Policy-makers and managers have always used a wide range of sources of evidence in making decisions about policy and the organization of services. However, they are under increasing pressure to adopt a more systematic approach to the utilization of the complex evidence base. Decision-makers must address complicated questions about the nature and significance of the problem to be addressed; the nature of proposed interventions; their differential impact; cost-effectiveness; acceptability and so on. This means that Cochrane-style reviews alone are not sufficient. Rather, they require access to syntheses of high-quality evidence that include research and non-research sources, and both qualitative and quantitative research findings. There is no single, agreed framework for synthesizing such diverse forms of evidence and many of the approaches potentially applicable to such an endeavour were devised for either qualitative or quantitative synthesis and/or for analysing primary data. This paper describes the key stages in reviewing and synthesizing qualitative and quantitative evidence for decision-making and looks at various strategies that could offer a way forward. We identify four basic approaches: narrative (including traditional ‘literature reviews’ and more methodologically explicit approaches such as ‘thematic analysis’, ‘narrative synthesis’, ‘realist synthesis’ and ‘meta-narrative mapping’), qualitative (which convert all available evidence into qualitative form using techniques such as ‘meta-ethnography’ and ‘qualitative cross-case analysis’), quantitative (which convert all evidence into quantitative form using techniques such as‘quantitative case survey’ or ‘content analysis’) and Bayesian meta-analysis and decision analysis (which can convert qualitative evidence such as preferences about different outcomes into quantitative form or ‘weights’ to use in quantitative synthesis). The choice of approach will be contingent on the aim of the review and nature of the available evidence, and often more than one approach will be required.

The objective was to assess the impact of new guidance on the conduct of narrative synthesis in systematic reviews of effectiveness, by means of a blinded comparison of guidance-led narrative synthesis against a meta-analysis of the same study data.The conclusions of the two syntheses were broadly similar. However, differences between the approaches meant that conclusions about the impact of moderators of effect appeared stronger when derived from the meta-analysis, whereas implications for future research appeared more extensive when derived from the narrative synthesis. These findings emphasize that a rigorously conducted narrative synthesis can add meaning and value to the findings of meta-analysis.The guidance framework provided a useful vehicle for structuring a narrative synthesis and increasing transparency and rigour of the process.While there may be risks with overinterpretation of study data, the framework, tools and techniques described in the guidance appear to increase the transparency and reproducibility of narrative synthesis.

Applying a complex systems perspective to public health evaluation may increase the relevance and strength of evidence to improve health and reduce health inequalities. In this review of methods, we aimed to: (i) classify and describe different complex systems methods in evaluation applied to public health; and (ii) examine the kinds of evaluative evidence generated by these different methods. We adapted critical review methods to identify evaluations of public health interventions that used systems methods. We conducted expert consultation, searched electronic databases (Scopus, MEDLINE, Web of Science), and followed citations of relevant systematic reviews. Evaluations were included if they self-identified as using systems- or complexity-informed methods and if they evaluated existing or hypothetical public health interventions. Case studies were selected to illustrate different types of complex systems evaluation. Seventy-four unique studies met our inclusion criteria. A framework was developed to map the included studies onto different stages of the evaluation process, which parallels the planning, delivery, assessment, and further delivery phases of the interventions they seek to inform; these stages include: 1) theorising; 2) prediction (simulation); 3) process evaluation; 4) impact evaluation; and 5) further prediction (simulation). Within this framework, we broadly categorised methodological approaches as mapping, modelling, network analysis and 'system framing' (the application of a complex systems perspective to a range of study designs). Studies frequently applied more than one type of systems method. A range of complex systems methods can be utilised, adapted, or combined to produce different types of evaluative evidence. Further methodological innovation in systems evaluation may generate stronger evidence to improve health and reduce health inequalities in our complex world.