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How UCSD Moores Cancer Center Unlocked Capacity by Reducing their No-Show Rate by up to 50%

Speakers

Gabriela Lacatus
Gabriela Lacatus, RN, BSN, OCN, PhD
Ambulatory Patient Care Manager, Moores Cancer Center, UC San Diego Health

Summary

University of California San Diego (UCSD) Moores Cancer Center accommodates 80,000 annual outpatient visits and has a mission to provide quality comprehensive cancer care. Despite an already-large capacity and facility expansion, the cancer center grappled with very high no-show rates for patients that led to much of that capacity going unused. Bottlenecked scheduling and long wait times led to frustration for both patients and staff. Compounding these problems was an EHR that only allowed for scheduling patients by standardized slots, rather than by acuity or appointment duration. 

To promote more efficient schedules and continue to optimize the capacity UCSD already invested in, Moores Cancer Center needed a solution to leverage historic appointment data to generate predictive, level-loaded scheduling templates based on expected treatment lengths, nurse staffing, and expanded capacity made available by likely cancellations. The solution also had to account for acuity and appointment length. 

By implementing LeanTaaS’ AI-powered iQueue for Infusion Centers solution, the cancer center was able to deliver these capabilities to its infusion leaders and staff. Using iQueue, Moores Cancer Center not only level loaded daily appointment schedules, but strategically adjusted its approach to staffing and nurse assignments. In this session, the Ambulatory Patient Care Manager at Moores Cancer Center discusses how the organization leveraged the iQueue network, data and custom analytics to drive internal change management and significantly move the needle on operational performance. 

Viewers of this webinar will be able to: 

  • Identify the operational challenges UCSD Moores Cancer Center faced with scheduling, unused capacity, and long wait times
  • Explain how implementing predictive, data-driven scheduling helped optimize infusion center capacity and improve efficiency
  • Apply the learnings from AI-powered technology to adjust organizational strategy toward better operations

Results

32%Reduction in no-shows
14%in Daily completed appointments
40Hours of appointments added to main schedule
We have seen daily completed volume up 14%...and that was supported by the fact that we were able to limit the number of same-day shrinkage and no-shows from over 20% to under 10%. So extremely successful and much appreciated all the way to our CEO.
Gabriela Lacatus, RN, BSN, OCN, PhD
Ambulatory Patient Care Manager, Moores Cancer Center UC San Diego Health

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