Evaluation of Interventions for Implementation of Thromboprophylaxis in Hospitalized Medical and Surgical Patients At Risk for Venous Thromboembolism: A Systematic Review and Metaanalysis
Bibliographic record
Abstract
Abstract Abstract 676 Introduction: Venous thromboembolism (VTE) is a leading cause of morbidity and mortality in hospitalized patients. Numerous randomized clinical trials (RCTs) show that the use of thromboprophylaxis in hospitalized patients at risk for VTE is safe, effective and cost-effective. Despite this, prophylactic therapies for VTE are underutilized. System-wide interventions may be more effective to improve the use of VTE prophylaxis than relying on individual providers' prescribing behaviors. Objectives: In this review, we aimed to determine the effectiveness of various system-wide interventions designed to increase the use of thromboprophylaxis in hospitalized medical and surgical patients at risk for VTE. Methods: We searched MEDLINE, EMBASE, and SCOPUS databases to identify studies that assessed an intervention designed to increase use of prophylaxis and/or decrease incidence of VTE. Extracted data included study design, setting, intervention, and outcomes including proportions receiving prophylaxis (RP) and receiving appropriate prophylaxis (RAP). Risk of bias was assessed using Cochrane guidelines. We performed meta-analysis for RCTs and non-randomized studies (NRS) separately. We categorized the interventions into three groups: education (e.g. grand rounds, self-administered course), alerts (e.g. electronic, human), and multifaceted interventions (e.g. combination of education, audit and feedback and alert). We performed a random effects meta-analysis and assessed heterogeneity using the I2 statistic. Results were pooled if three or more studies were available for a particular intervention group. Results: Out of 1802 records included in our primary screen of titles and abstracts, 79 studies were assessed for eligibility. Fifty-six studies were included in our systematic review, including eight RCTs (N=17,601) and 48 NRS (N=62,770). Among the RCTS, 4 studies included medical patients, 2 included medical and surgical patients, 1 included post-acute care patients and 1 did not report the types of patients included. The NRS were primarily before-and-after design. Fourteen included surgical patients, 10 included medical patients, 10 included medical and surgical patients, 8 included patients from other departments and 6 did not report the types of patients included. Our primary outcomes included received prophylaxis (RP) and received appropriate prophylaxis (RAP). Among the RCTs, there was sufficient data to pool one outcome (RP) for one intervention type (alert). Among the NRS, there was sufficient data to pool two outcomes (RP, RAP) for each intervention type (education, alert, multifaceted). I2 results showed substantial statistical heterogeneity among studies. A sensitivity analysis showed that multifaceted interventions which included an alert were more effective at improving rates of RP and RAP than those without an alert. Conclusions: We reviewed a large number of studies which implemented a variety of system-wide strategies aimed to improve thromboprophylaxis rates in many settings and patient populations. We found statistically significant improvements in prescription of prophylaxis associated with alerts and multifaceted interventions, and improvements in prescription of appropriate prophylaxis with the use of education, alerts or multifaceted interventions. Multifaceted interventions with an alert component seem to be the most effective. We chose to pool effect estimates despite significant heterogeneity because the results were generally in the same direction but of different magnitudes. We are continuing to investigate sources of heterogeneity including patient population, setting, baseline prophylaxis rates, and intervention characteristics. The results of our review will help physicians, hospital administrators and policy makers make practical decisions about adoption of specific system-wide measures to improve prevention of VTE. Funded by Canadian Institutes for Health Research Disclosures: Kahn: sanofi aventis: Honoraria, Research Funding; Leo Pharma: Honoraria.
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.044 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".