REMOTE PATIENT MONITORING SYSTEM (RPMS) MODEL TO IMPROVE EMERGENCY SERVICES IN PAKISTAN DURING COVID 19 - A CONCEPTUAL FRAMEWORK USING ICT TOWARDS OVERCOMING HEALTHCARE PROBLEMS IN PANDEMIC HISTORY
ARPN Journal of Engineering and Applied Sciences
; 16(12):1303-1311, 2021.
Article
in English
| Scopus | ID: covidwho-1414366
ABSTRACT
The history of the world during the pandemic era shows a worse kind of treatment to the effected people. The year 2020 is known as a terrifying year due to pandemics in the world. It badly exposes the healthcare system's weakness especially in the developing countries like Pakistan. Ambulance services played a major role in transporting affected people during pandemics. However, an independent survey shows that around 130 million people have very limited access to these facilities in Pakistan. The majority of the population of Pakistan lives in remote and rural areas and is deprived of these services. In this regard, remote monitoring of patients while they are in transit is very crucial. Considering the importance of providing better healthcare services to patients, we propose a model for remote patient monitoring systems (RPMS) integrated with emergency services in Pakistan. This healthcare model continuously keeps track of people including patients and nearest ambulances (the in-context emergency service and the key resource) for helping patients by transporting them to the appropriate healthcare center, as per needed assistance on the go. It helps reducing response time and yet increasing golden time by directly engaging the ambulance from the nearest location (using spatial and temporal features) and bypassing the call center to save the inevitable consumption of time shattered by conventional method. The represented model may enhance the availability of emergency healthcare facilities by reducing service time and allow efficient use of resources. © 2021 Asian Research Publishing Network (ARPN). All Rights Reserved.
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Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
ARPN Journal of Engineering and Applied Sciences
Year:
2021
Document Type:
Article
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