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Record W2148022235 · doi:10.1177/107815520000600201

The cost of blood transfusions in cancer patients: a reanalysis of a Canadian economic evaluation

2000· article· en· W2148022235 on OpenAlexafffundabout
George Dranitsaris

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2000
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer Research
FundersCanadian Blood Services
KeywordsMedicineActivity-based costingBlood transfusionPharmacoeconomicsCancerIntensive care medicineIntensive care unitAnemiaIndirect costsEmergency medicineCost driverUnit costBlood supplyMedical emergencySurgeryInternal medicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.052
GPT teacher head0.417
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2000
Admission routes3
Has abstractyes

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