Differences in work environment for staff as an explanation for variation in central line bundle compliance in intensive care units
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) are a common and costly quality problem, and their prevention is a national priority. A decade ago, researchers identified an evidence-based bundle of practices that reduce CLABSIs. Compliance with this bundle remains low in many hospitals. PURPOSE: The aim of this study was to assess whether differences in core aspects of work environments-workload, quality of relationships, and prioritization of quality-are associated with variation in maximal CLABSI bundle compliance, that is, compliance 95%-100% of the time in intensive care units (ICUs). METHODOLOGY/APPROACH: A cross-sectional study of hospital medical-surgical ICUs in the United States was done. Data on work environment and bundle compliance were obtained from the Prevention of Nosocomial Infections and Cost-Effectiveness Refined Survey completed in 2011 by infection prevention directors, and data on ICU and hospital characteristics were obtained from the National Healthcare Safety Network. Factor and multilevel regression analyses were conducted. FINDINGS: Reasonable workload and prioritization of quality were positively associated with maximal CLABSI bundle compliance. High-quality relationships, although a significant predictor when evaluated apart from workload and prioritization of quality, had no significant effect after accounting for these two factors. PRACTICE IMPLICATIONS: Aspects of the staff work environment are associated with maximal CLABSI bundle compliance in ICUs. Our results suggest that hospitals can foster improvement in ensuring maximal CLABSI bundle compliance-a crucial precursor to reducing CLABSI infection rates-by establishing reasonable workloads and prioritizing quality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it