Emergency medical service (EMS) occurs in a high-pressure and error-prone environment, where paramedics must provide prompt decisions in care while recording information with limited time, incomplete data, restricted resources, and competing priorities. The EMS requires cooperative workflows between patients or caregivers, paramedics and medical centers in the community. In a conventional EMS, they have difficulties in obtaining causes of emergencies and personal medical histories, which are important for a rapid and proper response. We analyzed the requirement of a smart EMS (SEMS) system and derived the key components in connected care environments leveraging information and communication technology. A survey of paramedics (n=113) revealed that a SEMS system using IoT technology should integrate personal lifelogs, electronic medical records, and patient monitoring in ambulances into pre-hospital care recording systems. It also addressed context-awareness in the EMS accelerates first responder's activities, while supporting personalized care not only at the scene of the emergency but also during the entire hospital stay. Based on requirement analysis, we designed and implemented SEMS using health information standards to provide interoperability between devices and systems. As an application of SEMS, an example service is introduced: lifelog-connected EMS for stroke patients with a real-time location service for managing timeline of treatment.
Bibliographical noteFunding Information:
This work was supported in part by the Field-Oriented Support of Fire Fighting Technology Research and Development Program through the National Fire Agency, South Korea under Grant MPSS-2015-70, in part by the National IT Industry Promotion Agency through the Ministry of Science and ICT and Ministry of Health and Welfare under Grant C1202-18-1001, P-HIS, and in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant NRF-2017R1D1A1B03029014.
© 2013 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)