Miami Cancer Institute achieves $10.9M ROI (15x cost) by optimizing infusion center scheduling with LeanTaaS iQueue

Miami Cancer Institute deployed Machine Learning & Predictive Analytics for Patient Flow & Hospital Operations in Hospital & Health System. As reported by leantaas.com: $10.9M (~15x cost) roi since go-live.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
$10.9M (~15x cost)ROI Since Go-Live
35%Reduction in Average Daily Drug Wait Time
15%Increase in Average Daily Completed Volumes

Source-reported figures (cited source: leantaas.com)

What Miami Cancer Institute was trying to fix

Miami Cancer Institute faced growing demand for infusion services with scheduling inefficiencies and inconsistent patient wait times. Key resources like chairs and nurses were unevenly utilized, and drug preparation wait times were negatively impacting patient experience. Nurse leaders spent excessive time manually pre-assigning patients to specific nurses before treatment days, and any nurse callout required redistributing an entire patient load.

What Miami Cancer Institute deployed

In June 2022, Miami Cancer Institute implemented LeanTaaS iQueue for Infusion Centers at their 60-chair Kendall location, followed by the 12-chair Plantation site in 2023. iQueue optimized infusion workload balancing and provided data-driven scheduling visibility. A key process change—supported by LeanTaaS's Process Optimization team—replaced manual nurse pre-assignment with dynamic real-time patient-to-nurse matching based on workload mix and patient needs.

Results

Since go-live, Miami Cancer Institute achieved a $10.9M ROI, approximately 15x the cost of the solution. Average daily completed infusion volumes increased by 15%, while average daily drug wait time dropped by 35%. The dynamic nurse-matching methodology significantly reduced administrative burden on nurse leaders and improved resilience to staffing changes.

Key Takeaways

  • Dynamic real-time nurse-patient matching eliminates the fragility of pre-assignment workflows and reduces administrative overhead for nurse leaders.
  • Deploying AI-driven scheduling across multiple infusion sites with different capacities (60-chair vs. 12-chair) requires phased rollout with dedicated process optimization support.
  • Operational ROI at 15x cost demonstrates that scheduling optimization yields compounding returns as patient volumes grow.

Evidence for Miami Cancer Institute's Patient Flow & Hospital Operations deployment

Reported outcome metrics
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Cited source
leantaas.com
Last updated
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