Optimizing staffing levels in clinical settings is a persistent challenge for healthcare leaders. UCLA Health's Office of Ambulatory Transformation & Performance (ATP) successfully tackled this issue by creating a transparent, data-driven staffing assessment process using customized analytics and web-based tools. This session will illustrate how leaders can use advanced analytics to balance patient care quality, operational efficiency, and financial sustainability by answering the question: How do we rightsize (not downsize) our workforce?
Participants will discover this innovative approach and how it addresses common healthcare staffing issues, including lack of transparency, disjointed processes, and suboptimal benchmarking. We'll share our journey of creating a single source of truth for staffing decisions, implementing automated approval workflows, and fostering leadership engagement.
Learning Objectives:
Construct a data-driven staffing model that balances patient care, operational efficiency, and financial sustainability
Develop custom analytics and web applications to streamline staffing decisions and enhance transparency
Design automated approval workflows and leadership engagement strategies for a more responsive and efficient staffing assessment system
