Variations in RBC and frozen plasma utilization rates across 62 Ontario community hospitals
Bibliographic record
Abstract
BACKGROUND: Recent province-wide audits of frozen plasma (FP) and RBC use in Ontario showed a high rate of inappropriate transfusions. STUDY DESIGN AND METHODS: This was a retrospective, ecological study to determine variations in RBC and FP utilization rates across Ontario community hospitals between 2012 and 2017. Annual utilization rates were reported using descriptive statistics. Rates of blood component use were correlated with size of hospital, presence of specialized programs, and quality improvement (QI) initiatives, using Poisson regression. RESULTS: RBC and FP utilization rates decreased from 2012 to 2017 (p = 0.03 for FP; p < 0.01 for RBC). There was a 10-fold difference in RBC and FP transfusion rates between the highest and lowest users. Smaller hospitals (p < 0.05) and sites with any QI initiative (p = 0.006) were associated with lower FP utilization rates. Hospitals without cancer programs (p = 0.02) and sites with RBC guidelines (p = 0.05) or with technologists who prospectively screened transfusion orders (p = 0.01) had lower RBC transfusion rates. RBC utilization rates decreased further after the implementation of RBC guidelines (p = 0.02) and order sets (p = 0.005). There was a positive correlation between FP and RBC transfusion rates for each fiscal year (p < 0.005 for all years). CONCLUSION: RBC and FP utilization showed wide variation across community hospitals in Ontario. Overall, transfusion rates decreased over time. A further decrease was observed at sites with QI initiatives, supporting their implementation in reducing utilization. These data will serve as a baseline to highlight sites and practices where QI initiatives may be most beneficial and replicated in other jurisdictions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".