Dynamic Resource Optimization in Healthcare Operations through Real-Time Predictive Analytics

Abstract

Hospitals, the place with high moving crowds, are busy on time. Due to increased patient count and requirement of facilities, it can lead to fully occupied emergency rooms and staff shortages. This problem is very crucial and important to solve in hospitals, since it affects the care and treatment effectiveness of the patients. The proposed system that is working on is a prediction system that uses entire past data of a hospital to predict the future necessity of the facilities required during a particular time. It predicts the busiest times in the hospital, emergency patient entries, according to the movement of the patients and as per the possible requirements for a particular patient. Using the acquired data, and the prediction analysis, dashboards will be created. All the predicted data is shown on the dashboard, and it provides key details of staff availability, bed availability and emergency room allocation. The solution is used to handle the delays and to improve the effectiveness of resource allocation throughout the hospital. The information from the dashboard helps the staff to allocate facilities correctly, make sure of ample staff availability particularly at the busiest hours, and prepare the hospital environment for overcrowded areas. It is safer, more effective and can handle extreme patient population at ease