An increasing body of literature attempts to describe and validate hospital readmission risk prediction tools. Interest in such models has grown for two reasons. First, transitional care interventions may reduce readmissions among chronically ill adults. Readmission risk assessment could be used to help target the delivery of these resource-intensive interventions to the patients at greatest risk. Ideally, models designed for this purpose would provide clinically relevant stratification of readmission risk and give information early enough during the hospitalization to trigger a transitional care intervention, many of which involve discharge planning and begin well before hospital discharge. Second, there is interest in using readmission rates as a quality metric. Recently, the Centers for Medicare & Medicaid Services (CMS) began using readmission rate as a publicly reported metric, with plans to lower reimbursement to hospitals with excess risk-standardized readmission rates. Valid risk adjustment methods are required for calculation of risk-standardized readmission rates which could, in turn, be used for hospital comparison, public reporting, and reimbursement determinations. Models designed for these purposes should have good predictive ability; be deployable in large populations; use reliable data that can be easily obtained; and use variables that are clinically related to, and validated in, the populations in which use is intended.

This systematic review was performed to synthesize the available literature on validated readmission risk prediction models, describe their performance, and assess their suitability for clinical or administrative use.

Contents

• PREFACE
• EXECUTIVE SUMMARY
  • CONTEXT
  • OBJECTIVE
  • METHODS
  • RESULTS
  • CONCLUSIONS
• INTRODUCTION
• METHODS
  • DATA SOURCES AND SEARCHES
  • STUDY SELECTION
  • DATA EXTRACTION AND QUALITY ASSESSMENT
  • DATA SYNTHESIS
• RESULTS
  • Models Relying on Retrospective Administrative Data
  • Models Using Real-Time Administrative Data
  • Models Incorporating Primary Data Collection
  • Use of variables
  • Potentially preventable readmissions
• DISCUSSION
• REFERENCES
• APPENDIX A SEARCH STRATEGY
• APPENDIX B INCLUSION/EXCLUSION CRITERIA FOR REVIEW OF FULL-TEXT ARTICLES
• APPENDIX C STUDY QUALITY ASSESSMENT CRITERIA

Prepared for: Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development Service, Washington, DC 20420. Prepared by: Evidence-based Synthesis Program (ESP) Center, Portland VA Medical Center, Portland, OR, Devan Kansagara, M.D., M.C.R., Director

Suggested citation:

Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M and Kripalani S. Risk Prediction Models for Hospital Readmission: A Systematic Review. VA-ESP Project #05-225; 2011.

This report is based on research conducted by the Evidence-based Synthesis Program (ESP) Center located at the Portland VA Medical Center, Portland, OR funded by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Health Services Research and Development. The findings and conclusions in this document are those of the author(s) who are responsible for its contents; the findings and conclusions do not necessarily represent the views of the Department of Veterans Affairs or the United States government. Therefore, no statement in this article should be construed as an official position of the Department of Veterans Affairs. No investigators have any affiliations or financial involvement (e.g., employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties) that conflict with material presented in the report.