Digital, Innovative, Sustainable, and Knowledge-based Acute Municipal Healthcare Services Illness and Trauma
August 4, 2025 updated by: Ostfold University College
Developing and Implementing Digital, Innovative, Sustainable, and Knowledge-based Municipal Healthcare Services in Acute Illness and Trauma
Through introducing physicians in front in the medical assessment and decision-making processes in acute and sub-acute illness in the municipalities, as well as including machine learning in analyzing prospective and retrospective data, the project will develop and implement innovative and knowledge-based digital diagnostic tools and decision-making support systems to be used in the municipalities.
As such, the project will contribute to early identification of severe illness, prevent deterioration of disease, and facilitate early medical intervention.
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Detailed Description
The overall objective of the project is to determine if and how innovative digital decision-making tools based on artificial intelligence (AI) can help to develop more accessible, efficient, cost-effective, and sustainable municipal healthcare services. More specifically, the project aims are:
- to explore different outcomes of a municipal rapid response car manned with dedicated physicians
- to compare outcomes from Norwegian and Swedish out-of-hospital EMS in acute illness
- to explore how decision-making tools based on AI can be used to optimize dispatch
- to explore how decision-making tools based on AI can assist dispatched personnel and in prehospital care
- to determine the quality and efficacy of the different systems explored through cost-analyses and exploration of stakeholders' experiences with the decision-making tools
Study Type
Observational
Enrollment (Actual)
1000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Viken
-
Fredrikstad, Viken, Norway, 1671
- Fredrikstad Casualty
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
All patients recieving services from the physician manned rapid response car will be included.
Description
Inclusion Criteria:all patients receiving services from the physician manned rapid response car -
Exclusion Criteria:none
-
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Acutely ill persons in the municipality
Patients recieving services from a rapid response vehicle manned with dedicated physicians from the municipality
|
All patients receiving services from the physician manned rapid response car will be included
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
At location
Time Frame: 2 hours
|
Patients treated at location
|
2 hours
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Transported
Time Frame: 2 hours
|
Patients being transported for further diagnostics
|
2 hours
|
Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Institutionalized
Time Frame: 12 hours
|
Patients being institutionalized
|
12 hours
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Investigators
- Study Chair: Randi M Sommerfelt, PhD, Østfold University College
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
October 1, 2022
Primary Completion (Actual)
January 1, 2025
Study Completion (Actual)
January 1, 2025
Study Registration Dates
First Submitted
January 23, 2023
First Submitted That Met QC Criteria
January 23, 2023
First Posted (Actual)
February 1, 2023
Study Record Updates
Last Update Posted (Actual)
August 8, 2025
Last Update Submitted That Met QC Criteria
August 4, 2025
Last Verified
August 1, 2025
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 971 567 376
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
YES
IPD Plan Description
The goal is to publish anonymized datasets.
ØUC is an institutional member of the DataverseNO community in Norway, and the DataverseNO-based repository ØUC Open Research Data, which is a generic repository of high quality, is suitable for this endeavor.
A part of the data generated by this research project consists of qualitative interviews.
In case these data cannot be anonymized, open publication of data will be refrained and rather opt for making metadata available.
Datasets and metadata will be published in connection with open access publication of research articles.
IPD Sharing Time Frame
After all publication
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- CSR
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.