AI-support in Emergency Medicine

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorRegion Stockholm

About this trial

The purpose of this study is to investigate whether the use of generative artificial intelligence (AI) as a support tool can improve physicians' ability to establish accurate differential diagnoses in emergency care.

The main questions it aims to answer are:

* Is AI-assisted differential diagnosis more accurate than the differential diagnosis performed by physicians? * Does physicians' differential diagnosis change - in terms of the number of correct diagnoses - when they have access to AI-assisted differential diagnosis?

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Adult patients >18 years admitted through the emergency departments at Karolinska University Hospital in Huddinge and Solna.

Disqualifiers

Children <18 years

Patients without a recorded final diagnosis

Trial population

Patients admitted to the hospital via the emergency department at Karolinska University Hospital in Huddinge and Solna, Sweden.

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

Not listed

Trial groups

No trial groups listed

Trial outcomes

Primary outcomes

1

The proportion of cases in which the final diagnosis is ranked highest by the physician and by the AI support, respectively

Considering the final diagnosis after discharge from the hospital.

Time frame
At discharge from the hospital
2

The proportion of physicians' differential diagnosis that change, in terms of the number of correct diagnoses, when they have access to AI-assisted differential diagnosis

This is meassured after the patient has been discharged from the hospital

Time frame
After discharge from the hospital

Secondary outcomes

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Region Stockholm

Lead sponsor

Karolinska Institutet

Collaborator

Karolinska University Hospital

Collaborator