Ali Pay Intelligent Navigation Applet-aided Pre-hospital Triage for Non-emergency Medical Service Patients With Acute Ischemic Stroke

Overview

According to the Bigdata Observatory platform for Stroke of China (BOSC), the proportion of patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis or endovascular treatment in China is 5.64% and 1.45% respectively. One of the important reasons for the low treatment rate is the prolonged pre-hospital and in-hospital delay. Besides, for patients receiving reperfusion therapy, the prolonged pre-treatment delay is associated with unfavorable functional outcomes. Although tons of efforts have been made to improve the efficiency of emergency medical system in the transportation of patients with AIS, little attention has been paid to patients who arrived at hospitals on their owns, which occupying approximately 2/3 of emergency patients. This leaves a huge gap in the pre-hospital management of patietns with AIS. Therefore, the investigators plan to develop an intelligent navigation system for patients with AIS. For the convenience of public use, this system was carried on the applet of Ali Pay, which has over 1.1 billion users in China. This system comprises of three functional modules, namely stroke knowledge education, stroke recognition and hospital recommendation. The investigators aim to explore whether this intelligent navigatino system could shorten pre-hospital delay and improve functional outcomes of patients with AIS undergoing reperfusion therapy.

According to the Bigdata Observatory platform for Stroke of China (BOSC), the proportion of patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis or endovascular treatment in China is 5.64% and 1.45% respectively. One of the important reasons for the low treatment rate is the prolonged pre-hospital and in-hospital delay. Besides, for patients receiving reperfusion therapy, the prolonged pre-treatment delay is associated with unfavorable functional outcomes. Although tons of efforts have been made to improve the efficiency of emergency medical system in the transportation of patients with AIS, little attention has been paid to patients who arrived at hospitals on their owns, which occupying approximately 2/3 of emergency patients. This leaves a huge gap in the pre-hospital management of patietns with AIS. Therefore, the investigators plan to develop an intelligent navigation system for patients with AIS. For the convenience of public use, this system was carried on the applet of Ali Pay, which has over 1.1 billion users in China. This system comprises of three functional modules, namely stroke knowledge education, stroke recognition and hospital recommendation.The investigators aim to explore whether this intelligent navigatino system could shorten pre-hospital delay and improve functional outcomes of patients with AIS undergoing reperfusion therapy.