Data Acquisition for Connected Network for EMSs Comprehensive Technical-support Using Artificial Intelligence
NCT05939258 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 15296
Last updated 2023-07-11
Summary
Currently, the domestic emergency medical system is disconnected from the information flow between hospitals, emergency sites, and control agencies, which are participants in the emergency medical system, and there are limitations in collecting and utilizing integrated data in emergency situations \[1\]. In addition, due to the lack of manpower for emergency services at the site and the lack of a real-time patient information delivery system, sufficient data records are not made to reflect the situation at the emergency site, and emergency patient information at the pre-hospital stage is not delivered to the transfer hospital \[1\]. Records of pre-hospital patient information that are currently being prepared are often written by hand, relying on the memory of paramedics after completing patient transfer, so the data is highly inaccurate and cannot be guaranteed to be reliable\[2\]. In particular, in the case of the four major serious emergency diseases, which are called cardiac arrest, severe trauma, cardiovascular emergency, and cerebrovascular emergency, the patient information identified in the emergency stage is very important in determining the severity, so it is very important to collect real-time patient information in the field to evaluate the severity, and based on the results of this evaluation, it is possible to select a medical institution suitable for treatment \[3,4\]. In addition, in the case of these serious emergency diseases, since targeted treatment is determined to be performed within a certain time, if the medical staff of the medical institution is aware of the patient's information before the patient arrives at the hospital, it is possible to prepare in advance for emergency treatment, thereby increasing the performance rate of emergency treatment within a reasonable time \[5,6,7\].
Conditions
- Emergency Patients Being Transported by Rescue Ambulance
Sponsors & Collaborators
-
Yonsei University
lead OTHER
Principal Investigators
-
Hyuk-Jae Chang · Severance Cardiovascular Hospital
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2021-04-19
- Primary Completion
- 2021-12-31
- Completion
- 2021-12-31
Countries
- South Korea
Study Locations
More Related Trials
-
Healthy Data: Improving Health Information Quality Using Intelligent Systems
NCT05144230 ·Status: UNKNOWN
-
AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data.
NCT07312968 ·Status: ACTIVE_NOT_RECRUITING
-
Artificial Intelligence-based Voice Assessment of Children and Adults Respiratory Conditions
NCT06630078 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Real-world Effectiveness Evaluation of Clinical Decision Support System Based on Artificial Intelligence (AI-CDSS)
NCT05065931 ·Status: COMPLETED
-
Evaluation and Optimization of Telephone Triage Using Artificial Intelligence (AI) Models for the Detection of Demands for Time-dependent Pathology at the Emergency and Urgent Care Coordination Center (CCUE).
NCT07247669 ·Status: RECRUITING
-
AI-Agent for Automated Diagnosis and Predicting Using EHR and Multimodal Data
NCT06791499 ·Status: RECRUITING
-
Optimization of Medical Time in the Emergency Department: Impact of an AI-Based System on Prescription Entry
NCT07312019 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
DAISY- Diagnostic AI System for Robotic and Automated Triage and Assessment
NCT06571838 ·Status: COMPLETED
-
Improving the Accuracy of Artificial Intelligence Triage in Primary Care
NCT07237919 ·Status: RECRUITING ·Phase: NA
-
Artificial Intelligence Algorithm for the Interpretation of Traumatic Bone Radiographs
NCT07329881 ·Status: ACTIVE_NOT_RECRUITING
-
Development of an AI-based Emergency Imaging Multi-Disease Rapid Joint Screening System
NCT05974163 ·Status: UNKNOWN
-
Research and Application of Ultrasonic Intelligent Diagnosis System for Ovarian Mass
NCT06528236 ·Status: NOT_YET_RECRUITING
-
Safety and Reliability of Artificial Intelligence Driven Symptom Assessment in Children and Adolescentes
NCT04661488 ·Status: UNKNOWN
-
Study on the Medical Education Capability of the EyeTeacher Artificial Intelligence Platform
NCT06759012 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Ultrasound Image Collection for the Development of an AI Software
NCT06920277 ·Status: COMPLETED
-
Would Artificial Intelligence Reduce Delays to Nurse Response Times
NCT06043986 ·Status: RECRUITING
-
Qualitative Research Among Physicians and Junior Doctors Into the Preconditions for Implementing a CDSS Based on AI in the ICU
NCT05303025 ·Status: COMPLETED
-
Artificial Intelligence (IA) Advanced Triage Tool for G&O Emergencies
NCT05382000 ·Status: ACTIVE_NOT_RECRUITING ·Phase: NA
-
AI-Assisted Medical Decision-Making
NCT06846229 ·Status: RECRUITING
-
Evaluating the Use of Artificial Intelligence to Improve Family Conversations for Intensive Care Patients and Their Families
NCT06756542 ·Status: RECRUITING
-
Artificial Intelligence-Generated Written Communication for Families of Intensive Care Unit Patients
NCT06969196 ·Status: COMPLETED ·Phase: NA
-
Virtual Assistant for Plastic Surgery Patients
NCT04017351 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Artificial Intelligence-Based Emergency Triage Education Tool in Enhancing Clinical Critical Thinking and Triage Practice
NCT06811987 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Artificial Intelligence (AI) in Cardiotocography (CTG) Interpretation
NCT04584281 ·Status: UNKNOWN
-
Assessment of Educational Effect of Home-made Robotic Surgery Simulator for Novice Robotic Surgeons
NCT03067532 ·Status: COMPLETED ·Phase: NA