Knowledge Translation Interventions for Critically Ill Patients
Bibliographic record
Abstract
OBJECTIVE: We systematically reviewed ICU-based knowledge translation studies to assess the impact of knowledge translation interventions on processes and outcomes of care. DATA SOURCES: We searched electronic databases (to July, 2010) without language restrictions and hand-searched reference lists of relevant studies and reviews. STUDY SELECTION: Two reviewers independently identified randomized controlled trials and observational studies comparing any ICU-based knowledge translation intervention (e.g., protocols, guidelines, and audit and feedback) to management without a knowledge translation intervention. We focused on clinical topics that were addressed in greater than or equal to five studies. DATA EXTRACTION: Pairs of reviewers abstracted data on the clinical topic, knowledge translation intervention(s), process of care measures, and patient outcomes. For each individual or combination of knowledge translation intervention(s) addressed in greater than or equal to three studies, we summarized each study using median risk ratio for dichotomous and standardized mean difference for continuous process measures. We used random-effects models. Anticipating a small number of randomized controlled trials, our primary meta-analyses included randomized controlled trials and observational studies. In separate sensitivity analyses, we excluded randomized controlled trials and collapsed protocols, guidelines, and bundles into one category of intervention. We conducted meta-analyses for clinical outcomes (ICU and hospital mortality, ventilator-associated pneumonia, duration of mechanical ventilation, and ICU length of stay) related to interventions that were associated with improvements in processes of care. DATA SYNTHESIS: From 11,742 publications, we included 119 investigations (seven randomized controlled trials, 112 observational studies) on nine clinical topics. Interventions that included protocols with or without education improved continuous process measures (seven observational studies and one randomized controlled trial; standardized mean difference [95% CI]: 0.26 [0.1, 0.42]; p = 0.001 and four observational studies and one randomized controlled trial; 0.83 [0.37, 1.29]; p = 0.0004, respectively). Heterogeneity among studies within topics ranged from low to extreme. The exclusion of randomized controlled trials did not change our results. Single-intervention and lower-quality studies had higher standardized mean differences compared to multiple-intervention and higher-quality studies (p = 0.013 and 0.016, respectively). There were no associated improvements in clinical outcomes. CONCLUSIONS: Knowledge translation interventions in the ICU that include protocols with or without education are associated with the greatest improvements in processes of critical care.
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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 | 0.059 | 0.269 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".