ArticleJoint Commission journal on quality and patient safety2014
Using the red/yellow/green discharge tool to improve the timeliness of hospital discharges.
Article in Joint Commission journal on quality and patient safety, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Defining Delayed Discharges of Inpatients and Their Impact in Acute Hospital Care: A Scoping Review.International journal of health policy and management · 2022Article
- Multi-Disciplinary Discharge Coordination Team to Overcome Discharge Barriers and Address the Risk of Delayed Discharges.Risk management and healthcare policy · 2022Article
- The Effectiveness of a Multidisciplinary Electronic Discharge Readiness Tool: Prospective, Single-Center, Pre-Post Study.JMIR human factors · 2021Article
- Introducing an electronic tracking tool into daily multidisciplinary discharge rounds on a medicine service: a quality improvement project to reduce length of stay.BMJ open quality · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundAs part of Yale-New Haven Hospital (Connecticut)'s Safe Patient Flow Initiative, the physician leadership developed the Red/Yellow/Green (RYG) Discharge Tool, an electronic medical record-based prompt to identify likelihood of patients' next-day discharge: green (very likely), yellow (possibly), and red (unlikely). The tool's purpose was to enhance communication with nursing/care coordination and trigger earlier discharge steps for patients identified as "green" or "yellow."
methodsData on discharge assignments, discharge dates/ times, and team designation were collected for all adult medicine patients discharged in October-December 2009 (Study Period 1) and October-December 2011 (Study Period 2), between which the tool's placement changed from the sign-out note to the daily progress note.
resultsIn Study Period 1, 75.9% of the patients had discharge assignments, compared with 90.8% in Period 2 (p < .001). The overall 11 A.M. discharge rate improved from 10.4% to 21.2% from 2007 to 2011. "Green" patients were more likely to be discharged before 11 A.M. than "yellow" or "red" patients (p < .001). Patients with RYG assignments discharged by 11 A.M. had a lower length of stay than those without assignments and did not have an associated increased risk of readmission. Discharge prediction accuracy worsened after the change in placement, decreasing from 75.1% to 59.1% for "green" patients (p < .001), and from 34.5% to 29.2% (p < .001) for "yellow" patients. In both periods, hospitalists were more accurate than house staff in discharge predictions, suggesting that education and/or experience may contribute to discharge assignment.
conclusionsThe RYG Discharge Tool helped facilitate earlier discharges, but accuracy depends on placement in daily work flow and experience.
Indexed as
Identifiers
What OpenQuestion holds
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.