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Stanford Health Care Reduced Median Wait Times for Infusion Patients by 31%
31% Lower median wait times
78% Lower emergency call-back overtime pay
17% Lower total cost per unit of service
25 Higher percentile points in nursing satisfaction

Summary

Part of Stanford Health Care, a prestigious academic health system that centers the whole patient in its mission to innovate care, The Stanford Cancer Center is one of 71 elite NCI-Designated Comprehensive Cancer Centers in the entire country. The Stanford Cancer Center advances the understanding and treatment of cancer through a multidisciplinary, integrated, and collaborative community of physicians and scientists. The Stanford Cancer Center performs over 65,000 infusions annually across three centers and is growing steadily. 

Profile

135 chairs

8 centers

Epic EHR

NCI / NCCN designation

Academic Medical Center

Northern California

Problem

Stanford Cancer Center experienced operational challenges that constricted its ability to accommodate growing volumes and provide patients with a seamless experience that supported their health and wellbeing. Daily schedules showed a triangular usage profile, with midday appointment “peaks” leaving unused capacity in the mornings and evenings. These in turn caused long wait times for patients with midday appointments, costly overtime for nurses who had to accommodate unexpected add-on patients past the scheduled end of their shifts, and an overall suboptimal use of resources.

Solution

The original healthcare partner of LeanTaaS, Stanford Health Care jointly developed the AI-driven capacity optimization platform iQueue for Infusion Centers and deployed it at a Stanford Cancer Center site with 60 chairs to create optimized infusion scheduling templates. iQueue utilizes historic data and predictive and prescriptive analytics to continuously maximize infusion patient flow and chair usage. Using the platform to smooth its utilization peak and much more evenly distribute appointments throughout the day, Stanford Cancer Center saw clear operational results.

We took two years of historical data and pumped that into the analytic engine as well as operating constraints, how many infusion chairs are available, the hours when the chairs are open and the staff that’s available and that’s translated into a level-loaded production schedule.
Sridhar Seshadri
Vice President, Cancer Services at Stanford Health Care

Download the full iQueue for Infusion Centers case study booklet

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