title: Estimates of electronic medical records in U.S. Emergency departments.
abstract: BACKGROUND
  Policymakers advocate universal electronic medical records (EMRs) and propose incentives for "meaningful use" of EMRs. Though emergency departments (EDs) are particularly sensitive to the benefits and unintended consequences of EMR adoption, surveillance has been limited. We analyze data from a nationally representative sample of US EDs to ascertain the adoption of various EMR functionalities.
  
  
  RESULTS
  We analyzed data from the National Hospital Ambulatory Medical Care Survey, after pooling data from 2005 and 2006, reporting proportions with 95% confidence intervals (95% CI). In addition to reporting adoption of various EMR functionalities, we used logistic regression to ascertain patient and hospital characteristics predicting "meaningful use," defined as a "basic" system (managing demographic information, computerized provider order entry, and lab and imaging results). We found that 46% (95% CI 39-53%) of US EDs reported having adopted EMRs. Computerized provider order entry was present in 21% (95% CI 16-27%), and only 15% (95% CI 10-20%) had warnings for drug interactions or contraindications. The "basic" definition of "meaningful use" was met by 17% (95% CI 13-21%) of EDs. Rural EDs were substantially less likely to have a "basic" EMR system than urban EDs (odds ratio 0.19, 95% CI 0.06-0.57, p = 0.003), and Midwestern (odds ratio 0.37, 95% CI 0.16-0.84, p = 0.018) and Southern (odds ratio 0.47, 95% CI 0.26-0.84, p = 0.011) EDs were substantially less likely than Northeastern EDs to have a "basic" system.
  
  
  CONCLUSIONS
  EMRs are becoming more prevalent in US EDs, though only a minority use EMRs in a "meaningful" way, no matter how "meaningful" is defined. Rural EDs are less likely to have an EMR than metropolitan EDs, and Midwestern and Southern EDs are less likely to have an EMR than Northeastern EDs. We discuss the nuances of how to define "meaningful use," and the importance of considering not only adoption, but also full implementation and consequences.
authors.affiliation: Institute for Technology Assessment, Harvard Medical School, Boston, Massachusetts, United States of America. ben.geisler@gmail.com
authors.forename: Benjamin P
authors.initials: BP
authors.lastname: Geisler
authors.forename: Jeremiah D
authors.initials: JD
authors.lastname: Schuur
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Pallin
mesh_terms: D016001:Confidence Intervals; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D004630:Emergencies; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D019538:Health Care Surveys / Q000706:statistics & numerical data*; D006748:Hospital Departments; D006801:Humans; D016015:Logistic Models; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D015146:Midwestern United States; D009511:New England; D012423:Rural Health / Q000706:statistics & numerical data; D014481:United States; D014504:Urban Health / Q000706:statistics & numerical data