Artificial Intelligence (AI) Support in Medical Emergency Calls

NCT04648449 | Active Not Recruiting

• 1 other identifier: 108573
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

More than 12.000 patients suffer acute stroke in Norway every year, but less than half of them reach hospital within the current treatment window for thrombolysis. Stroke is the third-highest cause of death and the number one cause of severe disability requiring long time care at institutions. Consequently this has a high impact on society, patients and relatives, in addition to high costs related to care estimated to approximately 10 billion NOK per year. Although there are few studies on emergency medical communication centres (EMCC) in Norway, some have shown that the performance of the emergency medical communication centres can be improved. This project will seek to amend EMCC´s handling of acute stroke inquiries using artificial intelligence (AI), thus contributing to getting the patient to hospital in time for optimal treatments.

Conditions

Stroke, Acute; Apoplexy; Brain; Emergencies; Communication, Multidisciplinary

Keywords

EMCC; Stroke; Apoplexy; Emergency Medical Service Communication Systems; Dispatch; Artificial intelligence; Machine learning

Outcome Measures

Primary Outcomes (1)

• Stroke recognition in medical emergency calls

  Survey AI's ability to recognize stroke, compared to the current system

  Sept. 22 - Sept. 23

Interventions

Artificial intelligence on emergency calls OTHER

AI listens to all calls to Bergen EMCC, detecting calls regarding possible stroke.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All calls to 113 in Bergen will be subject to the AI. A warning will be given the EMCC-operator if risk of stroke, when combining contents in the call and historical data in the hospital record, exceeds a certain limit.

You may qualify if:

• All callers to medical emergency number 113 in Bergen

You may not qualify if:

• Age \<18

Sponsors & Collaborators

• Haukeland University Hospital: lead
• Helse Vest: collaborator
• Western Norway University of Applied Sciences: collaborator
• Oslo University Hospital: collaborator
• The Norwegian Heart and Lung Patient Organization: collaborator
• Helsetjenestens driftsorganisasjon for nødnett HF (HDO): collaborator
• The Norwegian Stroke Register: collaborator

Study Sites (1)

Haukeland Universitetssykehus, Kirurgisk serviceklinikk, Nasjonalt kompetansesenter for helsetjenestens kommunikasjonsberedskap

Bergen, Bergen, 5021, Norway

Location

MeSH Terms

Conditions

Stroke; Emergencies; Communication

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Behavior

Study Officials

• Guttorm Brattebo, Professor II

  Haukeland University Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 23, 2020
• First Posted: December 1, 2020
• Study Start: September 1, 2020
• Primary Completion (Estimated): August 31, 2026
• Study Completion (Estimated): August 31, 2026
• Last Updated: September 22, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will not share

Locations

NO (1)