BackgroundThe effectiveness of many interventions to promote health and prevent disease has been well established. The imperative has therefore shifted from amassing evidence about efficacy to scale-up to maximise population-level health gains. Electronic implementation monitoring, or ‘e-monitoring’, systems have been designed to assist and track the delivery of preventive policies and programs. However, there is little evidence on whether e-monitoring systems improve the dissemination, adoption, and ongoing delivery of evidence-based preventive programs. Also, given considerable difficulties with e-monitoring systems in the clinical sector, scholars have called for a more sophisticated re-examination of e-monitoring’s role in enhancing implementation.MethodsIn the state of New South Wales (NSW), Australia, the Population Health Information Management System (PHIMS) was created to support the dissemination of obesity prevention programs to 6000 childcare centres and elementary schools across all 15 local health districts. We have established a three-way university-policymaker-practice research partnership to investigate the impact of PHIMS on practice, how PHIMS is used, and how achievement of key performance indicators of program adoption may be associated with local contextual factors. Our methods encompass ethnographic observation, key informant interviews and participatory workshops for data interpretation at a state and local level. We use an on-line social network analysis of the collaborative relationships across local health district health promotion teams to explore the relationship between PHIMS use and the organisational structure of practice.DiscussionInsights will be sensitised by institutional theory, practice theory and complex adaptive system thinking, among other theories which make sense of socio-technical action. Our working hypothesis is that the science of getting evidence-based programs into practice rests on an in-depth understanding of the role they play in the on-going system of local relationships and multiple accountabilities. Data will be synthesised to produce a typology to characterise local context, PHIMS use and key performance indicator achievement (of program implementation) across the 15 local health districts. Results could be used to continuously align e-monitoring technologies within quality improvement processes to ensure that such technologies enhance practice and innovation. A partnership approach to knowledge production increases the likelihood that findings will be put into practice.
A number of ways to conduct research are designed to maximise the likelihood that evidence from research is quickly transferred into practice. This includes action research and partnership research between researchers and policy makers. Such approaches focus research effort on questions of highest relevance to practice and policy so as to create ownership of the results. However, such approaches on their own do not necessarily visualise or illuminate possible pathways of action or create a sense of personal connection to these possible actions. We describe a simple, creative, innovative device: production of co-authored mock (that is, fake) in-house abstracts of peer-reviewed papers as an aid in this process. The intent is to foster high-level engagement with possible project findings by policy makers and researchers involved in partnership research. This occurs in advance of knowing the real results of the study. The mock abstracts process described here occurs within a research-policy maker-practitioner partnership studying the scaling-up of childhood statewide obesity prevention programmes and the electronic monitoring system being used to track progress. The mock abstracts are a tool for identifying priority interests among a large data set. They act as a trigger to uncovering different interpretations of findings among the team. They foster discussion and mental rehearsal of actions based on different scenarios. And they help the team coordinate participation in the analysis and writing-up of the real findings. They also represent a hypothetical variety of research endpoints which assist with maintaining project momentum during long phases of analysis.<br /><br />key messages<br /><br /><ol><li>Mock abstracts with mock (fake) results can be written in advance of research findings.</li><br /><li>The purpose is to reduce the evidence-to-practice gap by rehearsing both interpretation and action.</li><br /><li>Mock abstracts can be used to illustrate the role of theory in interpreting research findings.</li><br /><li>Potentially sensitive findings can be defused by illustrating pathways to address problems.</li></ol><br />
Background Population-level health promotion is often conceived as a tension between “top-down” and “bottom-up” strategy and action. We report behind-the-scenes insights from Australia’s largest ever investment in the “top-down” approach, the $45m state-wide scale-up of two childhood obesity programmes. We used Normalisation Process Theory (NPT) as a template to interpret the organisational embedding of the purpose-built software designed to facilitate the initiative. The use of the technology was mandatory for evaluation, i.e. for reporting the proportion of schools and childcare centres which complied with recommended health practices (the implementation targets). Additionally, the software was recommended as a device to guide the implementation process. We set out to study its use in practice. Methods Short-term, high-intensity ethnography with all 14 programme delivery teams across New South Wales was conducted, cross-sectionally, 4 years after scale-up began. The four key mechanisms of NPT (coherence/sensemaking, cognitive participation/engagement, collective action and reflexive monitoring) were used to describe the ways the technology had normalised (embedded). Results Some teams and practitioners embraced how the software offered a way of working systematically with sites to encourage uptake of recommended practices, while others rejected it as a form of “mechanisation”. Conscious choices had to be made at an individual and team level about the practice style offered by the technology—thus prompting personal sensemaking, re-organisation of work, awareness of choices by others and reflexivity about professional values. Local organisational arrangements allowed technology users to enter data and assist the work of non-users—collective action that legitimised opposite behaviours. Thus, the technology and the programme delivery style it represented were normalised by pathways of adoption and non-adoption. Normalised use and non-use were accepted and different choices made by local programme managers were respected. State-wide, implementation targets are being reported as met. Conclusion We observed a form of self-organisation where individual practitioners and teams are finding their own place in a new system, consistent with complexity-based understandings of fostering scale-up in health care. Self-organisation could be facilitated with further cross-team interaction to continuously renew and revise sensemaking processes and support diverse adoption choices across different contexts.
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