Logical Inconsistencies in the Health Years in Total and Equal Value of Life-Years Gained
Bibliographic record
Abstract
OBJECTIVES: This study aimed to assess whether recently proposed alternatives to the quality-adjusted life-year (QALY), intended to address concerns about discrimination, are suitable for informing resource allocation decisions. METHODS: We consider 2 alternatives to the QALY: the health years in total (HYT), recently proposed by Basu et al, and the equal value of life-years gained (evLYG), currently used by the Institute for Clinical and Economic Review. For completeness we also consider unweighted life-years (LYs). Using a hypothetical example comparing 3 mutually exclusive treatment options, we consider how calculations are performed under each approach and whether the resulting rankings are logically consistent. We also explore some further challenges that arise from the unique properties of the HYT approach. RESULTS: The HYT and evLYG approaches can result in logical inconsistencies that do not arise under the QALY or LY approaches. HYT can violate the independence of irrelevant alternatives axiom, whereas the evLYG can produce an unstable ranking of treatment options. HYT have additional issues, including an implausible assumption that the utilities associated with health-related quality of life and LYs are "separable," and a consideration of "counterfactual" health-related quality of life for patients who are dead. CONCLUSIONS: The HYT and evLYG approaches can result in logically inconsistent decisions. We recommend that decision makers avoid these approaches and that the logical consistency of any approaches proposed in future be thoroughly explored before considering their use in practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".