The Health Utilities Index (HUI®) system for assessing health-related quality of life in clinical studies
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".