An Italian hospital dramatically reduced patient waiting times by combining Lean Thinking with Mathematical Optimization. The hematology ward at Policlinico Santa Maria alle Scotte in Siena processes approximately 10,000 patients annually—and they achieved remarkable results.
The Problem
Patient dissatisfaction centered on two issues: environmental comfort and prolonged waiting times. The team identified waiting times as particularly amenable to systematic improvement—and set out to fix it.
The PDCA Approach
Plan. The team documented existing processes, cataloged seven therapy types with daily capacity limits, analyzed duration distributions, and identified staffing requirements. They translated therapies into seven distinct patient pathways.
Do. Root cause analysis revealed the need for advance treatment scheduling. The critical shift: moving from a "push" model (slots distributed upon arrival) to a "pull" model (appointments scheduled in advance). This transformation created an ideal application for mathematical optimization algorithms.
Check. Using simulation with historical data, the results proved remarkable: the average waiting time reduction amounted to up to 94% for all patients, with dramatically reduced variability in lead times.
Act. Implementation requires stakeholder buy-in from management, medical staff, and patients, plus software integration of the optimization model.
Key Takeaways
The synergy between Lean methodology and mathematical optimization proved more powerful than either technique alone. Lean helped restructure the process; optimization helped schedule it efficiently.
Neither technique alone would have achieved 94% reduction. Process restructuring without optimization would have improved things moderately. Optimization without process restructuring would have been optimizing a broken system.
Together, they unlocked substantial improvements in healthcare delivery—without hiring additional staff or buying new equipment.
Written by
Jonasz Staszek