Dynamic Erlangian Queueing Model for Telemedicine: A Hybrid Approach to Healthcare Services Efficiency - Saini, Balveer; Singh, Dharamender; Sharma, Kailash Chand (Communications in Mathematics and Applications, 2025)
In the realm of telemedicine, dynamic and priority-based service requirements are not sufficiently addressed by conventional queueing models. There is a need for more advanced and flexible queueing systems to increase the effectiveness and adaptability of telemedicine platforms. In this study, we present a Time-Dependent Erlangian Hybrid Queuing Model (TEHQM) to effectively schedule patient appointments and reduce waiting times. This approach strengthens our ability to design a telemedicine platform effectively, enhance resource allocation and staffing, facilitate the operation of a call center or help desk, oversee electronic health records (EHRs), optimize patient flow and capacity, evaluate and improve performance, and more. This strategy integrates a flexible queueing system with advanced technology such as artificial intelligence to strengthen real-time management. Furthermore, we present a case study demonstrating how TEHQM applied to flexible resource allocation significantly shortened wait times and queue lengths. We also discuss scalability, limitations, and future opportunities for enhancing telemedicine services using advanced queueing techniques. The findings of this study suggest that TEHQM can provide a robust and comprehensive framework to significantly enhance telemedicine services in real time.
Keywords: Telemedicine; TEHQM; Flexible Queueing System; Resource allocation and staffing; Real-time management