This blog post has been co-authored by Slawek Kierner, SVP of Enterprise Data & Analytics, Humana and Tie-Yan Liu, Assistant Managing Director, Microsoft Research China.
Using AI models to make real-world impact
Trips to the hospital happen. And while everyone in the industry strives to deliver world-class care for in-patient experiences, everyone—patients and care teams alike, would prefer to avoid those stays at the hospital. The teams at Humana believed they had enough data to explore the possibility of proactively identifying when patients were heading toward a high-risk event, and they putMicrosoft Cloud for Healthcareand AI technology to the test.
Humana’s questions were straightforward: How do we take the data we have today and use it proactively? How do we use AI to identify signals in our existing ecosystem that tell us someone might be experiencing a scenario that puts them at risk? And most importantly, how do we engage proactively, meeting our members in their own environment before they end up in an emergency room?
The first approach to monitor chronic patients is often focused on remote patient monitoring and IoT devices, but to approach this challenge, we wanted to take a different, and much bigger, approach with AI. By combining clinical data, key event triggers that might indicate a patient was experiencing deteriorating health, and a combination of predictive models, Microsoft Research and Humana data science teams collaborated on research to explore whether they could develop a system that would identify potential gaps in care among patients and engage high risk patients with care teams that could reach out and offer support.