Costs Associated with Erythropoiesis-Stimulating Agent Administration to Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND: Treatment of anemia in hemodialysis patients usually requires the use of expensive erythropoietic proteins. Cost analyses usually focus on drug acquisition costs. Other costs associated with anemia therapy include resources for anemia monitoring as well as preparation and administration of an erythropoiesis-stimulating agent. METHODS: The nonacquisition costs associated with subcutaneous administration of epoetin alfa were determined in a Canadian hemodialysis unit. A time-and-motion technique was used to determine the nursing time for preparation and administration. Fixed anemia costs were inventory control, monitoring, blood sampling, and laboratory analysis. Variable costs were those which varied with dosing frequency. The costs are expressed in Canadian dollars (2005). RESULTS: The mean time associated with preparation and administration was 3.2 min/injection. The annual nonacquisition per patient cost was CAD 2,290.04. Fixed costs were CAD 1,946.01, while the variable costs were CAD 344.03/year. Sensitivity analysis showed a decrease in cost to CAD 1,611.34, if iron monitoring were decreased from monthly to 3 monthly, and to CAD 2,090.66, if patients were converted to less frequent dosing using darbepoetin alfa. CONCLUSIONS: The nonacquisition costs associated with anemia therapy in hemodialysis patients are considerable. Less frequent monitoring of iron therapy and less frequent dosing could decrease costs by CAD 678.40 and CAD 199.38/patient/year, respectively.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".