Evidence map›Paper›PMID 23178639›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2013

Estimating a preference-based index from the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM): valuation of CORE-6D.

Ifigeneia Mavranezouli, John E Brazier, Donna Rowen, Michael Barkham

Open access · greenAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
9.2field-weighted citation impact, top 3% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Dimensions Used in Instruments for QALY Calculation: A Systematic Review.International journal of environmental research and public health · 2021
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  17. Estimating a Preference-Based Index for Mental Health From the Recovering Quality of Life Measure: Valuation of Recovering Quality of Life Utility Index.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Ifigeneia MavranezouliHealth Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (IM, JEB, DR)
John E BrazierHealth Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (IM, JEB, DR)
Donna RowenHealth Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (IM, JEB, DR)
Michael BarkhamCentre for Psychological Services Research, University of Sheffield, Sheffield, UK (MB)
Centre for Mental Health · GBUniversity College London · GBUniversity of Sheffield · GB

Funding

Medical Research Council
6 · The paper itself

Abstract

backgroundThe Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) is used to evaluate the effectiveness of psychological therapies in people with common mental disorders. The objective of this study was to estimate a preference-based index for this population using CORE-6D, a health state classification system derived from the CORE-OM consisting of a 5-item emotional component and a physical item, and to demonstrate a novel method for generating states that are not orthogonal.

methodsRasch analysis was used to identify 11 emotional health states from CORE-6D that were frequently observed in the study population and are, thus, plausible (in contrast, conventional statistical design might generate implausible states). Combined with the 3 response levels of the physical item of CORE-6D, they generate 33 plausible health states, 18 of which were selected for valuation. A valuation survey of 220 members of the public in South Yorkshire, United Kingdom, was undertaken using the time tradeoff (TTO) method. Regression analysis was subsequently used to predict values for all possible states described by CORE-6D.

resultsA number of multivariate regression models were built to predict values for the 33 health states of CORE-6D, using the Rasch logit value of the emotional state and the response level of the physical item as independent variables. A cubic model with high predictive value (adjusted R(2) = 0.990) was selected to predict TTO values for all 729 CORE-6D health states.

conclusionThe CORE-6D preference-based index will enable the assessment of cost-effectiveness of interventions for people with common mental disorders using existing and prospective CORE-OM data sets. The new method for generating states may be useful for other instruments with highly correlated dimensions.

Indexed as

Outcome Assessment, Health CareData CollectionHumans

Identifiers

PMID23178639
PMCPMC4107796
OpenAlexW2136440701

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.