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iQueue for Infusion Centers Case Study – UCSF


The UCSF Helen Diller Family Comprehensive Cancer Center is one of 71 elite NCI-designated Cancer Centers in the United States, and is one of only two centers in the Bay Area to receive the prestigious designation of “comprehensive” from the National Cancer Institute.

In the past year, the Center experienced a 21% growth rate in treatment volumes and were experiencing the following operational challenges:

  • Consistently operating over capacity
  • A peaky utilization profile leading to extended wait times in the middle of the day
  • Strained resources, resulting in decreasing staff and patient satisfaction


Leadership at the Helen Diller Family Comprehensive Cancer Center deployed iQueue for Infusion Centers at one of its centers with 12 chairs and 3 beds to create optimized infusion scheduling templates. After realizing significant results, iQueue for Infusion Centers was deployed at 4 additional centers that collectively added 82 more chairs.

iQueue for Infusion Centers uses data science and machine learning to create optimized scheduling templates in order to continuously maximize patient flow and chair usage.

Utilization Curve Before

UCSF before curve
  • Frequent “mid-day” peaks and slow mornings and evenings
  • Frequent overflow in waiting rooms – long patient waiting times

Utilization Curve After

UCSF after curve
  • Even workload throughout the day allows for more predictable schedules
  • Unlock capacity to help deal with unexpected delays and add-ons


The following results were calculated by comparing the six month period post-iQueue launch to the analogous six months in the previous calendar year.

Lower Waiting Times at Peak Hours
Lower Average Waiting Time
Lower Average Hours Over Capacity
Lower Overall Average Daily Peak
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