Machine learning: Pave the path to home

Q.  How are artificial intelligence and machine learning helping ensure a smooth transition to heal at home and avoid hospital readmissions?

A. Failures in our healthcare system increase post-acute spend for health plans by an estimated 20% to 25%, while patients face unnecessary risks. One of the biggest gaps is lack of communication and collaboration between providers and patients. New healthcare innovations, such as AI and machine learning, are helping us optimize post-acute care and keep patients safer.

By tapping into the latest technology, we can place patients at the center of their care team—whether they are in the hospital or healing at home. For example, we can now use predictive algorithms to test, apply and create a personalized pathway for a patient's recovery, lessening post-acute recovery time, reducing avoidable hospital readmissions and decreasing the cost of care. By feeding patient outcomes back into these care algorithms, we create a virtual circle that improves care for everyone.

For providers, AI and machine learning mean easy-to-use smart tools that help predict and flag potential obstacles in a patient's journey to recovery. By sharing valuable real-time information, we can also address gaps in care and communication that exist in healthcare silos today.

For health plans, these tools can help optimize provider networks and potentially reduce the nearly 75% of preventable hospital readmissions that cost the healthcare system over $40 billion annually. By leveraging machine learning, we can understand which care providers best support patients' recoveries and address the risks they encounter after a hospital stay.