  
  CONCLUSIONS
  The +LR indicates that the scoring tool was useful in predicting whether graduates who trained in a Michigan-based GME sponsoring institution were likely to practice medicine in Michigan following training. Other institutions could use these techniques to identify key information that could help pinpoint matriculating residents/fellows likely to practice medicine within the state in which they completed their training.
authors.forename: Tracy J
authors.initials: TJ
authors.lastname: Koehler
authors.forename: Jaclyn
authors.initials: J
authors.lastname: Goodfellow
authors.forename: Alan T
authors.initials: AT
authors.lastname: Davis
authors.forename: Jessaca
authors.initials: J
authors.lastname: Spybrook
authors.forename: John E
authors.initials: JE
authors.lastname: vanSchagen
authors.forename: Lori
authors.initials: L
authors.lastname: Schuh
mesh_terms: D004503:Education, Medical, Graduate / Q000706:statistics & numerical data*; D005257:Fellowships and Scholarships / Q000706:statistics & numerical data; D005260:Female; D005550:Foreign Medical Graduates / Q000706:statistics & numerical data; D006801:Humans; D007396:Internship and Residency / Q000706:statistics & numerical data*; D008297:Male; D008824:Michigan; D010820:Physicians / Q000600:supply & distribution*