Process improvement for the safe delivery of multidisciplinary-executed treatments-A case in Y-90 microspheres therapy.

PURPOSE: To develop a safe and robust workflow for yttrium-90 (Y-90) radioembolization procedures in a multidisciplinary team environment. METHODS AND MATERIALS: A generalized Define-Measure-Analyze-Improve-Control (DMAIC)-based approach to process improvement was applied to a Y-90 radioembolization workflow. In the first DMAIC cycle, events with the Y-90 workflow were defined and analyzed. To improve the workflow, a web-based interactive electronic white board (EWB) system was adopted as the central communication platform and information processing hub. The EWB-based Y-90 workflow then underwent a second DMAIC cycle. Out of 245 treatments, three misses that went undetected until treatment initiation were recorded over a period of 21 months, and root-cause-analysis was performed to determine causes of each incident and opportunities for improvement. The EWB-based Y-90 process was further improved via new rules to define reliable sources of information as inputs into the planning process, as well as new check points to ensure this information was communicated correctly throughout the process flow. RESULTS: After implementation of the revised EWB-based Y-90 workflow, after two DMAIC-like cycles, there were zero misses out of 153 patient treatments in 1 year. CONCLUSIONS: The DMAIC-based approach adopted here allowed the iterative development of a robust workflow to achieve an adaptable, event-minimizing planning process despite a complex setting which requires the participation of multiple teams for Y-90 microspheres therapy. Implementation of such a workflow using the EWB or similar platform with a DMAIC-based process improvement approach could be expanded to other treatment procedures, especially those requiring multidisciplinary management.

Eliminating inconsistencies in simulation and treatment planning orders in radiation therapy.

PURPOSE: To identify deficiencies with simulation and treatment planning orders and to develop corrective measures to improve safety and quality. METHODS AND MATERIALS: At Washington University, the DMAIIC formalism is used for process management, whereby the process is understood as comprising Define, Measure, Analyze, Improve, Implement, and Control activities. Two complementary tools were used to provide quantitative assessments: failure modes and effects analysis and reported event data. The events were classified by the user according to severity. The event rates (ie, number of events divided by the number of opportunities to generate an event) related to simulation and treatment plan orders were determined. RESULTS: We analyzed event data from the period 2008-2009 to design an intelligent SIMulation and treatment PLanning Electronic (SIMPLE) order system. Before implementation of SIMPLE, event rates of 0.16 (420 of 2558) for a group of physicians that were subsequently used as a pilot group and 0.13 (787 of 6023) for all physicians were obtained. An interdisciplinary group evaluated and decided to replace the Microsoft Word-based form with a Web-based order system. This order system has mandatory fields and context-sensitive logic, an ability to create templates, and enables an automated process for communication of orders through an enterprise management system. After the implementation of the SIMPLE order, the event rate decreased to 0.09 (96 of 1001) for the pilot group and to 0.06 (145 of 2140) for all physicians (P<.0001). The average time to complete the SIMPLE form was 3 minutes, as compared with 7 minutes for the Word-based form. The number of severe events decreased from 10.7% (45 of 420) and 12.1% (96 of 787) to 6.2% (6 of 96) and 10.3% (15 of 145) for the pilot group and all physicians, respectively. CONCLUSIONS: There was a dramatic reduction in the total and the number of potentially severe events through use of the SIMPLE system. In addition, the order process has become more efficient and reliable.