Discrete choice experiment to determine preferences of decision-makers in healthcare for different formats of rapid reviews.

Conjoint analysis Discrete choice experiment Evidence synthesis Preference Rapid review

Journal

Systematic reviews
ISSN: 2046-4053
Titre abrégé: Syst Rev
Pays: England
ID NLM: 101580575

Informations de publication

Date de publication:
20 04 2021
Historique:
received: 09 10 2020
accepted: 22 03 2021
entrez: 21 4 2021
pubmed: 22 4 2021
medline: 6 7 2021
Statut: epublish

Résumé

Time-saving formats of evidence syntheses have been developed to fulfill healthcare policymakers' demands for timely evidence-based information. A discrete choice experiment (DCE) with decision-makers and people involved in the preparation of evidence syntheses was undertaken to elicit preferences for methodological shortcuts in the conduct of abbreviated reviews. D-efficient scenarios, each containing 14 pairwise comparisons, were designed for the DCE: the development of an evidence synthesis in 20 working days (scenario 1) and 12 months (scenario 2), respectively. Six attributes (number of databases, number of reviewers during screening, publication period, number of reviewers during data extraction, full-text analysis, types of HTA domains) with 2 to 3 levels each were defined. These were presented to the target population in an online survey. The relative importance of the individual attributes was determined using logistic regression models. Scenario 1 was completed by 36 participants and scenario 2 by 26 participants. The linearity assumption was confirmed by the full model. In both scenarios, the linear difference model showed a preference for higher levels for "number of reviewers during data extraction", followed by "number of reviewers during screening" and "full-text analysis". Subgroup analyses showed that preferences were influenced by participation in the preparation of evidence syntheses. The surveyed persons expressed preferences for quality standards in the process of literature screening and data extraction.

Sections du résumé

BACKGROUND
Time-saving formats of evidence syntheses have been developed to fulfill healthcare policymakers' demands for timely evidence-based information. A discrete choice experiment (DCE) with decision-makers and people involved in the preparation of evidence syntheses was undertaken to elicit preferences for methodological shortcuts in the conduct of abbreviated reviews.
METHODS
D-efficient scenarios, each containing 14 pairwise comparisons, were designed for the DCE: the development of an evidence synthesis in 20 working days (scenario 1) and 12 months (scenario 2), respectively. Six attributes (number of databases, number of reviewers during screening, publication period, number of reviewers during data extraction, full-text analysis, types of HTA domains) with 2 to 3 levels each were defined. These were presented to the target population in an online survey. The relative importance of the individual attributes was determined using logistic regression models.
RESULTS
Scenario 1 was completed by 36 participants and scenario 2 by 26 participants. The linearity assumption was confirmed by the full model. In both scenarios, the linear difference model showed a preference for higher levels for "number of reviewers during data extraction", followed by "number of reviewers during screening" and "full-text analysis". Subgroup analyses showed that preferences were influenced by participation in the preparation of evidence syntheses.
CONCLUSION
The surveyed persons expressed preferences for quality standards in the process of literature screening and data extraction.

Identifiants

pubmed: 33879246
doi: 10.1186/s13643-021-01647-z
pii: 10.1186/s13643-021-01647-z
pmc: PMC8057003
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

121

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Auteurs

Christian Speckemeier (C)

Institute for Healthcare Management and Research, University of Duisburg-Essen, Thea-Leymann-Str. 9, 45127, Essen, Germany. christian.speckemeier@medman.uni-due.de.

Laura Krabbe (L)

Institute for Healthcare Management and Research, University of Duisburg-Essen, Thea-Leymann-Str. 9, 45127, Essen, Germany.

Susanne Schwenke (S)

Scossis, Karmeliterweg 42, 13465, Berlin, Germany.

Jürgen Wasem (J)

Institute for Healthcare Management and Research, University of Duisburg-Essen, Thea-Leymann-Str. 9, 45127, Essen, Germany.

Barbara Buchberger (B)

Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany.

Silke Neusser (S)

Institute for Healthcare Management and Research, University of Duisburg-Essen, Thea-Leymann-Str. 9, 45127, Essen, Germany.

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Classifications MeSH