Is there a kink in consumers' threshold value for cost‐effectiveness in health care?
Bibliographic record
Abstract
BACKGROUND: A reproducible observation is that consumers' willingness-to-accept (WTA) monetary compensation to forgo a program is greater than their stated willingness-to-pay (WTP) for the same benefit. Several explanations exist, including the psychological principle that the utility of losses weighs heavier than gains. We sought to quantify the WTP-WTA disparity from published literature and explore implications for cost-effectiveness analysis accept-reject thresholds in the south-west quadrant of the cost-effectiveness plane (less effect, less cost). METHODS: We reviewed published studies (health and non-health) to estimate the ratio of WTA to WTP for the same program benefit for each study and to determine if WTA is consistently greater than WTP in the literature. RESULTS: WTA/WTP ratios were greater than unity for every study we reviewed. The ratios ranged from 3.2 to 89.4 for environmental studies (n=7), 1.9 to 6.4 for health care studies (n=2), 1.1 to 3.6 for safety studies (n=4) and 1.3 to 2.6 for experimental studies (n=7). CONCLUSIONS: Given that WTA is greater than WTP based on individual preferences, should not societal preferences used to determine cost-effectiveness thresholds reflect this disparity? Current convention in cost-effectiveness analysis is that any given accept-rejection criterion (e.g. $50 k/QALY gained) is symmetric - a straight line through the origin of the cost-effectiveness plane. The WTA-WTP evidence suggests a downward 'kink' through the origin for the south-west quadrant, such that the 'selling price' of a QALY is greater than the 'buying price'. The possibility of 'kinky cost-effectiveness' decision rules and the size of the kink merits further exploration.
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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 | 0.136 | 0.297 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".