title: Rural EMR adoption rates overtake those in urban areas.
abstract: OBJECTIVE
  To assess rural-urban differences in electronic medical record (EMR) adoption among office-based physician practices in the United States.
  
  
  METHODS
  Survey data on over 270 000 office-based physician sites (representing over 1 280 000 physicians) in the United States from 2012 was used to assess differences in EMR adoption rates among practices in rural and urban areas. Logistic regression tests for differences in the determinants of EMR adoption by geography, and a nonlinear decomposition is used to quantify how much of the rural-urban gap is due to differences in measureable characteristics (such as type of practice or affiliation with a health system).
  
  
  RESULTS
  Overall EMR adoption rates were significantly higher for practices in rural areas (56%) vs those in urban areas (49%) in 2012 (P < 0.001). Twenty-nine states had statistically significantly different adoption rates between rural and urban areas, with only two states demonstrating higher rates in urban areas. EMR adoption continues to be higher for primary care practices when compared to specialists (51% vs 49%, P < 0.001), and state-level rural-urban differences in adoption are more pronounced for specialists. The decomposition technique finds that only 14% of the rural-urban gap can be explained by differences in measurable characteristics between practices.
  
  
  CONCLUSIONS
  At the national level, rates of EMR adoption are higher for rural practices than for their urban counterparts, reversing earlier trends. This suggests that outreach efforts, namely the Regional Extension Centers created by the Office of the National Coordinator, have been particularly effective in increasing EMR adoption in rural areas.
authors: Department of Agricultural Economics, Oklahoma State University 504 Ag Hall Stillwater, OK 74074, brian.whitacre@okstate.edu, (405) 744-9825.
authors: Brian E
authors: BE
authors: Whitacre
mesh_terms: D004059:Diffusion of Innovation; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D016015:Logistic Models; D017711:Nonlinear Dynamics; D011216:Practice Management, Medical / Q000706:statistics & numerical data*; D019035:Rural Health Services / Q000706:statistics & numerical data*; D014481:United States; D019037:Urban Health Services / Q000706:statistics & numerical data*
keywords: EMR adoption; Electronic Medical Records; decomposition; logistic regression; rural