The effectiveness of chronic care management for heart failure: meta-regression analyses to explain the heterogeneity in outcomes

Health Serv Res. 2012 Oct;47(5):1926-59. doi: 10.1111/j.1475-6773.2012.01396.x. Epub 2012 Mar 14.

Abstract

Objective: To support decision making on how to best redesign chronic care by studying the heterogeneity in effectiveness across chronic care management evaluations for heart failure.

Data sources: Reviews and primary studies that evaluated chronic care management interventions.

Study design: A systematic review including meta-regression analyses to investigate three potential sources of heterogeneity in effectiveness: study quality, length of follow-up, and number of chronic care model components.

Principal findings: Our meta-analysis showed that chronic care management reduces mortality by a mean of 18 percent (95 percent CI: 0.72-0.94) and hospitalization by a mean of 18 percent (95 percent CI: 0.76-0.93) and improves quality of life by 7.14 points (95 percent CI: -9.55 to -4.72) on the Minnesota Living with Heart Failure questionnaire. We could not explain the considerable differences in hospitalization and quality of life across the studies.

Conclusion: Chronic care management significantly reduces mortality. Positive effects on hospitalization and quality of life were shown, however, with substantial heterogeneity in effectiveness. This heterogeneity is not explained by study quality, length of follow-up, or the number of chronic care model components. More attention to the development and implementation of chronic care management is needed to support informed decision making on how to best redesign chronic care.

Publication types

  • Meta-Analysis
  • Review
  • Systematic Review

MeSH terms

  • Heart Failure / mortality
  • Heart Failure / therapy*
  • Hospitalization / statistics & numerical data
  • Humans
  • Long-Term Care / standards*
  • Long-Term Care / statistics & numerical data
  • Outcome and Process Assessment, Health Care / standards
  • Outcome and Process Assessment, Health Care / statistics & numerical data
  • Quality of Life
  • Regression Analysis
  • Treatment Outcome