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.
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
1,000
All patients receiving services from the physician manned rapid response car will be included
Fredrikstad Casualty
Fredrikstad, Akershus, Norway
At location
Patients treated at location
Time frame: 2 hours
Transported
Patients being transported for further diagnostics
Time frame: 2 hours
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