Developing a tracking system for coagulation factor concentrates in southern Ontario
Bibliographic record
Abstract
BACKGROUND: In response to the transfusion- transmitted AIDS epidemic, Canadian authorities recommended the development of tracking systems and improved reporting of adverse events. This study describes the development of a verifiable and comprehensive regional tracking system for coagulation factor concentrates. STUDY DESIGN AND METHODS: The Hamilton- Niagara Regional Hemophilia Program received distribution and utilization data from Canadian Blood Services, 26 regional hospitals, and 70 individuals with bleeding disorders on home-based therapy. Purpose-specific software, the Canadian Hemophilia Assessment and Resource Management System (CHARMS), was used to store, monitor, analyze, and validate data. RESULTS: During a 1-year period (2001), all factor concentrates distributed in this region were accounted for. A higher proportion of FVIII and FIX concentrates (88 vs. 12%) was infused at home than in hospitals, and a higher proportion (63 vs. 28%) was used to prevent than to treat bleeds. During a period of shortage, a 5-percent reduction in utilization of both FVIII and FIX concentrates was documented. One recall was managed swiftly and efficiently. Two patients reported allergic skin reactions. CONCLUSION: A verifiable tracking system has been developed that can provide ongoing data for both clinical and administrative purposes. Data collection from patients needs to be made more efficient and real-time recording is an important future objective. Such a system can be instituted locally for less than 1.5 percent of the cost of the factor concentrate used.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".