title: Electronic medical records, nurse staffing, and nurse-sensitive patient outcomes: evidence from California hospitals, 1998-2007.
abstract: OBJECTIVE
  To estimate the effects of electronic medical records (EMR) implementation on medical-surgical acute unit costs, length of stay, nurse staffing levels, nursing skill mix, nurse cost per hour, and nurse-sensitive patient outcomes.
  
  
  METHODS
  Data on EMR implementation came from the 1998-2007 HIMSS Analytics Databases. Data on nurse staffing and patient outcomes came from the 1998-2007 Annual Financial Disclosure Reports and Patient Discharge Databases of the California Office of Statewide Health Planning and Development (OSHPD).
  
  
  METHODS
  Longitudinal analysis of an unbalanced panel of 326 short-term, general acute care hospitals in California. Marginal effects estimated using fixed effects (within-hospital) OLS regression.
  
  
  RESULTS
  EMR implementation was associated with 6-10 percent higher cost per discharge in medical-surgical acute units. EMR stage 2 increased registered nurse hours per patient day by 15-26 percent and reduced licensed vocational nurse cost per hour by 2-4 percent. EMR stage 3 was associated with 3-4 percent lower rates of in-hospital mortality for conditions.
  
  
  CONCLUSIONS
  Our results suggest that advanced EMR applications may increase hospital costs and nurse staffing levels, as well as increase complications and decrease mortality for some conditions. Contrary to expectation, we found no support for the proposition that EMR reduced length of stay or decreased the demand for nurses.
authors.affiliation: School of Health Management and Policy, W. P. Carey School of Business, Arizona State University, PO Box 874506, Tempe, AZ 85287-4506, USA. michael.furukawa@asu.edu
authors.forename: Michael F
authors.initials: MF
authors.lastname: Furukawa
authors.forename: T S
authors.initials: TS
authors.lastname: Raghu
authors.forename: Benjamin B M
authors.initials: BB
authors.lastname: Shao
mesh_terms: D002140:California; D016208:Databases, Factual / Q000706:statistics & numerical data; D004469:Economics, Hospital / Q000706:statistics & numerical data; D017048:Health Care Costs / Q000706:statistics & numerical data*; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D007902:Length of Stay; D008137:Longitudinal Studies; D016347:Medical Records Systems, Computerized / Q000191:economics / Q000706:statistics & numerical data*; D009741:Nursing Staff, Hospital / Q000191:economics / Q000706:statistics & numerical data / Q000600:supply & distribution*; D017063:Outcome Assessment, Health Care / Q000191:economics / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data; D012044:Regression Analysis; D013503:Surgery Department, Hospital / Q000191:economics / Q000706:statistics & numerical data; D013997:Time Factors
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