Pharmacist Integration into the Hemophilia Treatment Centre: A Canadian Pilot Project to Optimize Treatment and Improve Cost-savings
Bibliographic record
Abstract
Coagulation factors used in prophylactic treatment of patients with clotting disorders are associated with significant costs to health care systems. These products have complex pharmacokinetic profiles subject to large inter-individual variation making their efficient use challenging. Prior to this project, pharmacists were not involved as part of the Hemophilia care teams across Canada. The purpose of this pilot project was to determine whether employment of a pharmacist with expertise and a focus on plasma protein and related products including hemophilia treatments, would be an effective strategy to reduce costs associated with clotting factor prophylaxis regimens and identify the pharmacist’s activities associated with this new role. A cost-minimization analysis was conducted to compare the addition of a pharmacist to the care team of the Hemophilia Treatment Centre (HTC) at a pediatric hospital serving 500,000 children and youth. The analysis was performed from the perspective of the formulary manager, Canadian Blood Services, over a 1-year period including 9 months of interventions. The pharmacist performed 18 therapeutic optimizations on 14 patients with moderate to severe hemophilia A or B, and 1 von Willebrand patient, aged 3 to 18 years old. As a result of the pharmacist’s intervention, clotting factor treatment costs extrapolated over one year were reduced by 20.5% for these patients. This represents a net savings of $225K CAD/year, or $12.5K CAD/optimization/year. The addition of a pharmacist to the HTC to manage recombinant and plasma-derived coagulation factors can optimise the treatment plan and significantly reduce the costs of managing patients with hemophilia.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 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".