Emergency Department Software for Reducing Overcrowding

Overseen By Mitchell Veverka, MD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Duke University

Disqualifiers: Minors, ESI class 1, pregnant, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to test new software designed to reduce emergency room overcrowding by improving waiting room care. Participants will receive care either with or without the ED management software to determine its impact. English-speaking adults who have completed lab work and are mentally clear are ideal candidates. The trial seeks to determine if this software can make emergency room visits quicker and more efficient. As an unphased trial, it offers participants the opportunity to contribute to innovative solutions that could enhance emergency room efficiency.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this software is safe for emergency department use?

A previous study tested software designed to give early warnings about crowding in hospitals. This software connects with hospital databases to predict real-time emergency department (ED) activity. By forecasting busy times, it helps improve patient care and manage resources more effectively. Although the study didn't focus on safety in the usual way, using this software poses no direct health risks to patients. Instead, it aims to enhance emergency care efficiency and safety by reducing overcrowding. No reports of negative effects have emerged from using this software, suggesting it integrates well into hospital systems and focuses on improving hospital operations rather than providing direct medical treatment. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Emergency Department (ED) management software because it has the potential to reduce overcrowding, a common challenge in emergency care. Unlike traditional methods that rely on manual processes for patient flow management, this software uses advanced algorithms to optimize the workflow and prioritize patient treatment more efficiently. By streamlining operations, the software aims to decrease wait times and improve patient outcomes, making it a promising innovation in emergency department management.

What evidence suggests that this software is effective for reducing emergency department overcrowding?

Research has shown that special software in emergency departments can help reduce overcrowding. In this trial, some participants will use the ED management software before a physician re-evaluates them, while others will receive care without the software. This software manages patient flow, moving patients through the system more efficiently. Studies have found that AI-driven systems can enhance emergency department operations, leading to better patient care. Predictive modeling, which anticipates patient needs, also helps manage resources and reduce waiting times. Overall, early evidence suggests that this software can streamline emergency department operations, potentially providing faster and better care for patients. ^{4 6 7 8 9}

Who Is on the Research Team?

Lauren Siewny, MD

Principal Investigator

Duke Health

Are You a Good Fit for This Trial?

This trial is for English-speaking adults over 18 who have completed lab work and are cognitively sound. It excludes minors, the most critically ill patients (ESI class 1), those unable to consent legally, pregnant individuals, and non-English speakers.

Inclusion Criteria

I am over 18 and have completed all required lab tests.

English is my primary language.

I am mentally clear and able to think well.

Exclusion Criteria

I am under 18 years old.

Emergency Severity Index (ESI) class 1 patients

Pregnant patients

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Intervention

Participants interact with the re-evaluation software on a tablet, while providers use the software on a desktop

Up to 1 year

Follow-up

Participants are monitored for changes in LBTC rates and disposition time

Up to 1 year

What Are the Treatments Tested in This Trial?

Interventions

• ED management software

Trial Overview The study is testing a new emergency department management software designed to improve waiting room care. Participants will use this software under observation to see if it enhances efficiency in an emergency setting.

How Is the Trial Designed?

Group I: Study Arm Experimental Treatment 1 Intervention

Patients who undergo use of the software prior to being re-evaluated by a physician

Group II: Healthy Control Active Control 1 Intervention

Patients undergo care without using the software

Who Is Running the Clinical Trial?

Duke University

Lead Sponsor

Trials

2,495

Recruited

5,912,000+

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10890971/

Strategies to Measure and Improve Emergency ... This study aims to identify and analyze strategies to enhance the structural performance of EDs, with a focus on reducing overcrowding, optimizing resource ...

2. bmcmedinformdecismak.biomedcentral.com bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-024-02704-y

Optimizing emergency department efficiency: a comparative ... This study aims to compare the efficacy of two process mining and simulation models in identifying bottlenecks and optimizing patient flow in the emergency ...

3. acep.org acep.org/siteassets/sites/acep/media/crowding/empc_crowding-ip_092016.pdf

Emergency Department Crowding: High Impact Solutions It impedes efforts of ED personnel to provide care to patients, stretching resources, delaying treatment and leading to poorer patient outcomes. It also causes ...

4. sciencedirect.com sciencedirect.com/science/article/pii/S1386505625000553

AI-driven triage in emergency departments: A review of ... AI-driven triage systems have the potential to transform ED operations by enhancing efficiency, improving patient outcomes, and supporting healthcare ...

5. i-jmr.org i-jmr.org/2023/1/e42016

The Utility of Predictive Modeling and a Systems Process ... This position paper proposes that the ED crowding problem can be optimally addressed by applying a systems approach using predictive modeling.

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10219867/

Early Warning Software for Emergency Department Crowding We present first results of a prospective crowding early warning software, that was integrated to hospital databases to create real-time predictions every hour.

7. sciencedirect.com sciencedirect.com/science/article/abs/pii/S0736467925003476

Rethinking Metrics for ED Crowding and Capacity Planning Emergency department (ED) crowding compromises patient safety and care efficiency. Most EDs assess crowding using the Annual Average (AA) ...

8. vizientinc.com vizientinc.com/insights/all/2025/from-every-angle-emergency-department-overcrowding

From Every Angle: Emergency Department overcrowding With ED volumes surging and inpatient bottlenecks worsening, hospitals must adopt bold, data-driven strategies to streamline care, expand access, and safeguard ...

9. annemergmed.com annemergmed.com/article/S0196-0644%2803%2900444-X/fulltext

A conceptual model of emergency department crowding The conceptual model of ED crowding has three interdependent components: input, throughput, and output, within an acute care system.