A method for comparing and combining cost-of-illness studies: an example from cardiovascular disease.
Bibliographic record
Abstract
This paper describes a method for comparing and combining the results of various cost-of-illness (COI) studies. The method consists of seven steps: identify the study design; stratify according to the cost components; create concatenated cost components; adjust for inflation; adjust for population growth; compare cost estimates; and combine cost estimates. Based on this method, and using published data from 1986, 1993 and 1994, the cost of cardiovascular disease was estimated to be $20.1 billion in Canada in 2000, or $653 per person per year. One cost component, premature mortality, was found to have significantly decreased over time. The method described in this paper is sophisticated yet simple to use, and provides an efficient way to update, compare and combine cost estimates. By analyzing changes in cost components over time, it contributes to the projection methodology of cost information from multiple COI studies. The method greatly facilitates economic impact analyses to provide up-to-date information for healthy public policies.
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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 | 0.148 | 0.451 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".