Costs of Rheumatoid Arthritis: New Estimates from the Human Capital Method and Comparison to the Willingness-to-Pay Method
Bibliographic record
Abstract
BACKGROUND: Individuals' valuation of changes in health states in monetary terms have been measured by examining changes in the direct and indirect costs of disease and by the willingness-to-pay (WTP) methodology. METHODS: In 2002, a 2-part study was conducted in Quebec. In one part of the study, 121 rheumatoid arthritis (RA) patients from the McGill University Health Centre were mailed the Stanford Cost Assessment Questionnaire, which enabled the elicitation of direct costs and indirect costs, according to the friction cost and the human capital methods. The other part was a phone survey conducted in a representative sample of the general population and in the same sample of patients, aiming to elicit the societal WTP for a complete cure of RA in the context of 2 different scenarios: a public coverage or private insurance. These estimates were then compared. RESULTS: Estimates of the cost of illness of RA ranged from 11,717 to 28,498 Canadian Dollars (CAD) depending on the method. These estimates are higher than those previously published in Canada from the 1990s, which is partly due to the recent and costly biological therapies and to a change in the measurement of productivity losses. These estimates are somewhat lower than the societal WTP elicited from the WTP survey, that is, 26,717 and 36,817 CAD per RA case, depending on the public or private health insurance context in which the cure would be available. CONCLUSION: Given that neither method is ideal, data from both methods would provide an important sensitivity analysis when monetary estimates of health state changes are required.
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.
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 | 0.017 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".