Use of machine learning algorithms to predict optimal hospital length of stay

Abstract

Problem: Hospitals often struggle to allocate beds, equipment, and staff efficiently, leading to unnecessary complications. Predicting a patient’s length of stay (LOS) early helps hospitals plan treatment, staffing, and bed availability more effectively. Both extremes of LOS carry risks: discharging too early can result in inadequate care and higher readmissions, while prolonged stays waste resources and increase costs. Solution: Optimizing LOS improves patient outcomes using machine learning, enhances operational efficiency, and reduces overall spending.