ABSTRACT
Managing
patient queues in hospitals is a persistent challenge that affects both the
quality of patient care and the efficiency of hospital operations. Patients
often experience prolonged waiting times, while staff face difficulty in resource
allocation and managing unexpected surges in patient flow. Existing queue
management systems frequently lack transparency, leaving patients uncertain
about their position in line and estimated wait times, which can lead to
frustration and dissatisfaction. Furthermore, without automated systems,
hospital administrators struggle to gather meaningful data to assess and
improve service quality, ultimately impacting the healthcare experience. To
address these issues, this study presents the design and implementation of Automated
Queue Management System (AQMS) tailored to the needs of hospitals. The AQMS is
intended to streamline the patient queuing process, reduce wait times, and
enhance overall patient satisfaction by leveraging modern web-based technologies.
This system was developed using the MERN stack (MongoDB, Express.js, React, and
Node.js), chosen for its scalability and efficiency in handling high volumes of
real-time data. MongoDB, as a NoSQL database, enables flexible data management,
while Express.js and Node.js support the backend processes that update queue
information instantly. The front end, developed with React, offers an intuitive
and responsive interface, allowing patients to easily view their queue position
and estimated wait time, and enabling staff to manage queue data seamlessly. An
Agile development methodology was adopted to facilitate iterative improvements
based on ongoing feedback from stakeholders, which allowed for continuous
enhancements in the system’s design and functionality. Key features of the AQMS
include a user-friendly check-in process, real-time queue updates for patients,
and a reporting module that provides insights for hospital management to make
informed, data-driven decisions. The system was tested extensively, showing
notable improvements in hospital queuing efficiency and patient experience.
Specifically, the AQMS contributed to a 40% reduction in average patient wait
times, a 25% increase in staff productivity related to patient flow management,
and a 35% improvement in patient satisfaction based on initial feedback.
-- (2024). Design And Implementation Of Automated Queue Management System:- Dickson Peter C. Mouau.afribary.org: Retrieved Dec 24, 2024, from https://repository.mouau.edu.ng/work/view/design-and-implementation-of-automated-queue-management-system-dickson-peter-c-7-2
--. "Design And Implementation Of Automated Queue Management System:- Dickson Peter C" Mouau.afribary.org. Mouau.afribary.org, 21 Nov. 2024, https://repository.mouau.edu.ng/work/view/design-and-implementation-of-automated-queue-management-system-dickson-peter-c-7-2. Accessed 24 Dec. 2024.
--. "Design And Implementation Of Automated Queue Management System:- Dickson Peter C". Mouau.afribary.org, Mouau.afribary.org, 21 Nov. 2024. Web. 24 Dec. 2024. < https://repository.mouau.edu.ng/work/view/design-and-implementation-of-automated-queue-management-system-dickson-peter-c-7-2 >.
--. "Design And Implementation Of Automated Queue Management System:- Dickson Peter C" Mouau.afribary.org (2024). Accessed 24 Dec. 2024. https://repository.mouau.edu.ng/work/view/design-and-implementation-of-automated-queue-management-system-dickson-peter-c-7-2