Evidence map›Paper›PMID 34694168›Full record

SynthesisMedical decision making : an international journal of the Society for Medical Decision Making2022

The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review.

Christopher J Cadham, Marie Knoll, Luz María Sánchez-Romero, K Michael Cummings, Clifford E Douglas, Alex Liber, David Mendez, Rafael Meza, Ritesh Mistry, Aylin Sertkaya and 2 more

Abstract readSystematic Review
In one paragraph

Synthesis in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

12 authors.

Christopher J CadhamDepartment of Health Management and Policy, University of Michigan, School of Public Health, Ann Arbor, MI, USA.ORCID 0000-0001-9531-2733
Marie KnollGeorgetown University, Lombardi Comprehensive Cancer Center, Washington, DC, USA.
Luz María Sánchez-RomeroGeorgetown University, Lombardi Comprehensive Cancer Center, Washington, DC, USA.
K Michael CummingsDepartment of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
Clifford E DouglasDepartment of Health Management and Policy, University of Michigan, School of Public Health, Ann Arbor, MI, USA.
Alex LiberGeorgetown University, Lombardi Comprehensive Cancer Center, Washington, DC, USA.
David MendezDepartment of Health Management and Policy, University of Michigan, School of Public Health, Ann Arbor, MI, USA.
Rafael MezaDepartment of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
Ritesh MistryDepartment of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI, USA.
Aylin SertkayaEastern Research Group, Inc., Lexington, MA, USA.
Nargiz TravisDepartment of Health Management and Policy, University of Michigan, School of Public Health, Ann Arbor, MI, USA.ORCID 0000-0001-6305-8259
David T LevyGeorgetown University, Lombardi Comprehensive Cancer Center, Washington, DC, USA.

Funding

Research Project 3: Modeling the Impact of Tobacco Control Policies on Polytobacco Use and Associated Health DisparitiesU54CA229974 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI David Mendez Emilien · 2018 to 2026
$39.2M
FDA HHSNCI NIH HHS U54 CA229974
6 · The paper itself

Abstract

backgroundExpert elicitation (EE) has been used across disciplines to estimate input parameters for computational modeling research when information is sparse or conflictual.

objectivesWe conducted a systematic review to compare EE methods used to generate model input parameters in health research. DATA SOURCES: PubMed and Web of Science. STUDY ELIGIBILITY: Modeling studies that reported the use of EE as the source for model input probabilities were included if they were published in English before June 2021 and reported health outcomes. DATA ABSTRACTION AND SYNTHESIS: Studies were classified as "formal" EE methods if they explicitly reported details of their elicitation process. Those that stated use of expert opinion but provided limited information were classified as "indeterminate" methods. In both groups, we abstracted citation details, study design, modeling methodology, a description of elicited parameters, and elicitation methods. Comparisons were made between elicitation methods. STUDY APPRAISAL: Studies that conducted a formal EE were appraised on the reporting quality of the EE. Quality appraisal was not conducted for studies of indeterminate methods.

resultsThe search identified 1520 articles, of which 152 were included. Of the included studies, 40 were classified as formal EE and 112 as indeterminate methods. Most studies were cost-effectiveness analyses (77.6%). Forty-seven indeterminate method studies provided no information on methods for generating estimates. Among formal EEs, the average reporting quality score was 9 out of 16. LIMITATIONS: Elicitations on nonhealth topics and those reported in the gray literature were not included.

conclusionsWe found poor reporting of EE methods used in modeling studies, making it difficult to discern meaningful differences in approaches. Improved quality standards for EEs would improve the validity and replicability of computational models. HIGHLIGHTS: We find extensive use of expert elicitation for the development of model input parameters, but most studies do not provide adequate details of their elicitation methods.Lack of reporting hinders greater discussion of the merits and challenges of using expert elicitation for model input parameter development.There is a need to establish expert elicitation best practices and reporting guidelines.

Indexed as

Research DesignComputer SimulationCost-Benefit AnalysisHumansProbabilitycomputational modelingexpert elicitationexpert judgmentexpert opinionsystematic review

Identifiers

PMID34694168
PMCPMC9035479

What OpenQuestion holds

Textmetadata
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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.