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Factors Limiting Subgroup Analysis in Cost-Effectiveness Analysis and a Call for Transparency

Author

Listed:
  • Gemma E. Shields

    (University of Manchester)

  • Mark Wilberforce

    (University of York)

  • Paul Clarkson

    (University of Manchester)

  • Tracey Farragher

    (University of Manchester)

  • Arpana Verma

    (University of Manchester
    University of Manchester)

  • Linda M. Davies

    (University of Manchester)

Abstract

The use of population averages in cost-effectiveness analysis may hide important differences across subgroups, potentially resulting in suboptimal resource allocation, reduced population health and/or increased health inequalities. We discuss the factors that limit subgroup analysis in cost-effectiveness analysis and propose more thorough and transparent reporting. There are many issues that may limit whether subgroup analysis can be robustly included in cost-effectiveness analysis, including challenges with prespecifying and justifying subgroup analysis, identifying subgroups that can be implemented (identified and targeted) in practice, resource and data requirements, and statistical and ethical concerns. These affect every stage of the design, development and reporting of cost-effectiveness analyses. It may not always be possible to include and report relevant subgroups in cost effectiveness, e.g. due to data limitations. Reasons for not conducting subgroup analysis may be heterogeneous, and the consequences of not acknowledging patient heterogeneity can be substantial. We recommend that when potentially relevant subgroups have not been included in a cost-effectiveness analysis, authors report this and discuss their rationale and the limitations of this. Greater transparency of subgroup reporting should provide a starting point to overcoming these challenges in future research.

Suggested Citation

  • Gemma E. Shields & Mark Wilberforce & Paul Clarkson & Tracey Farragher & Arpana Verma & Linda M. Davies, 2022. "Factors Limiting Subgroup Analysis in Cost-Effectiveness Analysis and a Call for Transparency," PharmacoEconomics, Springer, vol. 40(2), pages 149-156, February.
    • Handle: RePEc:spr:pharme:v:40:y:2022:i:2:d:10.1007_s40273-021-01108-4
    DOI: 10.1007/s40273-021-01108-4
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