Emergency Medical Communication CentresSIA-REMUNCT04953845
Artificial Intelligence System in Medical Regulation
An observational study of Emergency Medical Communication Centres and Call Management, run by Centre Hospitalier Universitaire de Besancon.
Trial summary
Population health needs are increasing. Information and communication technologies are changing. The digital shift offers new opportunities for the exploration and analysis of mass health data. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Emergency Medical Communication Centres, Call Management
- How many people
- 500,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Sep 2021to 30 Sep 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
Study population: all patient which call the emergency medical communication centres
Who may be able to join
- all patient which call the emergency medical communication centres
Who cannot join
- patient opposed to the study
About this study
Official title: Artificial Intelligence System for the Medical Regulation of Emergencies
Population health needs are increasing. Information and communication technologies are changing. The digital shift offers new opportunities for the exploration and analysis of mass health data. It is possible to rely on these new technologies to modernize, optimize patient management at the level of emergency medical communication centres.
Our project aims to integrate the methods and tools of artificial intelligence for emergency medical communication centres. The system aims to help regulate emergency calls at CRRA 15 in France, or Centrale 144 in Switzerland, to assess the severity of calls, identify care pathways, and improve efficiency when committing resources.
The development of such a system is aimed at securing and optimising the information system and the means of telecommunication used in the emergency medical communication centres, and provide an individualized response to the patient management.
What is being measured
The primary outcome is the main question the study is designed to answer.
Performance (sensitivity and specificity) of the artificial intelligence system in Emergency medical Communication Centres, concerning time sensitive disease
Once the artificial intelligence system in place, the diagnosis suspected by this system will be compared to the diagnosis validated in the medical record of each patient included. It will then be measured the performance values, such as sensitivity, specificity, positive and negative predictive value, time of identification of the pathology type time sensitive.
These results will then be compared to the usual practice of the Emergency medical Communication Centres without the help of the software to evaluate:
- the added value of the software for the patient,
- the added value of the call center through the quality indicators (intake rate, quality of service, load rate, average call duration, productivity)
Measured: through study completion, average 3 years
Secondary outcomes (1)
Patient transport time
The aim is to identify and model the available resources that can be used in the context of pre-hospital rescue (ambulances, helicopter, SMUR).
The following elements will be taken into consideration: location of intervention, access, clinical condition of the patient, weather conditions, traffic density.
The validity of the model will be evaluated through the access time to the patient, the transport time, the lack of ambulances or SMUR, comapred to the usual practice of the Emergency medical Communication Centres without the help of the software.
Measured: through study completion, average 3 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Jul 2021
- Study start1 Sep 2021 (estimated)
- Primary completion30 Sep 2024 (estimated)
- Study completion30 Sep 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Emergency Medical Communication CentresStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 500,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire de Besancon
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04953845
- Sponsor's protocol ID
- 2021/591
- Acronym
- SIA-REMU
- Status last verified
- Mar 2021
- First submitted
- 15 Jun 2021
- Last updated
- 8 Jul 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence System for the Medical Regulation of Emergencies
- ClinicalTrials.gov ID
- NCT04953845
- Acronym / sponsor ID
- SIA-REMU / 2021/591
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 500,000 participants (estimated)
- Lead sponsor
- Centre Hospitalier Universitaire de BesanconUniversity, hospital or other
- Study start
- 1 Sep 2021 (estimated)
- Primary completion
- 30 Sep 2024 (estimated)
- Study completion
- 30 Sep 2025 (estimated)
- First posted
- 8 Jul 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Population health needs are increasing. Information and communication technologies are changing. The digital shift offers new opportunities for the exploration and analysis of mass health data. It is possible to rely on these new technologies to modernize, optimize patient management at the level of emergency medical communication centres.
Our project aims to integrate the methods and tools of artificial intelligence for emergency medical communication centres. The system aims to help regulate emergency calls at CRRA 15 in France, or Centrale 144 in Switzerland, to assess the severity of calls, identify care pathways, and improve efficiency when committing resources.
The development of such a system is aimed at securing and optimising the information system and the means of telecommunication used in the emergency medical communication centres, and provide an individualized response to the patient management.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- all patient which call the emergency medical communication centres
Key inclusion criteria (1 listed)
- all patient which call the emergency medical communication centres
Key exclusion criteria (1 listed)
- patient opposed to the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Performance (sensitivity and specificity) of the artificial intelligence system in Emergency medical Communication Centres, concerning time sensitive disease
Time frame: through study completion, average 3 years
Once the artificial intelligence system in place, the diagnosis suspected by this system will be compared to the diagnosis validated in the medical record of each patient included. It will then be measured the performance values, such as sensitivity, specificity, positive and negative predictive value, time of identification of the pathology type time sensitive. These results will then be compared to the usual practice of the Emergency medical Communication Centres without the help of the software to evaluate: * the added value of the software for the patient, * the added value of the call center through the quality indicators (intake rate, quality of service, load rate, average call duration, productivity)
1 secondary outcome
Patient transport time
Time frame: through study completion, average 3 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jul 2021.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Emergency Medical Communication Centres and Call Management, run by Centre Hospitalier Universitaire de Besancon.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 Jul 2021. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Performance (sensitivity and specificity) of the artificial intelligence system in Emergency medical Communication Centres, concerning time sensitive disease (time frame: through study completion, average 3 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Jul 2021.