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TAKING PATIENT HETEROGENEITY AND PREFERENCES INTO ACCOUNT IN HEALTH TECHNOLOGY ASSESSMENTS

Published online by Cambridge University Press:  25 October 2017

Wietske Kievit
Affiliation:
Radboud Institute for Health Scienceswietske.kievit@radboudumc.nl
Marcia Tummers
Affiliation:
Radboud Institute for Health Sciences
Ralph van Hoorn
Affiliation:
Radboud Institute for Health Sciences
Andrew Booth
Affiliation:
Health Economics and Decision Science (HEDS)
Kati Mozygemba
Affiliation:
Institute for Public Health and Nursing Research (IPP)
Pietro Refolo
Affiliation:
Institute of Bioethics and Medical Humanities
Dario Sacchini
Affiliation:
Institute of Bioethics and Medical Humanities
Lisa Pfadenhauer
Affiliation:
Institute for Biometrics, Epidemiology and Medical Informatics
Ansgar Gerhardus
Affiliation:
Institute for Public Health and Nursing Research (IPP)
Gert Jan Van der Wilt
Affiliation:
Donders Institute for Brain, Cognition and Behaviour

Abstract

Objectives: The INTEGRATE-HTA project provided methodology to evaluate complex technologies. This study provides guidance on how to retrieve and critically appraise available evidence on moderators and predictors of treatment effects and on patient preferences for treatment outcomes as a source of complexity.

Methods: Search filters for PubMed were developed by hand-searching a large volume of articles reporting on relevant aspects. Search terms were retrieved from selected papers and algorithmically combined to find the optimal combination of search terms. For the development of the appraisal checklists literature was searched in PubMed and Google Scholar together with citation chasing. For the CHecklist for the Appraisal of Moderators and Predictors (CHAMP) a Delphi procedure was used to value a set of eligible appraisal criteria retrieved from the literature.

Results: Search filters were developed optimized for different accuracy measures. The final version of CHAMP consists of a seventeen questions covering the design, analysis, results and transferability of results of moderator and predictor analysis. The final checklist for appraisal of literature on patient preferences for treatment outcomes consist of six questions meant to help the user to identify relevant quality issues together with a guidance toward existing tools concerning the appraisal of specific preference elicitation methods.

Conclusions: Incorporating knowledge on subgroups for whom a specific treatment will produce more benefit holds the promise of better targeting and, ultimately, enhancing overall effectiveness and efficiency of healthcare technology. Finally, incorporating information on preferences for treatment outcomes will foster health technology assessment that addresses outcomes that are important to patients.

Type
Theme Submissions
Copyright
Copyright © Cambridge University Press 2017 

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References

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