Evidence map›Paper›PMID 20152041›Full record

ReviewHealth and quality of life outcomes2010

Using qualitative methods to inform the trade-off between content validity and consistency in utility assessment: the example of type 2 diabetes and Alzheimer's disease.

Clare McGrath, Diana Rofail, Elizabeth Gargon, Linda Abetz

Abstract readReview
In one paragraph

Review in Health and quality of life outcomes, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Quality of Life and Utility Values for Cost-Effectiveness Modeling in Japanese Patients with Type 2 Diabetes.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2020
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Health status and QOL instruments used in childhood cancer research: deciphering conceptual content using World Health Organization definitions.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2011
    Review
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

4 authors.

Clare McGrathHealth Technology Assessment Policy, Medical Division, Worldwide Pharmaceutical Operations, 3-1-60 Walton Oaks, Tadworth, Surrey KT20 7NS, UK.
Diana Rofail
Elizabeth Gargon
Linda Abetz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKey stakeholders regard generic utility instruments as suitable tools to inform health technology assessment decision-making regarding allocation of resources across competing interventions. These instruments require a 'descriptor', a 'valuation' and a 'perspective' of the economic evaluation. There are various approaches that can be taken for each of these, offering a potential lack of consistency between instruments (a basic requirement for comparisons across diseases). The 'reference method' has been proposed as a way to address the limitations of the Quality-Adjusted Life Year (QALY). However, the degree to which generic measures can assess patients' specific experiences with their disease would remain unresolved. This has been neglected in the discussions on methods development and its impact on the QALY values obtained and resulting cost per QALY estimate underestimated. This study explored the content of utility instruments relevant to type 2 diabetes and Alzheimer's disease (AD) as examples, and the role of qualitative research in informing the trade-off between content coverage and consistency.

methodA literature review was performed to identify qualitative and quantitative studies regarding patients' experiences with type 2 diabetes or AD, and associated treatments. Conceptual models for each indication were developed. Generic- and disease-specific instruments were mapped to the conceptual models.

resultsFindings showed that published descriptions of relevant concepts important to patients with type 2 diabetes or AD are available for consideration in deciding on the most comprehensive approach to utility assessment. While the 15-dimensional health related quality of life measure (15D) seemed the most comprehensive measure for both diseases, the Health Utilities Index 3 (HUI 3) seemed to have the least coverage for type 2 diabetes and the EuroQol-5 Dimensions (EQ-5D) for AD. Furthermore, some of the utility instruments contained items that could not be mapped onto either of the proposed conceptual models.

conclusionsContent of the utility measure has a significant impact on the treatment effects that can be observed. This varies from one disease to the next and as such contributes to lack of consistency in observable utility effects and incremental utility scores. This observation appears to have been omitted from the method development considerations such as reference methods. As a result, we recommend that patients' perspectives obtained via qualitative methods are taken into consideration in the ongoing methods development in health state descriptions for generic utility instruments. Also, as a more immediate contribution to improving decision making, we propose that a content map of the chosen utility measure with patient-reported domains be provided as standard reporting in utility measurement in order to improve the transparency of the trade-offs in relation to patient relevance and consistency.

Indexed as

Decision Support TechniquesHealth StatusQuality-Adjusted Life YearsAdolescentAlzheimer DiseaseChildCost-Benefit AnalysisDiabetes Mellitus, Type 2HumansOutcome Assessment, Health CareQualitative ResearchResource Allocation

Identifiers

PMID20152041
PMCPMC2844366

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.