Using Machine Learning to Analyze Hospital Admissions

This work studies the application of change point detection on daily hospital patient admissions to develop a decision support system for hospital management. Change point detection is a statistical technique used to identify abrupt shifts or changes in a time series. By employing this statistical technique to identify shifts in admission trends, this system aids healthcare administrators in optimizing resource allocation, responding to structural changes due to external factors, improving operational efficiency, and offering predictive capabilities for capacity planning. We demonstrate the potential of this approach in enhancing patient care, resource optimization, and healthcare service delivery.