The article explores how predictive analytics is reshaping healthcare, especially by allowing medical facilities to use advanced AI. It discusses how, through the advancement of proactive healthcare, predictive tools help with disease progression, predicting risk of hospital readmission, response to treatments, and managing healthcare resources. Things to think about technically are structuring the architecture, combining various systems, ways of modeling, deployment, and security for health-related data. Such strategies handle readiness in the organization, oversee data governance, integrate health records, manage change, and calculate ROI. Such environments give the chance to healthcare professionals in community hospitals and outpatient networks beyond academic centers to build predictive models that benefit their patients and work environment.
Keywords: AI implementation, Clinical Decision Support, health forecasting, machine learning healthcare, predictive analytics
