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Record W2015583354 · doi:10.3109/07853890109002092

The Health Utilities Index (HUI®) system for assessing health-related quality of life in clinical studies

2001· review· en· W2015583354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Medicine · 2001
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHealth Utilities IndexQuality of life (healthcare)MedicineQuality-adjusted life yearHealth related quality of lifeIndex (typography)GerontologyPopulationCost effectivenessEnvironmental healthRisk analysis (engineering)Computer sciencePathology

Abstract

fetched live from OpenAlex

This paper reviews the Health Utilities Index (HUI) systems as means to describe health status and obtain utility scores reflecting health-related quality of life (HRQoL). The HUI Mark 2 (HUI2) and Mark 3 (HUI3) classification and scoring systems are described. The methods used to estimate multiattribute utility functions for HUI2 and HUI3 are reviewed. The use of HUI in clinical studies for a wide variety of conditions in a large number of countries is illustrated. HUI provides a comprehensive description of the health status of subjects in clinical studies. HUI has been shown to be a reliable, responsive and valid measure in a wide variety of clinical studies. Utility scores provide an overall assessment of the HRQoL of patients. Utility scores are also useful in cost-utility analyses and related studies. General population norm data are available. The widespread use of HUI facilitates the interpretation of results and permits comparisons. HUI is a useful tool for assessing health status and HRQoL in clinical studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.213
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2130.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0140.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.910
GPT teacher head0.669
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it