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Bayesian econometric modelling of observational data for cost‐effectiveness analysis: establishing the value of negative pressure wound therapy in the healing of open surgical wounds

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  • Pedro Saramago
  • Karl Claxton
  • Nicky J. Welton
  • Marta Soares

Abstract

In the absence of evidence from randomized controlled trials on the relative effectiveness of treatments, cost‐effectiveness analyses increasingly use observational data instead. Treatment assignment is not, however, randomized, and naive estimates of the treatment effect may be biased. To deal with this bias, one may need to adjust for observed and unobserved confounders. In this work we explore and discuss the challenges of these adjustment strategies within a case‐study of negative pressure wound therapy (NPWT) for the treatment of surgical wounds healing by secondary intention. We could not demonstrate that existing uncontrolled confounding affects NPWT effectiveness, and thus there was no evidence that NPWT was cost effective compared with standard dressings for the treatment of surgical wounds healing by secondary intention.

Suggested Citation

  • Pedro Saramago & Karl Claxton & Nicky J. Welton & Marta Soares, 2020. "Bayesian econometric modelling of observational data for cost‐effectiveness analysis: establishing the value of negative pressure wound therapy in the healing of open surgical wounds," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1575-1593, October.
    • Handle: RePEc:bla:jorssa:v:183:y:2020:i:4:p:1575-1593
    DOI: 10.1111/rssa.12596
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