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.
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.
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).
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.
*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
Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website, www.lww-medicalcare.com.
The analyses on which this publication is based were performed under Contract Number Contract # HHSM-500-2008-00025I/HHSM-500-T0001, Modification No. 000007, funded by the Centers for Medicare & Medicaid Services, an agency of the US Department of Health and Human Services. The authors assume full responsibility for the accuracy and completeness of the ideas presented. The views expressed in this manuscript represent those of the authors. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. In addition, the views expressed in the manuscript do not necessarily represent the official views of the American College of Cardiology Foundation or the American Heart Association. This manuscript represents work performed under a contract from the Centers for Medicare and Medicaid Services.
R.L.M.: salary American Heart Association (major); endpoint adjudication committee Pfizer (minor). The remaining authors declare no conflict of interest.
Reprints: Robert L. McNamara, MD, MHS, Yale University School of Medicine, P.O. Box 208017, New Haven, CT 06520-8017. E-mail: firstname.lastname@example.org.