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SAGE Publications, Journal of Health Services Research and Policy, 4(13), p. 209-214

DOI: 10.1258/jhsrp.2008.008045

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Policy-makers' attitudes to decision support models for coronary heart disease: a qualitative study

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Objectives: To explore attitudes to the use of models for coronary heart disease to support decision-making for policy and service planning. Methods: Qualitative study using semi-structured interviews with 33 policy- and decision-makers purposively sampled from the UK National Health Service (NHS) (national, regional and local levels), academia and voluntary organizations. Interviews were transcribed, coded and emergent themes identified using framework analysis aided by NVivo software. Results: Policy-makers and planners were generally enthusiastic about models to assist in decision-making through: predicting trends; assessing the effect of interventions on health inequalities; quantifying the impact of population level and targeted interventions, and facilitating economic evaluation. The perceived advantages of using models included: more rational commissioning; the facility for scenario testing; advocacy for population level interventions and off-the-shelf synthesis to aid real time decision-making. However, although participants were aware of models to support decision-making, these were not being used routinely. Some participants felt that models oversimplify complex situations and that there is a lack of shared understanding as to how models work. Factors that increase confidence in decision support models included: rigorous validation and peer review, the availability of user-support and increased transparency. Conclusion: Policy-makers and planners were generally enthusiastic about the use of models to support decision-making, illustrating the potential uses for models and the factors that improve confidence in them. However, existing models are often not being used in practice. So new models that are fit for practice need to be developed.