Optimizing the timing and site of care during COVID and beyond

Using machine intelligence to schedule non-emergent deferrals and manage the phasing out of the Medicare inpatient only list

This webinar is on-demand and can be viewed at your convenience.  

While the efforts of states and health systems to temporarily delay elective care successfully reduced the spread of COVID, these efforts have contributed to a growing backlog of needed patient procedures. To add to this, health systems will need to prepare for reimbursement changes as the Medicare inpatient only list is phased out. These challenges give rise to the need for a smarter system for scheduling the time and site of care for patients.

Join Dr. Mohammed Saeed and Professor John Guttag, PhD in a discussion of how predictive machine intelligence can be used in conjunction with care manager outreach to prioritize the patient backlog and schedule patients for procedures at the right time and right setting of care to optimize outcomes.

Learning points:

  • The financial and clinical ramifications of delayed elective care
  • The financial and clinical benefits of choosing the optimal site of service for a patient
  • How machine intelligence can be used to work through the challenges posed by COVID and reimbursement changes
  • Additional use cases for predictive machine learning in healthcare 



Mohammed Saeed Headshot - McKenna Shier

Mohammed Saeed, MD, PhD

Chief Medical Officer for Health at Scale

john guttag headshot

John Guttag, PhD

CTO of Health at Scale and Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT