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AI could revolutionize ER triage and cut wait times

NCT ID NCT07312968

Knowledge-focused Sponsor: University of Catanzaro Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study explores whether artificial intelligence can help emergency rooms sort patients more accurately and predict how long they will stay. Researchers will analyze data from 1,500 patients to see if AI models can reduce mistakes in triage. The goal is to develop tools that help doctors make faster, better decisions in busy ERs.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to AI tools that help emergency rooms sort patients more accurately and manage resources better.
What could go wrong
This is an early observational study, so the AI may not work as well in real-world settings or may not improve outcomes significantly.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

1,500 people

The number who actually took part.

Started

Nov 2025

Expected to finish

Nov 2027

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

All individuals who request access to the ER will be duly considered.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * all Exclusion Criteria: * Patients labelled with red codes and serious injuries.

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As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

TRIAGE

Contacts and locations

Locations

  • University of Catanzaro

    Catanzaro, Italy

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