Developing a Staff-Led Vertical Flow Model Policy in a Rural Emergency Department.

Authors

Grace F Winchester, Jennifer Rogers

Published in

Journal of emergency nursing. Aug 14, 2026. Epub Aug 14, 2026.

Abstract

Emergency department overcrowding contributes to prolonged wait times, increased mortality, and staff burnout. The vertical flow model was developed to improve patient flow and has demonstrated reductions in length of stay, door-to-provider time, and rates of patients who leave without being seen. Although it is adaptable to different emergency department settings, implementation has primarily occurred in large, urban hospitals. This project aimed to develop a staff-led policy for a modified vertical flow model tailored to a small, rural emergency department.
An anonymous survey was distributed to emergency department staff to assess perceptions of the current patient flow and perceived areas for improvement. Survey data were analyzed using descriptive statistics and used to guide the development of a modified vertical flow model policy. The proposed policy was submitted to emergency department leadership for review and was revised based on feedback.
Nearly 75% of participants rated the current patient flow as 3 or lower on a 5-point Likert scale. Participants identified reducing door-to-provider time as a key factor in improving patient flow. Major barriers included the increasing patient volume and delays in orders and discharge processes. When comparing emergency department performance metrics 6 months before and 6 months postimplementation, a decrease was found in length of stay and rates of patients who left without being seen.
A modified vertical flow model policy was developed using the waiting room as the vertical flow area and was revised due to limited provider availability to include protocol orders in triage. The revised policy was accepted by emergency department leadership, demonstrating that the model can be adapted successfully in small, rural emergency departments.

PMID:
42599252
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.