Machine Learning based Integrated Hospital Appointment Booking and Queue Management System

Hospitals have a growing challenge of long queues and consequently more waiting time for patients. Hospitals can better manage resources and anticipate more inflow of patients through estimations on patient count. In this paper, we propose a web-based Machine Learning based Integrated Hospital Appointment Booking and Queue Management System that aims to reduce the queue time of patients and forecast the number of patients present at a given hour of the day. Queue time reduction is done by generating a unique token number for every patient which is used to lead him directly to the respective department and patient forecasting is done using Demand Forecasting which is a Machine Learning Regression Algorithm to predict future patient count at a particular hour of the day. The results can help patients make a better decision of choosing a less crowded time. This will also help the hospital to manage the patient crowd, logistics and resources more efficiently.