Healthcare Economics-Vital Threat Detection System Efficiency: A Business Process Analysis Methodology

Continuous monitoring of vital signs is a significant challenge in healthcare, particularly for individuals requiring precise and frequent follow-ups, such as elderly and chronically ill patients often resulting in delayed responses to emergencies. This research uses a business process analysis approach to propose and present “SafePulse,” a solution that utilizes a smartwatch to collect vital data such as blood pressure, heart rate, and glucose levels through the Internet of Things (IoT). The data is sent to the cloud, where it is stored and analyzed using artificial intelligence (AI) algorithms to predict critical health conditions. When any abnormalities are detected, immediate alerts are sent to family members or caregivers via mobile applications, enabling a quick response. The system provides high flexibility and scalability to accommodate a large number of users, improving healthcare quality through proactive monitoring and real-time information. After realizing and analyzing the data of KPI extracted from the “SafePulse” process, the IoT solution emerges as an effective and adaptable solution for addressing the challenges of vital sign monitoring; and this answers the main research question of this work; which is; how a business process methodology is used to analyze, implement and monitor continuous improvements of the process of continuous monitoring of vital threat signs.