Predicting the Unpredictable: Using Analytics to Match Staffing-to-Patient Demand
Karin Olson, RN
Executive Director, Clinical & Systems Transformation
Vancouver Coastal Health
Director, Capacity Management
What if you could accurately forecast patient demand one day, one week, even one month out rather than having to scramble to match staff to patients who have already arrived? How would that change a typical day for everyone involved in patient care? How would it affect labor costs?
With the right tools and data, patient demand is surprisingly predictable. This session will describe how Lion’s Gate Hospital, a division of Vancouver Coastal Health in British Columbia, has been using predictive analytics since 2010 to staff to anticipated volume and adjust for patient flow by day, week and surgeon, as well as forecast volume for the ED and surgical units. By reliably forecasting demand with a 95 percent accuracy rate, in one year they saved $1.4 million in overtime savings and increased revenue by $1.5 million.
After This Webinar You'll Be Able To:
- Describe the inputs needed to accurately predict patient demand.
- Leverage forecasted demand to lower baseline and optimize variable staffing levels.
- Use a predictive analytics model to smooth inpatient surgical census between two hospitals.
- Understand potential impact of predictive modeling on financial performance.
COOs, CFOs, CNOs, process improvement engineers
Field of Study
Specialized Knowledge and Applications
Basic knowledge of labor costs and staffing issues
HFMA members & ACPE members: Free
Note: This on-demand webinar is available until Sept. 24, 2014.