ArticleContemporary clinical trials communications2023
Comparing the Safety Action Feedback and Engagement (SAFE) Loop with an established incident reporting system: Study protocol for a pragmatic cluster randomized controlled trial.
Article in Contemporary clinical trials communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- The Safety Action Feedback and Engagement (SAFE) Loop: Initial Testing and Refinement of a Novel Intervention to Enhance Hospital Incident Reporting and Patient Safety.Journal of patient safety · 2026Article
- The Safety Action Feedback and Engagement (SAFE) Loop: Initial Testing and Refinement of a Novel Intervention to Enhance Hospital Incident Reporting and Patient Safety.medRxiv : the preprint server for health sciences · 2025Article
- Training Hospital Nurses to Write Detailed Narratives and Describe Contributing Factors in Incident Reports: The SAFER Education Program.Joint Commission journal on quality and patient safety · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Background: Incident reporting is widely used in hospitals to improve patient safety, but current reporting systems do not function optimally. The utility of incident reports is limited because hospital staff may not know what to report, may fear retaliation, and may doubt whether administrators will review reports and respond effectively. Methods: This is a clustered randomized controlled trial of the Safety Action Feedback and Engagement (SAFE) Loop, an intervention designed to transform hospital incident reporting systems into effective tools for improving patient safety. The SAFE Loop has six key attributes: obtaining nurses' input about which safety problems to prioritize on their unit; focusing on learning about selected high-priority events; training nurses to write more informative event reports; prompting nurses to report high-priority events; integrating information about events from multiple sources; and providing feedback to nurses on findings and mitigation plans. The study will focus on medication errors and randomize 20 nursing units at a large academic/community hospital in Los Angeles. Outcomes include: (1) incident reporting practices (rates of high-priority reports, contributing factors described in reports), (2) nurses' attitudes toward incident reporting, and (3) rates of high-priority events. Quantitative analyses will compare changes in outcomes pre- and post-implementation between the intervention and control nursing units, and qualitative analyses will explore nurses' experiences with implementation. Conclusion: If effective, SAFE Loop will have several benefits: increasing nurses' engagement with reporting, producing more informative reports, enabling safety leaders to understand problems, designing system-based solutions more effectively, and lowering rates of high-priority patient safety events.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.