ArticleHealth services research2023
Alternatives to the quality-adjusted life year: How well do they address common criticisms?
Article in Health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- The economic burden of functional neurological disorder.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- New Anticancer Drugs: Reliably Assessing "Value" While Addressing High Prices.Current oncology (Toronto, Ont.) · 2024Article
- An Alternative Measure of Health for Value Assessment: The Equal Value Life-Year.PharmacoEconomics · 2023Article
- Alternatives to the quality-adjusted life year: How well do they address common criticisms?Health services research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo analyze whether other outcome measures used in health technology assessment (HTA) address the criticisms of quality-adjusted life years (QALYs). DATA SOURCES AND STUDY
settingHTA methods guidance from 11 US comparator countries (the G10 and Australia) and six value frameworks from US organizations were reviewed to identify health outcome measures currently used to evaluate the benefits of a drug. STUDY
designThe study involved a documentary analysis of guidelines to identify outcome measures used by the sampled HTA organizations. Similar outcomes were grouped together into outcome types. Each type was analyzed to determine the extent to which it replicates key advantages and responds to criticisms of QALYs extracted from the literature. EXTRACTION
methodsOutcomes were included if guidance from at least one HTA organization identified the outcome as acceptable for HTA. Outcomes measuring or evaluating the benefit, clinical effect, or impact of a drug or health technology was included; methods of calculating costs were excluded. PRINCIPAL
findingsSeven types of outcome measures were identified falling into three groups: preference-based, single-dimension outcomes, and outcomes using non-health perspectives. Among the seven QALY alternative outcome measures currently used for HTA by the sampled countries, no one outcome measure addresses all the QALY criticisms while retaining the advantageous features of the QALY.
conclusionsProposals to adopt health technology assessment (HTA) to support value-based pricing of prescription drugs in the US have faced pushback over the use of the QALY. There is no single "right" outcome measure, and the criticisms of QALYs apply to other outcome measures used to evaluate health. The measures identified have different features and strengths, which may be appropriate for specific decision making goals, but the QALY remains the best option for decision making that requires comparisons of the overall societal value of health gains.
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What OpenQuestion holds
Registered trials
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.