The OMERACT Initiative. Towards a Reference Approach to Derive QALY for Economic Evaluations in Rheumatology
Bibliographic record
Abstract
Within the OMERACT Economics Workgroup, an initiative was started to work towards consensus on the approach to calculate quality-adjusted life-years (QALY) in rheumatology. We report on a first meeting May 7, 2008, in Toronto attended by rheumatologists and experts in QALY. Following a summary of an international QALY workshop of pharmacoeconomists conducted under the umbrella of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), participating experts identified a series of high-level generic principles to be considered for QALY estimations. The OMERACT workgroup then addressed specific issues rheumatologists should concentrate on in research to build consensus on QALY in rheumatology; discussion was based on results of a Web-based survey, conducted prior to the meeting, to identify attributes of a QALY considered important and approaches considered suitable for the QALY estimations in rheumatology. One priority was to further explore indirect approaches to QALY estimation as representation of patients' preference for health in clinical decisions and to explore the additional value of patients' preferences versus societal preferences in allocation decisions. The role of the different descriptive systems and their influence on the QALY, the role of the visual analog scale to value preferences, and comparison of methods to integrate utility over time were also identified as research priorities. Approaches should be easy to apply, easy to understand by different parties, reproducible, and sensitive to change.
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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 | 0.111 | 0.228 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".