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Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration

Author

Listed:
  • Qi Cao

    () (University of Groningen
    University of Groningen, University Medical Center Groningen)

  • Erik Buskens

    (University of Groningen, University Medical Center Groningen)

  • Hans L. Hillege

    (University of Groningen, University Medical Center Groningen
    University of Groningen, University Medical Center Groningen, Groningen)

  • Tiny Jaarsma

    (Linköping University)

  • Maarten Postma

    (University of Groningen
    University of Groningen, University Medical Center Groningen
    University of Groningen, University Medical Center Groningen (UMCG)
    University of Groningen, University Medical Center Groningen (UMCG))

  • Douwe Postmus

    (University of Groningen, University Medical Center Groningen)

Abstract

Objectives We sought to explore to what extent the use of Subpopulation Treatment Effect Pattern Plot (STEPP) may help to identify efficient treatment allocation strategy. Methods The analysis was based on data from the COACH study, in which 1023 patients with heart failure were randomly assigned to three treatments: care-as-usual, basic support, and intensive support. First, using predicted 18-month mortality risk as the stratification basis, a suitable strategy for assigning different treatments to different risk groups of patients was developed. To that end, a graphical exploration of the difference in net monetary benefit (NMB) across treatment regimens and baseline risk was used. Next, the efficiency gains resulting from this proposed subgroup strategy were quantified by computing the difference in NMB between our stratified approach and the best performing population-wide strategy. Results The analysis using STEPPs suggested that a differentiated approach, based on offering intensive support to low-risk patients (18-month mortality risk ≤ 0.16) and basic support to intermediate- to high-risk patients (18-month mortality risk > 0.16) would be an economically efficient treatment allocation strategy. This was confirmed in the subsequent cost-effectiveness analysis, where the average gain in NMB resulting from the proposed stratified approach compared to basic support for all was found to be €1312 (95% CI €390–€2346) per patient. Conclusions STEPP provides a systematic approach to assess the interaction between baseline risk and the difference in NMB between competing interventions and to identify cutoffs to stratify patients in a health economically optimal manner.

Suggested Citation

  • Qi Cao & Erik Buskens & Hans L. Hillege & Tiny Jaarsma & Maarten Postma & Douwe Postmus, 2019. "Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 475-482, April.
  • Handle: RePEc:spr:eujhec:v:20:y:2019:i:3:d:10.1007_s10198-018-1013-z
    DOI: 10.1007/s10198-018-1013-z
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    References listed on IDEAS

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    1. Janneke Grutters & Mark Sculpher & Andrew Briggs & Johan Severens & Math Candel & James Stahl & Dirk Ruysscher & Albert Boer & Bram Ramaekers & Manuela Joore, 2013. "Acknowledging Patient Heterogeneity in Economic Evaluation," PharmacoEconomics, Springer, vol. 31(2), pages 111-123, February.
    2. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    3. Andrew R. Willan & Andrew H. Briggs & Jeffrey S. Hoch, 2004. "Regression methods for covariate adjustment and subgroup analysis for non‐censored cost‐effectiveness data," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 461-475, May.
    4. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430, July.
    5. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    6. Karl Claxton & John Posnett, "undated". "An Economic Approach to Clinical Trial Design and Research Priority Setting," Discussion Papers 96/19, Department of Economics, University of York.
    7. Drummond, Michael F. & Sculpher, Mark J. & Claxton, Karl & Stoddart, Greg L. & Torrance, George W., 2015. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 4, number 9780199665884.
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