0 IS THE PRICE OF CANCER TREATMENT FALLING?
Bibliographic record
Abstract
Rationale: Cancer care represents one of the most costly sectors of medical care. Rapidly rising costs in medical care put in question the “sustainability ” of the publicly funded health care system. Given rapidly evolving medical technology, it is unclear whether it is higher prices or greater utilization that contributes more to the increase in health care system costs. Objectives: The goal of this study is to assess the impact of changing technology for cancer treatments on health care costs in order to distinguish price changes from quality/quantity changes. Methodology: We estimate two types of price indexes: a service price index (SPI) that reflects the price of particular treatments over time, and a cost-of-living index (COLI) which measures an outcome-adjusted cost of treating a specific health problem and reflects price variations by discounting any technological/quality effects. The two indexes are estimated for the period 1995/96, 2001/02 and 2002/03 by combining data on cancer patients admitted to hospitals participating in the Ontario Case Costing Initiative (OCCI) with death data from the Canadian Cancer Registry (CCR).
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".