Evidence map›Paper›PMID 29909877›Full record

ReviewValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research2018

Experiences of Structured Elicitation for Model-Based Cost-Effectiveness Analyses.

Marta O Soares, Linda Sharples, Alec Morton, Karl Claxton, Laura Bojke

Abstract readReview
In one paragraph

Review in Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Pooled it
  4. Article
  5. Article
  6. Co-designing a Structured Expert Elicitation with Clinicians to Enhance Health Care Decision Making in Exercise Oncology.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Direct healthcare costs of non-metastatic castration-resistant prostate cancer in Italy.International journal of technology assessment in health care · 2023
    Article
  14. Article
  15. Reference Case Methods for Expert Elicitation in Health Care Decision Making.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Authors' Response to: "Health Opportunity Costs and Expert Elicitation: A Comment on Soares et al." by Sampson, Firth, and Towse.Medical decision making : an international journal of the Society for Medical Decision Making · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marta O SoaresCentre for Health Economics, University of York, York, UK. Electronic address: marta.soares@york.ac.uk.
Linda SharplesMedical Statistics Department, London School of Hygiene and Tropical Medicine, London, UK.
Alec MortonManagement Science, University of Strathclyde, Glasgow, UK.
Karl ClaxtonCentre for Health Economics, University of York, York, UK; Department of Economics, University of York, York, UK.
Laura BojkeCentre for Health Economics, University of York, York, UK.

Funding

Medical Research Council MR/N028511/1
6 · The paper itself

Abstract

backgroundEmpirical evidence supporting the cost-effectiveness estimates of particular health care technologies may be limited, or it may even be missing entirely. In these situations, additional information, often in the form of expert judgments, is needed to reach a decision. There are formal methods to quantify experts' beliefs, termed as structured expert elicitation (SEE), but only limited research is available in support of methodological choices. Perhaps as a consequence, the use of SEE in the context of cost-effectiveness modelling is limited.

objectivesThis article reviews applications of SEE in cost-effectiveness modelling with the aim of summarizing the basis for methodological choices made in each application and recording the difficulties and challenges reported by the authors in the design, conduct, and analyses.

methodsThe methods used in each application were extracted along with the criteria used to support methodological and practical choices and any issues or challenges discussed in the text. Issues and challenges were extracted using an open field, and then categorised and grouped for reporting.

resultsThe review demonstrates considerable heterogeneity in methods used, and authors acknowledge great methodological uncertainty in justifying their choices. Specificities of the context area emerging as potentially important in determining further methodological research in elicitation are between- expert variation and its interpretation, the fact that substantive experts in the area may not be trained in quantitative subjects, that judgments are often needed on various parameter types, the need for some form of assessment of validity, and the need for more integration with behavioural research to devise relevant debiasing strategies.

conclusionsThis review of experiences of SEE highlights a number of specificities/constraints that can shape the development of guidance and target future research efforts in this area.

Indexed as

Cost-Benefit AnalysisComparative Effectiveness ResearchConsensusDecision Support TechniquesHumansModels, EconomicProbabilityResearch DesignBayesiancost effectivenessdecision modelingelicitationexpert judgmentsubjective

Identifiers

PMID29909877
PMCPMC6021555

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.