title: Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.
abstract: BACKGROUND
  Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking.
  
  
  METHODS
  With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development.
  
  
  RESULTS
  The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD).
  
  
  CONCLUSIONS
  This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.
authors.affiliation: *Yale New Haven Health Services Corporation-Center for Outcomes Research and Evaluation †Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT ‡American Heart Association, Quality and Health IT §Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX ∥Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Yale University School of Medicine ¶Department of Health Policy and Management, Yale School of Public Health #Section of General Internal Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT.
authors.forename: Robert L
authors.initials: RL
authors.lastname: McNamara
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Wang
authors.forename: Chohreh
authors.initials: C
authors.lastname: Partovian
authors.forename: Julia
authors.initials: J
authors.lastname: Montague
authors.forename: Purav
authors.initials: P
authors.lastname: Mody
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Eddy
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
authors.forename: Susannah M
authors.initials: SM
authors.lastname: Bernheim
mesh_terms: D000368:Aged; D014487:Centers for Medicare and Medicaid Services, U.S.; D057286:Electronic Health Records; D005260:Female; D017052:Hospital Mortality; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007345:Insurance Claim Review; D008297:Male; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000401:mortality* / Q000628:therapy*; D017063:Outcome Assessment, Health Care; D058996:Quality Improvement; D012042:Registries; D018570:Risk Assessment; D014481:United States