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This study aims to verify the effectiveness of the connected network for EMS comprehensive technical-support using artificial intelligence (CONNECT-AI) system through demonstration in the local community. The study was designed as a prospective non-random cross-intervention study design in two preselected communities. The subjects of the study are patients transferred to the local emergency department(ED) through an ambulance of a fire department in the selected community. If the storage and transmission of information collected by an ambulance fails or the information of the transferred patient cannot be verified in the transferred ED, it is excluded from the study. In this study, the developed CONNECT-AI system was installed in all emergency vehicles and EDs in two regional cohorts, and the effectiveness was measured by operating an intersection for the same period. The primary outcome is the transfer time spent in the pre-hospital stage, and the secondary outcome is whether the optimal transfer hospital is selected.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Case | Experimental | Emergency patient transferred by CONNECT AI system |
|
| Control | No Intervention | Emergency patient transferred by conventional EMS |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CONNECT AI system group | Other | A. During the Intervention period, paramedics wear equipment for multi-faceted data acquisition and press the start button of the system. B. During the Intervention period, inside the ambulance, a application that implements a function that automatically evaluates the patient's severity, displays a list of optimal transfer hospitals based on this, and shares real-time information of the hospitals, is installed so that paramedics can refer to the work. C. ED's medical staff will receive through ER-kiosk pre-hospital patient information collected and analyzed through the CONNECT AI system before arrival. |
| Measure | Description | Time Frame |
|---|---|---|
| transfer time spent in the pre-hospital stage | Time taken from the time the paramedic arrives at the scene to the transfer hospital | up to 1 month |
| Measure | Description | Time Frame |
|---|---|---|
| Whether to select the optimal transfer hospital | In the case of transfer to another hospital or death without resolving the emergency situation at the initial ED | up to 1 month |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Hyuk-Jae Chang | Division of Cardiology, Yonsei university college of medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Yonsei University | Seoul | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39847421 | Derived | Kim JH, Kim MJ, Kim HC, Kim HY, Sung JM, Chang HJ. A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: Community Intervention Study. J Med Internet Res. 2025 Jan 23;27:e58177. doi: 10.2196/58177. |
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