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.
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.
Authors: Lakshmi Santanam; Coen Hurkmans; Sasa Mutic; Corine van Vliet-Vroegindeweij; Scott Brame; William Straube; James Galvin; Prabhakar Tripuraneni; Jeff Michalski; Walter Bosch Journal: Int J Radiat Oncol Biol Phys Date: 2012-01-13 Impact factor: 7.038
Authors: Travis R Denton; Lisa B E Shields; Michael Hahl; Casey Maudlin; Mark Bassett; Aaron C Spalding Journal: J Appl Clin Med Phys Date: 2015-11-07 Impact factor: 2.102