Optimizing Hospital Resources with AI Forecasting

HealthOptima deployed an AI-driven predictive model to forecast patient admissions in a large urban hospital. By analyzing historical admission data, seasonal trends, and local health indicators, the system predicted admission spikes with 87% accuracy. This allowed the hospital to optimize staff schedules and bed availability, reducing patient wait times by 25% and cutting overtime costs by 15%. The AI system also provided real-time dashboards for administrators, enhancing decision-making. Challenges included integrating diverse data sources, which was overcome by using standardized APIs and data cleaning algorithms.