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Appraising the value of evidence generation activities: an HIV modelling study
  1. Beth Woods1,
  2. Claire Rothery1,
  3. Sarah-Jane Anderson2,
  4. Jeffrey W Eaton2,
  5. Paul Revill1,
  6. Timothy B Hallett2,
  7. Karl Claxton1
  1. 1 Centre for Health Economics, University of York, York, UK
  2. 2 Department of Infectious Disease Epidemiology, Imperial College London, London, UK
  1. Correspondence to Beth Woods; beth.woods{at}york.ac.uk

Abstract

Introduction The generation of robust evidence has been emphasised as a priority for global health. Evidence generation spans a wide range of activities including clinical trials, surveillance programmes and health system performance measurement. As resources for healthcare and research are limited, the desirability of research expenditure should be assessed on the same basis as other healthcare resources, that is, the health gains from research must be expected to exceed the health opportunity costs imposed as funds are diverted to research rather than service provision.

Methods We developed a transmission and costing model to examine the impact of generating additional evidence to reduce uncertainties on the evolution of a generalised HIV epidemic in Zambia.

Results We demonstrate three important points. First, we can quantify the value of additional evidence in terms of the health gain it is expected to generate. Second, we can quantify the health opportunity cost imposed by research expenditure. Third, the value of evidence generation depends on the budgetary policies in place for managing HIV resources under uncertainty. Generating evidence to reduce uncertainty is particularly valuable when decision makers are required to strictly adhere to expenditure plans and when transfers of funds across geographies/programmes are restricted.

Conclusion Better evidence can lead to health improvements in the same way as direct delivery of healthcare. Quantitative appraisals of evidence generation activities are important and should reflect the impact of improved evidence on population health, evidence generation costs and budgetary policies in place.

  • health economics
  • health policy
  • health services research
  • AIDS
  • HIV

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Footnotes

  • Handling editor Sanni Yaya

  • Contributors All authors contributed to the design of the study, interpretation of results, critically revised the manuscript and approved the final version for submission. BW programmed the resource allocation model and conducted the analyses. SJA and JE developed the transmission model. BW developed the first draft of the manuscript.

  • Funding This study was funded by the HIV Modelling Consortium, which is funded by a grant from the Bill & Melinda Gates Foundation to Imperial College London.

  • Competing interests All authors had financial support from the Bill & Melinda Gates Foundation for the submitted work; BW reports personal fees from Servier Laboratories; SJA reports personal fees from the Bill & Melinda Gates Foundation, Global Fund, Anansi Health and Avenir Health; TH reports grants from the Bill & Melinda Gates Foundation, World Bank, the Joint United Nations Programme on HIV/AIDS, Rush Foundation, Wellcome Trust and personal fees from the Bill & Melinda Gates Foundation, New York University, the World Health Organisation and The Global Fund to Fight AIDS, Tuberculosis and Malaria; KC reports personal fees from Roche Payor Evidence Council.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No additional data are available.