title: Using electronic prescribing transaction data to estimate electronic health record adoption.
abstract: OBJECTIVE
  To determine whether electronic prescribing transaction data can be used to accurately and efficiently track national and regional electronic health record (EHR) adoption in order to evaluate progress toward national goals and identify and address regional disparities.
  
  
  METHODS
  This study compared national EHR use estimates derived from Surescripts electronic prescribing data for 2007 and 2008 with contemporary National Ambulatory Medical Care Survey (NAMCS) estimates.
  
  
  METHODS
  The ratio of relative risks was adapted to test the statistical significance of the difference in the differences between Surescripts and NAMCS estimates in 2007 and 2008.
  
  
  RESULTS
  In 2007, the relative ratio (RR) of NAMCS to Surescripts data was 3.73 (95% confidence interval [CI] = 3.27, 4.26). In 2008, the RR was 2.06 (95% CI = 1.75, 2.42). The ratio of RRs for 2007 compared with 2008 was 1.81 (P <.0001), suggesting that Surescripts transactional data for providers prescribing through an EHR is becoming better aligned with accepted measures of EHR adoption in the United States with time. Surescripts-derived state estimates for EHR use ranged from less than 8% (North Dakota, New Jersey, New Mexico) to more than 37% (Minnesota, Wisconsin, Massachusetts, Iowa).
  
  
  CONCLUSIONS
  Surescripts transactional data may allow for the ongoing identification of regional trends and assist policy makers in identifying and mitigating emerging disparities in EHR adoption. Further analysis is needed to ensure that Surescripts data continue to correlate with NAMCS results for 2009-2010.
authors.affiliation: Duke University School of Medicine, Durham, NC 27701, USA. erm@duke.edu
authors.forename: Emily Ruth
authors.initials: ER
authors.lastname: Maxson
authors.forename: Melinda J Beeuwkes
authors.initials: MJ
authors.lastname: Buntin
authors.forename: Farzad
authors.initials: F
authors.lastname: Mostashari
mesh_terms: D004059:Diffusion of Innovation; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D055695:Electronic Prescribing / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D006801:Humans; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data; D012306:Risk; D014481:United States