Outpatient departments in most small and mid-sized hospitals still rely on manual token counters, first-come-first-served queues, and telephone-based appointment booking. This creates long, unpredictable waiting times, clustering of patients at clinic opening hours, high front-desk workload, and a persistently high rate of missed appointments. The Medi-Queue system was conceived to address these operational gaps through a unified, mobile-and-web-based platform that lets patients book appointments, join a live virtual queue, and receive real-time wait-time updates, while giving hospital staff a dashboard to monitor, re-sequence, and forecast patient flow.

The objective of this study is to design, implement, and evaluate a smart queue and appointment management system that reduces patient waiting time, lowers appointment no-show rates, and improves the utilisation of doctor consultation slots without requiring new hardware investment by the hospital. The system was built using a three-tier architecture — a patient-facing mobile/web application, a Node.js/REST middleware layer, and a cloud-hosted relational database — augmented with a lightweight machine-learning module that forecasts consultation duration and dynamically re-orders the queue. A pilot was carried out across five outpatient departments of a multi-specialty hospital over an eight-week period, comparing operational metrics against the pre-existing manual system.

Results from the pilot show that average patient waiting time fell by nearly 57%, the appointment no-show rate dropped from 21.8% to 8.4%, and patient-reported satisfaction rose from 3.1 to 4.5 out of 5. Front-desk query volume also fell sharply as patients could track their position in the queue independently. These findings indicate that a moderately-resourced, cloud-based smart queue system can produce measurable gains in healthcare service delivery. The study concludes that Medi-Queue is a scalable, low-infrastructure-cost solution suitable for adoption by clinics and hospitals seeking to modernise patient flow management, and it recommends future integration with electronic health records and hospital resource-planning systems for deeper impact.

Key words: Medi-Queue, Outpatient, Appointment, Queue, Healthcare