The cost of blood transfusions in cancer patients: a reanalysis of a Canadian economic evaluation
Bibliographic record
Abstract
Background. Cancer patients undergoing chemotherapy are at an increased risk for anemia. Hence, they are high consumers of allogenic blood transfusions. In 1997, an economic evaluation was undertaken at the Princess Margaret Hospital to estimate the cost of a transfusion in cancer patients. The analysis relied on published costing information and on an internal review of patient resource utilization. Overall, the cost of a blood transfusion was estimated at Can$599. Since 1997, there have been some major changes in the management of Canada's blood supply and within the Princess Margaret Hospital. Methods. In order to evaluate how these changes affected the cost of a transfusion in cancer patients, the original 1997 economic database was reanalyzed using updated 1999 costing information obtained from Canadian Blood Services (CBS) and from the Princess Margaret Hospital. Results. The reanalysis suggested that the cost of a blood transfusion in cancer patients increased from Can$599 in 1997 to Can$731 in 1999. The major incremental costs responsible for this increase were additional screening tests, increased opportunity costs for donors and a modest rise in distribution and administration within the hospital. Costs that were no longer relevant in 1999 were the cost of treating transfusion-related infections. Conclusions. These results support the findings of the original publication that a unit of blood is a highly resource intensive commodity which requires that each blood unit be used appropriately. Therefore, preventative strategies that would reduce the use of blood products have to be identified and implemented.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.011 | 0.025 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".