Cost of illness: An international comparison Australia, Canada, France, Germany and The Netherlands
Bibliographic record
Abstract
Objectives To assess international comparability of general cost of illness (COI) studies and to examine the extent to which COI estimates differ and why.Methods Five general COI studies were examined. COI estimates were classified by health provider using the system of health accounts (SHA). Provider groups fully included in all studies and matching SHA estimates were selected to create a common data set. In order to explain cost differences descriptive analyses were carried out on a number of determinants.Results In general similar COI patterns emerged for these countries, despite their health care system differences. In addition to these similarities, certain significant disease-specific differences were found. Comparisons of nursing and residential care expenditure by disease showed major variation. Epidemiological explanations of differences were hardly found, whereas demographic differences were influential. Significant treatment variation appeared from hospital data.Conclusions A systematic analysis of COI data from different countries may assist in comparing health expenditure internationally. All cost data dimensions shed greater light on the effects of health care system differences within various aspects of health care. Still, the study's objectives can only be reached by a further improvement of the SHA, by international use of the SHA in COI studies and by a standardized methodology.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".