Effectiveness of interventions for the implementation of thromboprophylaxis in hospitalised patients at risk of venous thromboembolism: an updated abridged Cochrane systematic review and meta-analysis of randomised controlled trials
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of system-wide interventions designed to increase the implementation of thromboprophylaxis and decrease the incidence of venous thromboembolism (VTE) in hospitalised medical and surgical patients at risk of VTE. DESIGN: Systematic review and meta-analysis of randomised controlled trials (RCTs). DATA SOURCES: Medline, PubMed, Embase, BIOSIS, CINAHL, Web of Science, CENTRAL, DARE, EED, LILACS and clinicaltrials.gov without language restrictions from inception to 7 January 2017, as well as the reference lists of relevant review articles. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: RCTs that evaluated the effectiveness of system-wide interventions such as alerts, multifaceted, education, and preprinted orders when compared with no intervention, existing policy or another intervention. RESULTS: We included 13 RCTs involving 35 997 participants. Eleven RCTs had data available for meta-analysis. Compared with control, we found absolute increase in the prescription of prophylaxis associated with alerts (21% increase, 95% CI [15% to 275%]) and multifaceted interventions (4% increase, 95% CI [3% to 11%]), absolute increase in the prescription of appropriate prophylaxis associated with alerts (16% increase, 95% CI [12% to 20%]) and relative risk reductions (risk ratio 64%, 95% CI [47% to 86%]) in the incidence of symptomatic VTE associated with alerts. Computer alerts were found to be more effective than human alerts, and multifaceted interventions with an alert component appeared to be more effective than multifaceted interventions without, although comparative pooled analyses were not feasible. The quality of evidence for improvement in outcomes was judged to be low to moderate certainty. CONCLUSIONS: Alerts increased the proportion of patients who received prophylaxis and appropriate prophylaxis, and decreased the incidence of symptomatic VTE. Multifaceted interventions increased the proportion of patients who received prophylaxis but were found to be less effective than alerts interventions. TRIAL REGISTRATION NUMBER: CD008201.
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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 | 0.035 | 0.109 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.038 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".