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Open Access Research

A meta-review of evidence on heart failure disease management programs: the challenges of describing and synthesizing evidence on complex interventions

Lori A Savard1, David R Thompson2 and Alexander M Clark1*

Author Affiliations

1 University of Alberta, 3rdFloor, Clinical Sciences Building, Edmonton, AB, T6G 2G3, Canada

2 Department of Health Sciences and Department of Cardiovascular Sciences, University of Leicester, Leicester, LE1 6TP, UK

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Trials 2011, 12:194  doi:10.1186/1745-6215-12-194

Published: 16 August 2011

Abstract

Background

Despite favourable results from past meta-analyses, some recent large trials have not found Heart Failure (HF) disease management programs to be beneficial. To explore reasons for this, we evaluated evidence from existing meta-analyses.

Methods

Systematic review incorporating meta-review was used. We selected meta-analyses of randomized controlled trials published after 1995 in English that examined the effects of HF disease management programs on key outcomes. Databases searched: MEDLINE, EMBASE, Cochrane Database of Systematic Reviews (CDSR), DARE, NHS EED, NHS HTA, Ageline, AMED, Scopus, Web of Science and CINAHL; cited references, experts and existing reviews were also searched.

Results

15 meta-analyses were identified containing a mean of 18.5 randomized trials of HF interventions +/- 10.1 (range: 6 to 36). Overall quality of the meta-analyses was very mixed (Mean AMSTAR Score = 6.4 +/- 1.9; range 2-9). Reporting inadequacies were widespread around populations, intervention components, settings and characteristics, comparison, and comparator groups. Heterogeneity (statistical, clinical, and methodological) was not taken into account sufficiently when drawing conclusions from pooled analyses.

Conclusions

Meta-analyses of heart failure disease management programs have promising findings but often fail to report key characteristics of populations, interventions, and comparisons. Existing reviews are of mixed quality and do not adequately take account of program complexity and heterogeneity.