Application of Machine Learning to Predict Hospital Churning

Nowadays, with options in health amenities, healthcare is going through a digital transformation to find ways to be able to retain patients and reduce patient churn, which consequently is crucial for their success and growth. In the healthcare system, patients are seen as treasured customers, and hospitals are trying to re-orient around providing enhancements in treatments for achieving this, but patient churn is an ongoing challenge for this. Therefore, hospitals are increasingly relying on AI and Machine Learning based insights to find those factors that are most likely to lead to patient churn and then take appropriate actions on it to reduce them. To predict the churn ratio is the main aim of our work which will assist hospitals to identify the patients who are most likely subject to churn. We identify the factors to predict the churn ratio and see how effectively we can use machine learning techniques which will help us to strengthen prediction performance by identifying, attract, and retain preferred patients.