PURPOSE: To assess efficacy of an incident learning system in the management of error in radiation treatment. MATERIALS AND METHODS: We report an incident learning system implementation customized for radiation therapy where any "unwanted or unexpected change from normal system behaviour that causes or has the potential to cause an adverse effect to persons or equipment" is reported, investigated and learned from. This system thus captures near-miss (potential) and actual events. Incidents are categorized according to severity, type and origin. RESULTS: Our analysis spans a period of 3 years with an average accrual of 11.6 incidents per week. We found a significant reduction in actual incidents of 28% and 47% in the second and third year when compared to the first year (p<0.001), which we attribute to the many interventions prompted by the analysis of incidents reported. We also saw a similar significant reduction in incidents generated at the treatment unit correlating with the introduction of direct treatment parameter transfer and electronic imaging (p<0.001). CONCLUSIONS: Implementation of an incident learning system has helped us to establish a just environment where all staff members report deviations from normal system behaviour and thus generate evidence to initiate safety improvements. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
PURPOSE: To assess efficacy of an incident learning system in the management of error in radiation treatment. MATERIALS AND METHODS: We report an incident learning system implementation customized for radiation therapy where any "unwanted or unexpected change from normal system behaviour that causes or has the potential to cause an adverse effect to persons or equipment" is reported, investigated and learned from. This system thus captures near-miss (potential) and actual events. Incidents are categorized according to severity, type and origin. RESULTS: Our analysis spans a period of 3 years with an average accrual of 11.6 incidents per week. We found a significant reduction in actual incidents of 28% and 47% in the second and third year when compared to the first year (p<0.001), which we attribute to the many interventions prompted by the analysis of incidents reported. We also saw a similar significant reduction in incidents generated at the treatment unit correlating with the introduction of direct treatment parameter transfer and electronic imaging (p<0.001). CONCLUSIONS: Implementation of an incident learning system has helped us to establish a just environment where all staff members report deviations from normal system behaviour and thus generate evidence to initiate safety improvements. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
Authors: M Saiful Huq; Benedick A Fraass; Peter B Dunscombe; John P Gibbons; Geoffrey S Ibbott; Arno J Mundt; Sasa Mutic; Jatinder R Palta; Frank Rath; Bruce R Thomadsen; Jeffrey F Williamson; Ellen D Yorke Journal: Med Phys Date: 2016-07 Impact factor: 4.071
Authors: Eric Ford; Leigh Conroy; Lei Dong; Luis Fong de Los Santos; Anne Greener; Grace Gwe-Ya Kim; Jennifer Johnson; Perry Johnson; James G Mechalakos; Brian Napolitano; Stephanie Parker; Deborah Schofield; Koren Smith; Ellen Yorke; Michelle Wells Journal: Med Phys Date: 2020-04-15 Impact factor: 4.071
Authors: Ashley E Rubinstein; W Scott Ingram; Brian M Anderson; Skylar S Gay; Xenia J Fave; Rachel B Ger; Rachel E McCarroll; Constance A Owens; Tucker J Netherton; Kelly D Kisling; Laurence E Court; Jinzhong Yang; Yuting Li; Joonsang Lee; Dennis S Mackin; Carlos E Cardenas Journal: J Appl Clin Med Phys Date: 2017-06-06 Impact factor: 2.102
Authors: Guanghua Yan; Kathryn Mittauer; Yin Huang; Bo Lu; Chihray Liu; Jonathan G Li Journal: J Appl Clin Med Phys Date: 2013-11-04 Impact factor: 2.102
Authors: Eric C Ford; Matthew Nyflot; Matthew B Spraker; Gabrielle Kane; Kristi R G Hendrickson Journal: J Appl Clin Med Phys Date: 2017-09-12 Impact factor: 2.102