Using AI for Staff Optimization and Team Satisfaction

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Leveraging Predictive Analytics & Automation
Staffing remains one of the toughest challenges for perioperative leaders. Fluctuating surgical volumes, siloed decision-making, and time-consuming manual workflows make it difficult to balance efficiency, cost control, and staff satisfaction. But what happens when predictive analytics and automation are introduced into the equation?

Listen on-demand as a team from Oregon Health & Science University (OHSU) discuss how their health system is transforming OR staffing with real-time data and AI-driven workforce planning. They’ll share lessons learned from the implementation process, the impact on scheduling and resource allocation, and the cultural shift required to adopt data-driven staffing models.

This interactive conversation will highlight practical strategies for optimizing perioperative staffing while enhancing team satisfaction and operational efficiency.

Highlights

  • Why traditional OR staffing models fall short—and how data can help leaders make proactive, informed decisions
  • How predictive analytics is reducing manual scheduling burden and improving OR utilization at OHSU
  • Navigating change management and gaining leadership buy-in and engaging frontline staff in data-driven staffing
  • Review early results from OHSU’s journey toward more efficient, transparent, and equitable staffing

Meet the Panelists

Dio Sumagaysay, RN, MS
Vice President, Perioperative & Multi-Specialty Procedural Services, OHSU

Taryn Tomlinson, RN
Assistant Nurse Manager, Center for Healing and Healing Operating Room, OHSU

Erika Scott
SST Service Coordinator, Center for Health and Healing Operating Room, OHSU

Moderator: Jake Runion MBA, BSN, RN
Sr. Manager AORN Center for Perioperative Leadership

No contact hours are available for this program.

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