To expedite the current process of Physician Assistants manually reviewing each patient’s case that is recommended for surgery and assigning a location, MPrOVE built a predictive model that will automatically assign locations for a majority of cases. This predictive model will optimize staff time, expedite the surgery scheduling process, and ultimately lead to improved provider and patient satisfaction.

Background: Patients who are referred for surgery at Michigan Medicine have to be assigned a surgery site that is either at the University Hospital (UH) or at an Ambulatory Surgery Center (ASC). Physician Assistants (PAs) at the Preoperative Clinic have to manually review each case and assign a location; either UH or ASC; depending on the type of surgery and relative risk level of patient. Manually reviewing cases is time-consuming and can create a barrier for scheduling the surgery in a timely manner.

MPrOVE Role: MPrOVE built a predictive model that is designed to learn which location different patients and procedure types end up at based on historical cases and Pre-op PA reviews in 2020-2021. Once implemented, it has the potential to organize each case into a category; the intention is this will streamline the review process and provided additional growth opportunity for optimization.

Anticipated Outcomes: The review of surgical cases for site optimization & appropriateness will help ensure patients undergo surgery at the right location: one that matches their risk and the risk of their surgical procedure. This model embedded within the EHR will:

• Optimize staff time

• Expedite surgery scheduling

• Increase provider & patient satisfaction

Additional Links:

ASC Review Website