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Implement Lean Methodology to Make Our Current Process of CT Simulation to Treatment More Efficient

S Boddu

S Boddu*, A Morrow , N Krishnamurthy , A McVicker , N Deb , D Rangaraj , Scott & White Hospital, Temple, TX


WE-H-BRC-4 (Wednesday, August 3, 2016) 4:30 PM - 6:00 PM Room: Ballroom C


Our goal is to implement lean methodology to make our current process of CT simulation to treatment more efficient.


In this study, we implemented lean methodology and tools and employed flowchart in excel for process-mapping. We formed a group of physicians, physicists, dosimetrists, therapists and a clinical physics assistant and huddled bi-weekly to map current value streams. We performed GEMBA walks and observed current processes from scheduling patient CT Simulations to treatment plan approval. From this, the entire workflow was categorized into processes, sub-processes, and tasks. For each process we gathered data on touch time, first time quality, undesirable effects (UDEs), and wait-times from relevant members of each task. UDEs were binned per frequency of their occurrence. We huddled to map future state and to find solutions to high frequency UDEs. We implemented visual controls, hard stops, and documented issues found during chart checks prior to treatment plan approval.


We have identified approximately 64 UDEs in our current workflow that could cause delays, re-work, compromise the quality and safety of patient treatments, or cause wait times between 1 - 6 days. While some UDEs are unavoidable, such as re-planning due to patient weight loss, eliminating avoidable UDEs is our goal. In 2015, we found 399 issues with patient treatment plans, of which 261, 95 and 43 were low, medium and high severity, respectively. We also mapped patient-specific QA processes for IMRT/Rapid Arc and SRS/SBRT, involving 10 and 18 steps, respectively. From these, 13 UDEs were found and 5 were addressed that solved 20% of issues.


We have successfully implemented lean methodology and tools. We are further mapping treatment site specific workflows to identify bottlenecks, potential breakdowns and personnel allocation and employ tools like failure mode effects analysis to mitigate risk factors to make this process efficient.

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