Reducing readmissions with personalized post-acute care navigation

Tuesday, June 22nd, 2021 | 12:00 PM - 1:00 PM CT


Helping patients choose the right skilled nursing facility (SNF), home health agency (HHA), or other provider at discharge is critical to avoiding readmissions. But what’s the best way to choose? Hospitals can’t rely on quality stars alone — they need better tools to identify the right post-acute provider for patients to ensure optimal outcomes.

With advances in machine learning, hospitals and patients can now choose providers based on their ability to enable better outcomes. Join us as we review the results of a recent peer-reviewed study and discuss how machine learning can be used to reduce readmissions by personalizing post-acute care navigation at the point of discharge.

In this webinar, you’ll learn:

  • How machine learning can be used to identify SNFs, HHAs, and other post-acute providers that will reduce readmission risk
  • Why personalized provider navigation is key to enabling optimal outcomes for each patient
  • About a peer-reviewed study comparing outcomes for machine learning-based SNF recommendations to current methods


Mohammed Saeed Headshot - Maddi Billings

Mohammed Saeed, MD PhD

Assistant Professor and Cardiologist at U-Michigan Medicine, and Chief Medical Officer at Health at Scale