This meta-review is the first of meta-analyses of HF disease management programs and conveys the challenges of performing meta-analyses of complex health services interventions. Overall, quality of the reviews was moderate though very mixed across reviews - this quality is important to consider when deciding whether review findings should guide practice and guidelines [22, 41, 42].
Based on the consistency and size of effect sizes identified by the meta-analyses, it would immediately appear reasonable to conclude either that, in generality, programs work or that programs of various types work . However, this meta-review supports concerns that populations, programs, and analyses of these programs are inconsistently and poorly described [44, 45]. For example, studies were poorly described in terms of populations and treatments with only one-fifth of reviews defining programs comprehensively in terms of approach, personnel, setting, and content. Even with the use of operationalised definitions to guide study selection in reviews, findings from interventions with very diverse characteristics and populations were pooled and, though mentioned in reviews, the implications of trial quality or statistical, clinical or methodological heterogeneity were seldom actually taken into account in analyses. No progress over time was evident in quality of reporting. Hence, reviews continue to focus on the results of study pooling over issues related to program complexity and heterogeneity.
Why might program complexity and heterogeneity be comparatively neglected in comparison to the findings of reviews? Firstly, this emphasis is understandable due to limitations in methodology. Complex interventions are often poorly described in published manuscripts  and it is well known that HF disease management programs are complex and diverse [43, 45, 47]. Current statistical and methodological techniques to describe and analyse such interventions in systematic review remain rudimentary . Current meta-analyses also predate the existence of a taxonomy to classify HF disease management programs  and more extensive CONSORT reporting requirements for non-pharmacological trials .
Secondly, scientific findings that are more positive are more likely to be published in higher impact journals and cited more often in guidelines [50, 51]. This reduces incentives to qualify results to take account of 'messy' issues related to program diversity and heterogeneity and fosters a disproportionate emphasis on positive findings without qualification  or recognition of how elements of context may moderate intervention effects . This tendency may be combined with a wider perceived political need to champion multi-disciplinary health services interventions to attain greater recognition and usage of such interventions in healthcare systems seen to favour pharmacological interventions and biomedicine .
However, paradoxically, ignoring complexity and heterogeneity may actually reduce knowledge translation. This follows because uptake is likely to be reduced by unclear descriptions of what programs and comparison groups consist of, lack of clarity over likely benefits in important patient groups (for example: the effects of both age and sex on program outcomes are not known), and lack of specificity in findings regarding key program characteristics [16, 53].
In future reviews, programs should be described comprehensively using systematic classification methods . More sophisticated taxonomies are needed to fully capture the deeper characteristics of programs . These should be used in future reviews to describe programs comprehensively and the effects of clinical, methodological, and statistical heterogeneity - as per PRISMA guidelines - must be formally taken into account in methods and conclusions . Future trials should report key elements of populations, interventions, comparison group, and outcomes in accordance with the modified CONSORT statement for non-pharmacological trials . These factors should be incorporated and reported comprehensively in meta-analyses. Findings from meta-analyses should be evaluated prior to application to practice and policy with review quality being assessed using valid quality criteria .
In terms of limitations, as with any review, this meta-review was constrained by the quality of reporting of the component studies. The data presented here are descriptive because it was inappropriate to synthesise outcomes to generate pooled effect sizes due to the wide diversity of programs subsumed in the reviews and the lack of comprehensive reporting in the reviews of intervention, comparator groups, and population characteristics [55, 56]. As pivotal elements of programs, reporting of these components has to be clear and comprehensive if synthesis is to be undertaken.