Anticoagulation stewardship: Improving adherence to clinical guidelines and reducing overuse of venous thromboembolism prophylaxis in hospitalized medical patients
Bibliographic record
Abstract
Adherence to guideline recommendations for venous thromboembolism prophylaxis (VTE) in hospitalized medical patients is suboptimal despite national policies and institutional interventions. The aim of this quality improvement project was to improve adherence to guidelines and decrease the overuse of VTE prophylaxis in order to reduce the institutional cost for heparins. A multidisciplinary anticoagulation stewardship program (ACSP) using the audit and feedback strategy was implemented on the medicine inpatient units at a teaching hospital in Canada. The primary outcome measure was a comparison, pre and post introduction of the ACSP, of the costs per 6-month period for prophylactic dose enoxaparin and unfractionated heparin on the medicine units. The balancing measures were the 90-day VTE rate and major bleeding rate during the hospitalization. Six months after the implementation of the ACSP, the cost was decreased by >50 % without any observed negative impact on patient safety. This study demonstrates the potential for anticoagulation stewardship programs to optimize the use of VTE prophylaxis and reduce the associated costs and risks.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".