Katie Little, RN, BSN, AS, OCN, is nurse manager at Inova Schar Cancer. At Fairfax West, one of five infusion centers in the Inova system, she and her team faced a familiar challenge for infusion leaders: how to expand hours and introduce new roles while still protecting the patient experience. Just as important, they needed to avoid burning out staff or creating inequities in the schedule.
In this Q&A, Katie shares how her team used AI-enabled staffing templates, data visibility and clear guardrails to make scheduling more consistent and transparent. She will expand on this work during the upcoming Transform Infusion Center Operations Virtual Summit on February 24 (10 a.m. – 1 p.m. CT).
Question: Where did Inova’s journey begin when it came to optimizing infusion center operations?
Katie Little: In 2019, we were seeing growing patient volumes and increasing scheduling complexity across Inova’s infusion centers. Midday bottlenecks delayed treatments, early and late hours were underutilized, and even small disruptions could ripple across the day. We needed a more consistent, data-driven way to manage flow and protect the patient and staff experience.
That led us to partner with LeanTaaS and implement iQueue for Infusion Centers, starting with our primary Fairfax site in May 2019 and our Fairfax West site in December 2019. We’ve seen meaningful improvements since then. Wait times at our primary Fairfax site have fallen by 56% and we’ve increased completed volumes by 146%. Specifically at Fairfax West, we reduced wait times by about 50% and increased completed volume by 36%.
Because of the trust and partnership we built over those years, it was a natural decision to pilot a new tool that optimizes staffing from the LeanTaaS team in 2025, focused specifically on staffing redesign at Fairfax West.
Question: What was happening specifically at Fairfax West that led you to redesign staffing in 2025?
KL: When I stepped into my role in 2022, Fairfax West had strong growth, but we didn’t have the same structured roles as some of our other sites. We didn’t have a dedicated charge nurse, port nurse or fast track model.
At the same time, we were operating at full capacity on nine-hour days. In April 2025, we needed to expand to 10-hour days to support our growing community and help absorb volume from another site. The stakes were high. We needed to keep wait times under five minutes while scaling.
I was manually tracking ratios and trying to calculate capacity scenarios on my own. It became clear that as we expanded hours, we needed more data-driven guardrails to design the right shifts and make sure the workload was fair.
Question: How did optimizing staffing with AI support the one-hour expansion at Fairfax West?
KL: When we expanded to 10-hour days, the LeanTaaS team approached us about piloting their new Workforce Optimization tool within iQueue to help support the transition. It gave us an opportunity not only to design the right shifts for expanded hours, but also to take advantage of additional scheduling and staffing benefits. The core question was simple: What shifts do we actually need to meet our demand?
Instead of manually estimating nurse hours and treatment time, the system aligned staffing with predicted patient demand and incorporated individual nurse availability and preferences. We have nine-hour nurses, 10-hour nurses, staggered shifts and nurses with specific accommodations. The templates reflected all of that.
As a result, we were able to maintain nurse coverage at nearly 100% of predicted demand while honoring preferences. It also positioned the Fairfax West site to absorb redirected system volume and even see more patients than I could have predicted manually.
Question: What changed operationally once the new shift templates were in place?
KL: First, it reduced the mental load. I was no longer spending hours building and rebuilding schedules by hand. If we needed to adjust touch times or evaluate a different scenario, we could model it quickly.
Second, it made fairness visible. We could show how patient flow would look throughout the day and how discharges would be distributed between nine- and 10-hour shifts. That transparency helped reduce anxiety about late stays.
And finally, it gave us the flexibility to account for individual situations. For example, if a nurse had a shorter shift or a medical accommodation, we could build that into the template instead of trying to patch it together manually.
Question: How did you approach change management with your nursing team?
KL: Trust was critical. I was a new manager, and we were introducing new roles and new shift structures at the same time.
Nurses respond to data. After each role change, whether it was adding a port nurse or a fast track model, I could show the impact on drug wait times and infusion wait times. When staff saw that wait times improved and patient flow stabilized, it reinforced that these changes were purposeful.
We also kept feedback flowing. If someone felt something was not working, we went back to the data together and evaluated it. That engagement helped the team feel heard and more comfortable with the transition.
Question: How does the work at Fairfax West fit into the broader strategy across Inova?
KL: The hour expansion and intelligent staffing work at Fairfax West are part of a larger journey. We are expanding the Workforce Optimization tool across additional sites, and we recently went live with iQueue’s Patient Assignment tool and SmartSquare integration to automate shift syncing.
For us, this is about more than filling shifts. It is about creating consistent guardrails, balancing fairness across nurses and building a staffing model that can support growth across the entire Inova system.
Katie Little will share additional lessons learned and practical strategies during Transform Infusion Center Operations Virtual Summit on February 24 (10 a.m. – 1 p.m. CT). Register to hear more about how Inova is aligning staffing with demand while building trust and fairness across the team.
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