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      How long does biomedical research take? Studying the time taken between biomedical and health research and its translation into products, policy, and practice

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          Abstract

          Background

          The time taken, or ‘time lags’, between biomedical/health research and its translation into health improvements is receiving growing attention. Reducing time lags should increase rates of return to such research. However, ways to measure time lags are under-developed, with little attention on where time lags arise within overall timelines. The process marker model has been proposed as a better way forward than the current focus on an increasingly complex series of translation ‘gaps’. Starting from that model, we aimed to develop better methods to measure and understand time lags and develop ways to identify policy options and produce recommendations for future studies.

          Methods

          Following reviews of the literature on time lags and of relevant policy documents, we developed a new approach to conduct case studies of time lags. We built on the process marker model, including developing a matrix with a series of overlapping tracks to allow us to present and measure elements within any overall time lag. We identified a reduced number of key markers or calibration points and tested our new approach in seven case studies of research leading to interventions in cardiovascular disease and mental health. Finally, we analysed the data to address our study’s key aims.

          Results

          The literature review illustrated the lack of agreement on starting points for measuring time lags. We mapped points from policy documents onto our matrix and thus highlighted key areas of concern, for example around delays before new therapies become widely available. Our seven completed case studies demonstrate we have made considerable progress in developing methods to measure and understand time lags. The matrix of overlapping tracks of activity in the research and implementation processes facilitated analysis of time lags along each track, and at the cross-over points where the next track started. We identified some factors that speed up translation through the actions of companies, researchers, funders, policymakers, and regulators. Recommendations for further work are built on progress made, limitations identified and revised terminology.

          Conclusions

          Our advances identify complexities, provide a firm basis for further methodological work along and between tracks, and begin to indicate potential ways of reducing lags.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1478-4505-13-1) contains supplementary material, which is available to authorized users.

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          Most cited references46

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          Diffusion of Innovations.

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            The case for knowledge translation: shortening the journey from evidence to effect.

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              Knowledge translation: closing the evidence-to-practice gap.

              Knowledge translation describes any activity or process that facilitates the transfer of high-quality evidence from research into effective changes in health policy, clinical practice, or products. This increasingly important discipline attempts to conceptually combine elements of research, education, quality improvement, and electronic systems development to create a seamless linkage between interventions that improve patient care and their routine implementation in daily clinical practice. We outline the gap between research and practice and present a case study of an emergency medicine example of validated evidence that has failed to achieve widespread implementation. The authors describe a model of organization of evidence and its relationship with the process that links research from the scientific endeavor to changes in practice that affect patient outcomes. Obstacles to evidence uptake are explored, as well as the limitations of current educational strategies. Innovative strategies in realms such as computerized decision support systems designed to enhance evidence uptake are also described. The potential interface between knowledge translation and continuous quality improvement, as well as the role for bedside tools, is also presented. Research in knowledge translation includes studies that attempt to quantify and understand the discrepancies between what is known and what is done, as well as those that examine the impact and acceptability of interventions designed to narrow or close these gaps. Sentinel examples in this line of research conducted in the emergency department setting are described.
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                Author and article information

                Contributors
                stephen.hanney@brunel.ac.uk
                scastlec@rand.org
                jonathan.grant@kcl.ac.uk
                sguthrie@rand.org
                chris@chrishenshall.co.uk
                jmestre-ferrandiz@ohe.org
                MPistollato@ohe.org
                apollitt@rand.org
                jsussex@ohe.org
                wooding@rand.org
                Journal
                Health Res Policy Syst
                Health Res Policy Syst
                Health Research Policy and Systems
                BioMed Central (London )
                1478-4505
                1 January 2015
                1 January 2015
                2015
                : 13
                : 1
                : 1
                Affiliations
                [ ]Health Economics Research Group, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH UK
                [ ]RAND Europe, Westbrook Centre, Milton Road, Cambridge, CB4 1YG UK
                [ ]King’s Policy Institute, King’s College London, Virginia Woolf Building, 22 Kingsway, London, WC2B 6NR UK
                [ ]Office of Health Economics, 105 Victoria Street, London, SW1E 6QT UK
                Article
                368
                10.1186/1478-4505-13-1
                4297458
                25552353
                2e556d5b-004f-4d59-b39f-534889b266ba
                © Hanney et al.; licensee BioMed Central. 2015

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 16 July 2014
                : 31 October 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Health & Social care
                basic research,clinical guidelines,discovery research,economic impact of research,human research,pharmaceutical industry,process marker model,regulatory approval,time lags,timelines

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