Home // International Journal On Advances in Networks and Services, volume 11, numbers 3 and 4, 2018 // View article
Authors:
Khulood Alghamdi
Shada Alsalamah
Ghada Al-Hudhud
Thamer Nouh
Ibrahim Alyahya
Sakher AlQahtani
Keywords: mHealth; Emergency medical services; Emergency department; Dijkstra algorithm; Fusion algorithm.
Abstract:
Ambulance diversion in overcrowded hospitals and Emergency Departments (EDs) can have negative consequences on patients' health and safety. Saudi Arabia is thriving to enhance its healthcare sector through an ongoing digitization transition as part of Vision 2030. However, existing infrastructure is still ill-equipped to integrate the distributed siloed systems involved in hospital bed and Emergency Medical Services (EMSs) ecosystem leading to delayed decisions and poor outcomes based on incomplete and inaccurate information. This article addresses this problem by proposing, mEmergency, a smart proactive mobile healthcare solution that connects EMS ambulances with EDs in Riyadh trauma centers to facilitate making real-time informed decisions in a timely fashion to save lives. First, mEmergency predicts inpatient bed capacity using Fusion Algorithm and prioritizes the nearest and most equipped ED for the patient’s condition to paramedics using a mHealth application. Second, it uses Dijkstra’s Algorithm to route the ambulance path taken to the right ED, while the patient’s vital signs are being recorded into the solution along with physical assessment. Finally, mEmergency disseminates the paramedic’s assessment information to the ED prior to arrival to optimize time and resources for continuous readiness. mEmergency is an effective solution that should optimize EMS resources, reduce ED crowding, and increase the quality of urgent care services to help stakeholders regain trust in Saudi urgent care service delivery.
Pages: 92 to 102
Copyright: Copyright (c) to authors, 2018. Used with permission.
Publication date: December 30, 2018
Published in: journal
ISSN: 1942-2644