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Epidemiology and policy
P1-99 A policy effectiveness-feasibility loop for evidence-based public health policy
  1. S Bowman1,
  2. N Unwin2,
  3. J Critchley3,
  4. A Husseini4,
  5. B Unal5,
  6. F Fouad6,
  7. W Maziak6,
  8. H B Romdhane7,
  9. S Capewell8
  1. 1Institute of Health and Society, University of Newcastle, Newcastle Upon Tyne, UK
  2. 2The Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
  3. 3St. George's Hospital Medical School, University of London, London, UK
  4. 4Institute of Community and Public Health, Birzeit University, Birzeit, Occupied Palestinian Territory
  5. 5Department of Public Health, School of Medicine, Dokuz Eylul University, Izmir, Turkey
  6. 6Syrian Center for Tobacco Studies, Aleppo, Syria
  7. 7National Public Health Institute, CVD Epidemiology and Prevention Research Laboratory, Tunis, Tunisia
  8. 8School of Population Community and Behavioural Sciences, University of Liverpool, Liverpool, UK

Abstract

Introduction While public health policy could profoundly effect health status1, research informing policy-making and implementation is underutilised.1–5 A range of evidence types are required to support policy-making, and involving policy makers in generating and evaluating evidence is important. This work aims to develop, implement and evaluate an interactive approach to informing policy for preventing and managing cardiovascular disease (CVD) and diabetes (focusing on four territories with a high disease burden: Palestine, Turkey, Tunisia and Syria).

Methods and Results Three main types of research activity are proposed:

  1. Epidemiological modelling: three models estimate major risk factor trends including relative contribution to overall reduction in CHD deaths.

  2. Situation analysis: three main elements are investigated using mixed methods. Analysis will suggest acceptable and feasible interventions and opportunities and barriers for implementation.

  3. Economic modelling: potentially effective and feasible options will be evaluated, including country-specific cost and cost-effectiveness ratios.

A ‘policy effectiveness-feasibility loop’ model (based on an ‘equity effectiveness loop’7) is proposed to link evidence types and facilitate its systematic, operational use in policy-formulation. Illustrative findings from using this model in four focus countries will be described. Policy makers are involved throughout, informing the situation analysis and choosing and appraising options for implementation.

Conclusion Other non-linear models exist for how research influences policy-making6. This work proposes a pragmatic framework to: combine all evidence types (particularly cost effectiveness); involve policy makers; and use evidence to develop policy options (initially for CVD and diabetes prevention). Next steps for evaluation are suggested.

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