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Discrete choice experiments for complex health‐care decisions: does hierarchical information integration offer a solution?

Author

Listed:
  • Debby van Helvoort‐Postulart
  • Benedict G. C. Dellaert
  • Trudy van der Weijden
  • Maarten F. von Meyenfeldt
  • Carmen D. Dirksen

Abstract

This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi‐faceted health‐care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health‐care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health‐care professionals and that of patients. We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi‐faceted health‐care decisions (objectives 1 and 2), but that the feasibility of HII to support health‐care management, in particular in challenging implementation projects, seems less favourable (objective 3). Copyright © 2008 John Wiley & Sons, Ltd.

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  • Debby van Helvoort‐Postulart & Benedict G. C. Dellaert & Trudy van der Weijden & Maarten F. von Meyenfeldt & Carmen D. Dirksen, 2009. "Discrete choice experiments for complex health‐care decisions: does hierarchical information integration offer a solution?," Health Economics, John Wiley & Sons, Ltd., vol. 18(8), pages 903-920, August.
  • Handle: RePEc:wly:hlthec:v:18:y:2009:i:8:p:903-920
    DOI: 10.1002/hec.1411
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    References listed on IDEAS

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    Cited by:

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    2. Stuart J. Wright & Caroline M. Vass & Gene Sim & Michael Burton & Denzil G. Fiebig & Katherine Payne, 2018. "Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(5), pages 475-488, October.
    3. Lucas M. A. Goossens & Marcel F. Jonker & Maureen P. M. H. Rutten-van Mölken & Melinde R. S. Boland & Annerika H. M. Slok & Philippe L. Salomé & Onno C. P. van Schayck & Johannes C. C. M. in ‘t Ve, 2019. "The Fold-in, Fold-out Design for DCE Choice Tasks: Application to Burden of Disease," Medical Decision Making, , vol. 39(4), pages 450-460, May.
    4. Mesfin G. Genie & Nicolas Krucien & Mandy Ryan, 2021. "Weighting or aggregating? Investigating information processing in multi‐attribute choices," Health Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 1291-1305, June.
    5. Michael Clark & Domino Determann & Stavros Petrou & Domenico Moro & Esther Bekker-Grob, 2014. "Discrete Choice Experiments in Health Economics: A Review of the Literature," PharmacoEconomics, Springer, vol. 32(9), pages 883-902, September.
    6. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    7. Peter Waerden & Emilie Couwenberg & Geert Wets, 2018. "Travelers’ preferences regarding the interior of public buses: a hierarchical information integration approach," Public Transport, Springer, vol. 10(3), pages 529-543, December.

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