Translating the Results of Discrete Choice Experiments into p-/e-/m-Health Decision Support Tools

Jack Dowie, Mette Kjer Kaltoft

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Abstract

The rapidly growing number of health-related Discrete Choice Experiments (DCEs) has not been matched by studies of their impact on decision or policymaking. However, it is widely assumed that this impact has been very limited, despite the potential relevance of the resulting average preferences to group policy development. The main, but at the moment essentially speculative, explanation offered, focuses on the methodological quality of the DCEs and their reporting. An alternative explanation, equally speculative, lies in the research-practice gap created by the conceptualisation of the DCE as a purely research exercise, not supplemented by any attempt to translate the findings into analytic decision support form. This also applies in the clinical decision context, where there are frequent claims that DCE results can assist in an individual's decision making. In the absence of suggestions as to how group results can analytically facilitate preference-sensitive care (and legally informed consent), we propose a generic add-on for DCEs with 'real' options, attributes, and attribute levels. This takes the form of a multi-criteria analysis-based decision support tool. Exemplars, showing how preference-sensitive individualised opinions can be derived from published DCEs for Heavy Menstrual Bleeding and Prostate Cancer Screening, may be consulted online.

Original languageEnglish
Title of host publicationProceedings of pHealth 2019
EditorsBernd Blobel, Mauro Giacomini
Volume261
PublisherIOS Press
Publication date2019
Pages193-198
ISBN (Print)978-1-61499-974-4
ISBN (Electronic)978-1-61499-975-1
DOIs
Publication statusPublished - 2019
Event16th International Conference on Wearable, Micro & Nano technologies for Personalized Health - Italy, Italy
Duration: 10. Jun 201912. Jun 2019
Conference number: 16

Conference

Conference16th International Conference on Wearable, Micro & Nano technologies for Personalized Health
Number16
CountryItaly
CityItaly
Period10/06/201912/06/2019
SeriesStudies in Health Technology and Informatics
Volume261
ISSN0926-9630

Keywords

  • decision support
  • Discrete Choice Experiment
  • heavy menstrual bleeding
  • Multi-Criteria Decision Analysis
  • prostate cancer screening
  • Prostate-Specific Antigen
  • Choice Behavior
  • Early Detection of Cancer
  • Humans
  • Decision Support Techniques
  • Male
  • Patient Preference
  • Telemedicine
  • Prostatic Neoplasms/diagnosis

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