Utilization of Lean and Six Sigma Methodologies to Characterize and Optimize Simulation Throughput

Abstract

Process improvement methodologies, including Lean and Six Sigma, enable evaluation of critical operations. The current simulation process utilizes a single simulator to support four Linac and brachytherapy operations. It is hypothesized that improving inefficiencies in patient and information flow would significantly improve throughput. We sought to define baseline operational cycle times, throughput and develop solutions associated with an optimized future state. Ninety-four patients simulated in January 2020 were retrospectively evaluated to determine simulation-specific metrics including throughput, utilization, and the percentage of patients traveling greater than 50 miles that were simulated on the same day as consult. Throughput was defined as the number of patients simulated per day. Utilization was calculated by dividing machine uptime, defined as the time a patient is on the simulation table, by total time monitored. Additionally, 19 patients in February 2020 were tracked prospectively from clinic arrival through simulation completion to quantify operational cycle times and note process delays. Start-to-end and start-to-start cycle times were defined as the total patient time in the simulation suite and the time between consecutive patients entering the simulation suite, including pre-simulation processes, respectively. Immobilization cycle time was defined as the time required to create the immobilization device. Baseline simulation throughput was calculated at 7.2 ± 1.9 patients per day. Utilization was calculated at 46.7 ± 1.6% with a start-to-end cycle time of 0.5 ± 0.2 hours. The calculated start-to-start cycle time demonstrated increased magnitude and variability at 1.1 ± 0.8 hours. During retrospective evaluation it was noted that 37.2% of patients checked in late with an average of 0.8-hour delay. Patients seen in consult traveling from greater than 50 miles away achieved 37.5% same-day simulation. Immobilization cycle time was calculated at 0.2 ± 0.0 hours. The current-state simulation process is highly dependent on serial completion of pre-simulation activities. It is recommended to decouple these processes from simulation where possible. First, it is recommended to divide the day into two-hour time blocks with three patients scheduled per block to reduce dependence on patient arrival time and pre-simulation processes. Additionally, making immobilization devices off-line prior to patient placement on the simulation table would decrease start-to-end cycle time and improve throughput. Finally, improved communication associated with patient preparation would potentially decrease non-value-added wait times associated with bladder filling or oral contrast administration. Future directions include piloting the proposed solutions, conservatively estimated to result in throughput of 10-12 patients per day, which represents an estimated 40 to 65% improvement over current baseline.