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Evidence-based policy-making is believed to produce higher quality policies and when it comes to child survival policy, the stakes are incredibly high: each year nearly 6 million children under 5 die, nearly all in low- and middle-income countries (LMICs), with the three leading causes of death being pneumonia (15% of deaths), diarrhea (9%), and malaria (7%) (Liu et al., 2012; You et al., 2015). To increase access to prompt and effective treatment of childhood illness, global-level policy-makers developed integrated community case management of childhood illness (iCCM), an evidence-based strategy to provide life-saving care for these three diseases (Young et al., 2012). To date, nearly all African countries have adopted some form of iCCM policy (Rasanathan et al., 2014). In recent years, calls have increased to move toward evidenceinformed decision-making in global health and public policy following observations in the 1990s and 2000s that policies did not reflect evidence as much as they could and that stores of useful research were going to waste (Davis and Howden-Chapman, 1996; Hanney et al., 2003; Lavis et al., 2002). Concurrently, new directions are emerging in the types of knowledge considered relevant to health policy making, with a growing consensus that earlier conceptions of evidence, defined “statistical inference about events in populations that are studied prospectively,” were too narrow and should be expanded to include observational and qualitative studies and health policy and systems research (HPSR) (Black, 2001; Fox, 2005; Sturm, 2002). However it is unclear the extent to which these recommendations, alongside global initiatives such as WHO’s Evidence-Informed Policy Network (EVIPNet) and Alliance for HPSR, among others, which produce policy briefs, research syntheses and analyses of policy options, have achieved the broader goal of informing health policy decision-makers in LMICs (Rosenbaum et al., 2011). Systematic reviews drawing mainly on studies from Western countries have identified numerous barriers to the use of evidence in policy-making, including nonexistent or low-quality evidence (Oliver et al., 2014a; Orton et al., 2011), lack of contact between policy-makers and researchers (Innvaer et al., 2002; Orton et al., 2011) and policy-makers’ insufficient research skills or awareness of research findings (Oliver et al., 2014a; Orton et al., 2011). Meanwhile the public health and public policy literature are just beginning to explore the use of evidence in policy-making in LMICs and identify specific challenges inherent to low-resource settings (Rodríguez et al., 2015b; Greenhalgh and Wieringa, 2011). While policy-makers in LMICs nearly universally cite evidence as being crucial to making good policy decisions (Burchett et al., 2012), existing studies tend to emphasize the under-use of relevant evidence or data to inform decision-making (Gupta et al., 2003) or specific barriers to using research, echoing the barriers noted above for Western countries but also including political, budgetary or bureaucratic obstacles (Aaserud et al., 2005; Mubyazi and Gonzalez-Block, 2005; Woelk et al., 2009). In addition to problems of under-investment in research, governments in LMICs also have fewer human resources to devote to policy development processes, quantitatively and often qualitatively, resulting in lesser capacity to assess evidence and incorporate it into policy (Ogundahunsi et al., 2015; Olivier de Sardan & Tidjani Alou, 2012). Existing theoretical and empirical work on evidence-based policy-making has focused, implicitly or explicitly, on uptake of peer-reviewed academic research evidence, a narrow definition of knowledge attributed to the rationalist epistemological stance found in evidence-based medicine. Whereas policy-makers themselves interpret “evidence” in a broader sense, including forms of knowledge beyond research evidence strictly construed (for example practical experience and tacit knowledge), the public health literature as yet mainly has not, leading to under-emphasis on sociological aspects of knowledge use in policy development and particularly the role of power (Greenhalgh and Wieringa, 2011; Oliver et al., 2014b). This is less true of relevant work coming out of other literature, such as sociology, where the contested meanings of “evidence-based policy” are frequently interrogated, for example around climate change policies (Pearce, 2014; Pearce et al., 2014), and in Science & Technology Studies, where theories of “co-production” have been proposed to examine how technical experts and society interact to produce knowledge, in ways that are inextricably linked to societal mechanisms of organization and control (Jasanoff, 2006). With such considerations in mind, analysts have called on researchers to adopt a critical perspective and examine power dynamics in the use of evidence in policy development in LMICs (Behague et al., 2009; Greenhalgh and Wieringa, 2011; Shiffman, 2014). Greenhalgh and Weiringa additionally propose using an Aristotelian view of knowledge or evidence with three components: episteme (facts or explicit knowledge, including notably research evidence), techne (skill or practice) and phronesis (situation-specific practical wisdom). Phronesis, perhaps the slipperiest concept, has traditionally been translated as “prudence,” and is sometimes defined as the ability to apply general rules to particular situations; it involves ethical and practical considerations about which ends to pursue (Montgomery, 2006). In this article we present a case study of the use of evidence in the policy development process for iCCM for child illness in Niger, a low-income West African country which historically has had among the world’s highest rate of child mortality and was one of the first African countries to adopt iCCM. Following Greenhalgh and Weiringa, we critically examine the three types of knowledge discussed above and explore how these were used during policy development, with a particular attention to power throughout the policy-making process. Finally, we summarize our findings, discuss lessons learned and suggest future directions for research on evidence-based policy making in LMICs.
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