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Webinar

Infusion Capacity Management: How Johns Hopkins Medicine Decreased Drug Wait Time by 13%-32% Year-Over-Year, and University of Kansas Cancer Center Increased Average Daily Volumes by 19%

Speakers

DebbieFernandezHeadshot - Mallory Hufford
Debbie Fernandez, MS, MHSA, LMLP, CPHQ
Director of Quality, Oncology Service Line University of Kansas Health System
Jamie-Bachman
Jamie Bachman
Chief Administrative Officer Johns Hopkins Medicine

Summary

Why do health systems struggle to efficiently utilize assets? The fundamental problem is one of matching a volatile, unpredictable demand for services with the constrained availability of supply. Backward-facing tools such as dashboards are not adequately equipped to address this supply-demand issue.

Infusion centers face these supply-demand challenges on a daily basis. Building out a schedule for appointments at infusion centers is a coordinated effort that must consider various factors, from peak visit times to supply and capacity demands. These centers experience the same outcomes of unacceptable patient wait times, lack of available appointments, and nurses who can’t get off the floor for their breaks.

Johns Hopkins Medicine and University of Kansas Cancer Center both comprised hundreds of infusion chairs across multiple locations, serving tens of thousands of patients annually. Both organizations struggled with daily scheduling bottlenecks at peak midday hours, which led to long patient wait times and unpredictable, overloaded schedules for staff. 

Learn how these cancer centers adopted LeanTaaS’ AI-powered iQueue for Infusion Centers solution to better match demand for infusion appointments with their supply of chairs, nurses, and time. As a result, the centers level-loaded their schedules, accommodated more patients in less time, and promoted consistent work days for nurses. 

Viewers of this webinar will be able to: 

  • Explain how a supply-demand forms the root cause of many inefficiencies in healthcare 
  • Describe how AI, mathematical algorithms and predictive analytics to infusion center operations can match supply with demand, to streamline efficiencies for both patients and clinicians
  • Apply these principles to solve the scheduling and capacity challenges that infusion centers contend with nearly every day

Results

13%-32%Year-over-year decrease in drug wait time at Johns Hopkins Medicine
14%Growth in patient volumes during COVID at one Johns Hopkins location
32%Reduction in average chair wait time at University of Kansas Cancer Center
19%Increase in accommodated average daily completed volumes at University of Kansas Cancer Center
We’ve improved our physician satisfaction. Not only are we able to accommodate add-ons now, but our physicians have the confidence that when they start a new patient treatment we have the ability to quickly accommodate that patient in the schedule.
Debbie Fernandez, MS, MHSA, LMLP, CPHQ
Director of Quality, Oncology Service Line, University of Kansas Health System

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