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Problem

Huntsman Cancer Institute (HCI) is part of the University of Utah Health Care system. HCI is a National Cancer Institute (NCI)-Designated Comprehensive Cancer Center, which means it meets the highest standards for cancer care and research and receives support for its scientific endeavors.

HCI is also a member of the National Comprehensive Cancer Network (NCCN), a not-for-profit alliance of the world’s leading cancer centers. The Center was experiencing much busier days due to an increase in volume, and was experiencing the following operational challenges:

  • Increasing volumes was making it hard to find slots for longer treatments
  • Exceeding capacity in peak hours and peak days was impacting patient wait times
  • Exceeding capacity in peak hours was affecting nurse satisfaction

Solution

HCI deployed iQueue for Infusion Centers at its 36-chair center to create optimized infusion scheduling templates.

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

Utilization Curve After

Results

16%
DECREASE IN
Average Wait Times on
Peak Day
26%
DECREASE IN
Average Wait Time
During Peak Hours
0days
ABOVE
Capacity Since
implementation
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