Using natural experiments to evaluate population health and health system interventions: new framework for producers and users of evidence
Peter Craiga, Mhairi Campbella✉, Manuela Deiddab, Ruth Dundasa, John Greenc, Srinivasa Vittal Katikireddia, Jim Lewseyd, David Ogilviee, Frank de Vochtf g, Martin Whitee
- aMRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
- bSchool of Health and Wellbeing, University of Glasgow, Glasgow, UK
- cWellcome Centre for Cultures and Environments of Health, University of Exeter, Exeter, UK
- dHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
- eMRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- fNIHR Applied Research Collaboration West, Bristol, UK
- gPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- ✉Corresponding author
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Abstract
Natural experiments are widely used to evaluate the impacts on health of changes in policies, infrastructure, and services. The UK Medical Research Council (MRC) and National Institute for Health and Care Research (NIHR) have published a new framework for conducting and using evidence from natural experimental evaluations. The framework defines key concepts and describes recent advances in designing and planning evaluations of natural experiments, including the relevance of a systems perspective, mixed methods, and stakeholder involvement. It provides an overview of the strengths, weaknesses, applicability, and limitations of the range of methods now available, and makes good practice recommendations for researchers, funders, publishers, and users of evidence.
TL;DRA new framework for conducting and using evidence from natural experimental evaluations is published, which defines key concepts and describes recent advances in designing and planning evaluations of natural experiments, including the relevance of a systems perspective, mixed methods, and stakeholder involvement. (Semantic Scholar)