ArticleExpert review of pharmacoeconomics & outcomes research2016
ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare.
Article in Expert review of pharmacoeconomics & outcomes research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps.BMC medical informatics and decision making · 2018Pooled it
- Incorporating health equity into value assessment: frameworks, promising alternatives, and future directions.Journal of managed care & specialty pharmacy · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
objectiveIn this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare.
methodsThe application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers' (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery.
resultsThe criteria were ranked from 1-5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval.
conclusionsELICIT is appropriate in situations where only ordinal DMs' preferences are available to elicit decision criteria weights.
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Registered trials
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