This study aimed to review the literature describing and quantifying time lags in the health research translation process. Papers were included in the review if they quantified time lags in the development of health interventions. The study identified 23 papers. Few were comparable as different studies use different measures, of different things, at different time points. We concluded that the current state of knowledge of time lags is of limited use to those responsible for R&D and knowledge transfer who face difficulties in knowing what they should or can do to reduce time lags. This effectively ‘blindfolds’ investment decisions and risks wasting effort. The study concludes that understanding lags first requires agreeing models, definitions and measures, which can be applied in practice. A second task would be to develop a process by which to gather these data.

Background Public involvement in health-care policy has been advocated as a means to enhance health system responsiveness, yet evidence for its impact has been difficult to ascertain.

BackgroundEnd-of-life care policy has a focus on enabling patients to die in their preferred place; this is believed for most to be home. This review assesses patient preferences for place of death examining: the extent of unreported preferences, the importance of patient factors (place of care and health diagnosis) and who reports preferences.Methods and FindingsSystematic literature review of 7 electronic databases, grey literature, backwards citations from included studies and Palliative Medicine hand search. Included studies published between 2000–2015, reporting original, quantifiable results of adult UK preferences for place of death. Of 10826 articles reviewed, 61 met the inclusion criteria. Summary charts present preferences for place of death by health diagnosis, where patients were asked and who reported the preference. These charts are recalculated to include ‘missing data,’ the views of those whose preferences were not asked, expressed or reported or absent in studies. Missing data were common. Across all health conditions when missing data were excluded the majority preference was for home: when missing data were included, it was not known what proportion of patients with cancer, non-cancer or multiple conditions preferred home. Patients, family proxies and public all expressed a majority preference for home when missing data were excluded: when included, it was not known what proportion of patients or family proxies preferred home. Where patients wished to die was related to where they were asked their preference. Missing data calculations are limited to ‘reported’ data.ConclusionsIt is unknown what proportion of patients prefers to die at home or elsewhere. Reported preferences for place of death often exclude the views of those with no preference or not asked: when ‘missing data’ are included, they supress the proportion of preferences for all locations. Caution should be exercised if asserting that most patients prefer to die at home.

We believe that it is important to make the various process modelling methods more easily accessible to health care by providing clear guidelines or computer-based tool support for health care-specific process modelling. These supports can assist health care workers to apply initially unfamiliar, but eventually more effective modelling methods.

This article reviews the small literature on how to interview elites. It examines the veracity of three sets of assumptions embedded in the literature: about the nature of truth; dishonest respondents; and sophisticated but powerless researchers. It suggests ways forward, including ensuring that researchers place their work in more explicit philosophical and reflexive frameworks. This would result in more rigorous research and improved pedagogy.

While current evidence is poor, this does not justify maintaining current practice which risks lives. Building up an evidence base is critical, but requires agreed definitions, measures and methods, which can be applied to systematic evaluation of plausible solutions.

Collaborations between managers and researchers can improve research relevance and quality and research capacity development. Factors critical to success relate to the fit between the project and the management fellow and how clearly the purpose is understood.

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