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Translating health information into policy-making: A pragmatic framework

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  • Funk, Tjede
  • Sharma, Tarang
  • Chapman, Evelina
  • Kuchenmüller, Tanja

Abstract

Knowledge translation (KT) is increasingly acknowledged to have the potential to improve policy-making. The value of health information (HI), as part of the KT context, is now also increasingly understood. This paper aims to identify existing tools for the translation of HI into policy-making and to develop a related framework facilitating future application of these identified tools. Updating and building upon a scoping review undertaken for the Health Evidence Network (HEN) Synthesis Report No. 54, commissioned by the World Health Organization (WHO) Regional Office for Europe in 2017, a literature search was conducted using the same databases (PubMed and Scopus) and the same keywords as in the WHO/HEN scoping review. All papers elaborating on tools enhancing the use of HI in policy-making were included. Of the 2549 records screened, 17 publications were included in this study. This review identified four different types of tools: 1) Visualisation and modelling tools, 2) Information packaging and synthesis tools, 3) Communication and dissemination tools and 4) Information linkage and exchange tools. The distinctions between these are fluid as different tools can be combined or incorporated into one another to complement each other. Our framework shows that communication/dissemination or linkage tools are crucial to effectively inform policy decisions through HI. This study helps to understand and guide the processes of KT of HI.

Suggested Citation

  • Funk, Tjede & Sharma, Tarang & Chapman, Evelina & Kuchenmüller, Tanja, 2022. "Translating health information into policy-making: A pragmatic framework," Health Policy, Elsevier, vol. 126(1), pages 16-23.
  • Handle: RePEc:eee:hepoli:v:126:y:2022:i:1:p:16-23
    DOI: 10.1016/j.healthpol.2021.10.001
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    References listed on IDEAS

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    1. Brownson, R.C. & Chriqui, J.F. & Stamatakis, K.A., 2009. "Understanding evidence-based public health policy," American Journal of Public Health, American Public Health Association, vol. 99(9), pages 1576-1583.
    2. Bogaert, Petronille & van Oers, Hans & Van Oyen, Herman, 2018. "Towards a sustainable EU health information system infrastructure: A consensus driven approach," Health Policy, Elsevier, vol. 122(12), pages 1340-1347.
    3. Chung, Younjin & Bagheri, Nasser & Salinas-Perez, Jose Alberto & Smurthwaite, Kayla & Walsh, Erin & Furst, MaryAnne & Rosenberg, Sebastian & Salvador-Carulla, Luis, 2020. "Role of visual analytics in supporting mental healthcare systems research and policy: A systematic scoping review," International Journal of Information Management, Elsevier, vol. 50(C), pages 17-27.
    4. Jo-An Atkinson & Dylan Knowles & John Wiggers & Michael Livingston & Robin Room & Ante Prodan & Geoff McDonnell & Eloise O’Donnell & Sandra Jones & Paul S. Haber & David Muscatello & Nadine Ezard & Ng, 2018. "Harnessing advances in computer simulation to inform policy and planning to reduce alcohol-related harms," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(4), pages 537-546, May.
    5. Sarah Giest, 2017. "Big data for policymaking: fad or fasttrack?," Policy Sciences, Springer;Society of Policy Sciences, vol. 50(3), pages 367-382, September.
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    1. Qianjin Zong & Zhihong Huang & Jiaru Huang, 2023. "Can open access increase LIS research’s policy impact? Using regression analysis and causal inference," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4825-4854, August.

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