Evidence map›Paper›PMID 30414074›Full record

ArticlePharmacoEconomics2019

Determining Value in Health Technology Assessment: Stay the Course or Tack Away?

J Jaime Caro, John E Brazier, Jonathan Karnon, Peter Kolominsky-Rabas, Alistair J McGuire, Erik Nord, Michael Schlander

Abstract read
In one paragraph

Article in PharmacoEconomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

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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

7 authors.

J Jaime CaroLondon School of Economics and Political Science, London, UK. j.caro@lse.ac.uk.
John E BrazierSchool of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
Jonathan KarnonSchool of Public Health, University of Adelaide, Adelaide, SA, Australia.
Peter Kolominsky-RabasInterdisciplinary Centre for Health Technology Assessment and Public Health, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany.
Alistair J McGuireLondon School of Economics and Political Science, London, UK.
Erik NordNorwegian Institute of Public Health, Oslo, Norway.
Michael SchlanderDivision of Health Economics, German Cancer Research Center (DKFZ), University of Heidelberg, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The economic evaluation of new health technologies to assess whether the value of the expected health benefits warrants the proposed additional costs has become an essential step in making novel interventions available to patients. This assessment of value is problematic because there exists no natural means to measure it. One approach is to assume that society wishes to maximize aggregate health, measured in terms of quality-adjusted life-years (QALYs). Commonly, a single 'cost-effectiveness' threshold is used to gauge whether the intervention is sufficiently efficient in doing so. This approach has come under fire for failing to account for societal values that favor treating more severe illness and ensuring equal access to resources, regardless of pre-existing conditions or capacity to benefit. Alternatives involving expansion of the measure of benefit or adjusting the threshold have been proposed and some have advocated tacking away from the cost per QALY entirely to implement therapeutic area-specific efficiency frontiers, multicriteria decision analysis or other approaches that keep the dimensions of benefit distinct and value them separately. In this paper, each of these alternative courses is considered, based on the experiences of the authors, with a view to clarifying their implications.

Indexed as

Quality-Adjusted Life YearsBiomedical TechnologyCost-Benefit AnalysisDecision Support TechniquesHumansTechnology Assessment, Biomedical

Identifiers

PMID30414074
PMCPMC6386014

What OpenQuestion holds

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LicenceCC BY-NC
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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.