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Guidance on the use of complex systems models for economic evaluations of public health interventions.
Breeze, Penny R; Squires, Hazel; Ennis, Kate; Meier, Petra; Hayes, Kate; Lomax, Nik; Shiell, Alan; Kee, Frank; de Vocht, Frank; O'Flaherty, Martin; Gilbert, Nigel; Purshouse, Robin; Robinson, Stewart; Dodd, Peter J; Strong, Mark; Paisley, Suzy; Smith, Richard; Briggs, Andrew; Shahab, Lion; Occhipinti, Jo-An; Lawson, Kenny; Bayley, Thomas; Smith, Robert; Boyd, Jennifer; Kadirkamanathan, Visakan; Cookson, Richard; Hernandez-Alava, Monica; Jackson, Christopher H; Karapici, Amanda; Sassi, Franco; Scarborough, Peter; Siebert, Uwe; Silverman, Eric; Vale, Luke; Walsh, Cathal; Brennan, Alan.
Afiliación
  • Breeze PR; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Squires H; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Ennis K; British Medical Journal Technology Appraisal Group, London, UK.
  • Meier P; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Scotland, UK.
  • Hayes K; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Lomax N; School of Geography, University of Leeds, Leeds, UK.
  • Shiell A; Department of Public Health, LaTrobe University, Melbourne, Australia.
  • Kee F; Centre for Public Health, Queen's University Belfast, Belfast, UK.
  • de Vocht F; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • O'Flaherty M; NIHR Applied Research Collaboration West (ARC West), Bristol, UK.
  • Gilbert N; Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
  • Purshouse R; CRESS, University of Surrey, Guildford, UK.
  • Robinson S; Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
  • Dodd PJ; Business School, University of Newcastle, Newcastle, UK.
  • Strong M; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Paisley S; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Smith R; Lumanity-HEOR, South Yorkshire, Sheffield, UK.
  • Briggs A; College of Medicine and Health, University of Exeter, Exeter, UK.
  • Shahab L; London School of Hygiene & Tropical Medicine, London, UK.
  • Occhipinti JA; Department of Behavioural Science and Health, UCL, London, UK.
  • Lawson K; Brain and Mind Centre, University of Sydney, New South Wales, Camperdown, Australia.
  • Bayley T; Brain and Mind Centre, University of Sydney, New South Wales, Camperdown, Australia.
  • Smith R; United Kingdom Health Security Agency, Birmingham, UK.
  • Boyd J; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Kadirkamanathan V; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Cookson R; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
  • Hernandez-Alava M; Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
  • Jackson CH; Centre for Health Economics, University of York, Heslington, UK.
  • Karapici A; School of Health and Related Research, University of Sheffield, Sheffield, UK.
  • Sassi F; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
  • Scarborough P; NIHR SPHR, London School of Hygiene and Tropical Medicine, London, UK.
  • Siebert U; Centre for Health Economics & Policy Innovation, Imperial College Business School, London, UK.
  • Silverman E; Nuffield Department of Population Health, University of Oxford, Oxfordshire, Oxford, UK.
  • Vale L; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Tyrol, Austria.
  • Walsh C; Division of Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
  • Brennan A; Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard T.H. Chan School of Public Health, Massachusetts, Boston, USA.
Health Econ ; 32(7): 1603-1625, 2023 07.
Article en En | MEDLINE | ID: mdl-37081811
To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Política Pública / Salud Pública Tipo de estudio: Guideline / Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Health Econ Asunto de la revista: SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Política Pública / Salud Pública Tipo de estudio: Guideline / Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Health Econ Asunto de la revista: SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article