Quality in quality improvement research - a new benchmark
Bibliographic record
Abstract
CITATION: Scales DC, Dainty K, Hales B, Pinto R, Fowler RA, Adhikari NK, Zwarenstein M: A multifaceted intervention for quality improvement in a network of intensive care units: a cluster randomized trial. JAMA 2011, 305:363-72. CONTEXT: Evidence-based practices improve intensive care unit (ICU) outcomes, but eligible patients may not receive them. Community hospitals treat most critically ill patients but may have few resources to devote to quality improvement. OBJECTIVE: To determine the effectiveness of a multicenter quality improvement program to increase delivery of 6 evidence-based ICU practices. DESIGN, SETTING, AND PARTICIPANTS: Pragmatic, cluster-randomized trial among 15 community hospital ICUs in Ontario, Canada. A total of 9269 admissions occurred during the trial (November 2005 to October 2006) and 7141 admissions during a decay-monitoring period (December 2006 to August 2007). INTERVENTION: The authors implemented a videoconference-based forum including audit and feedback, expert-led educational sessions, and dissemination of algorithms to sequentially improve delivery of 6 practices. The ICUs were randomized into 2 groups. Each group received this intervention, targeting a new practice every 4 months, while acting as control for the other group, in which a different practice was targeted in the same period. MAIN OUTCOMES: The primary outcome was the summary ratio of odds ratios (ORs) for improvement in adoption (determined by daily data collection) of all 6 practices during the trial in intervention vs control ICUs. RESULTS: Overall, adoption of the targeted practices was greater in intervention ICUs than in controls (summary ratio of ORs, 2.79; 95% confidence interval [CI], 1.00-7.74). Improved delivery in intervention ICUs was greatest for semi recumbent positioning to prevent ventilator-associated pneumonia (90.0% of patient-days in last month vs. 50.0% in first month; OR, 6.35; 95% CI, 1.85-21.79) and precautions to prevent catheter-related bloodstream infection (70.0% of patients receiving central lines vs. 10.6%; OR, 30.06; 95% CI, 11.00-82.17). Adoption of other practices, many with high baseline adherence, changed little. CONCLUSION: In a collaborative network of community ICUs, a multi-faceted quality improvement intervention improved adoption of care practices.
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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 | 0.437 | 0.477 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.031 | 0.025 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.043 | 0.051 |
| Open science | 0.009 | 0.024 |
| Research integrity | 0.019 | 0.040 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".