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Penn Medicine Increased Infusion Patient Volumes by 25%


Ranked as Pennsylvania’s number one health system, Penn Medicine is a world renowned academic medical center in Philadelphia that combines education, research, and clinical approaches to provide the best possible care for the patient.

Penn Medicine’s Abramson Cancer Center Infusion Suite at the Perelman Center for Advanced Medicine sees over 50,000 infusion visits each year. Like many high volume infusion centers, it experienced severe operational challenges that limited the ability to serve an optimal patient volume and provide the best quality experience. Uneven schedules and patient arrival patterns, which tended to be slow in the mornings and evenings and overloaded in the middle of the day, led to inconsistent workloads for nurses and extended wait times for patients. Nurses felt rushed and pressured while performing essential functions like documentation and education, and were unable to give patients due attention in educating them or building relationships. These circumstances produced a history of dissatisfaction among both patients and staff.

To begin addressing these issues, leadership at Penn Medicine Abramson Cancer Center initially deployed the analytics-based iQueue for Infusion Centers on the infusion suite’s 21-chair fourth floor to optimize their scheduling templates, provide daily management guidance about what to expect each day, and to understand why days did not go as planned. In the pilot center, iQueue helped support an even workload throughout the day that allowed for more predictable schedules, which also unlocked capacity to help deal with unexpected delays and add-ons. 

As a result of the outstanding results Penn Medicine Abramson Cancer Center achieved, leadership extended the use of iQueue for Infusion Centers to many of its other floors and locations, bringing the solution to more than 15 centers across their network.

Key Takeaways


Explain the ways daily midday infusion schedule “peaks” contribute to long-term patient and staff dissatisfaction


Recognize how level-loading infusion schedules reduces wait times and unlocks capacity for further patient volume


Understand the role of an analytics-driven solution in level-loading infusion schedules


25% increase in patient volumes
20% increase in patient hours
22% decrease in average wait times
13% decrease in average wait times during peak hours

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