How Predictive Analytics is Improving OR's Operational Efficiencies

A collaborative mission drives the staff at UCHealth: Keep costs down while improving quality of care. Accomplishing this goal can be tricky, but current models of predictive analytics for healthcare are helping achieve that balance.

“Our use of analytics creates a win-win-win scenario for patients, payers and providers,” Steve Hess, CIO of UCHealth, tells HealthTech. “And that’s something that is very rare in healthcare.”

Four years ago, the Aurora, Colo.-based organization began moving down a path toward predictive analytics by focusing on patient surveillance in outpatient care. And that has since compelled UCHealth to leverage an existing universal database to better predict patient outcomes in clinical settings — including operating rooms.

Dr. Clint Devin, an orthopedic spine surgeon at UCHealth Yampa Valley Medical Center in Steamboat Springs, Colo., helped launch that database in 2008 while working at Vanderbilt University School of Medicine. Formerly known as the Quality Outcomes Database (QOD) Spine registries, the effort was established in coordination with nonprofit NeuroPoint Alliance to collect, sort and analyze the safety of care, patient-reported outcomes and satisfaction of care across multiple healthcare settings in spine surgery.