Juan López-Tarjuelo1, Ana Bouché-Babiloni2, Agustín Santos-Serra3, Virginia Morillo-Macías2, Felipe A Calvo4, Yuri Kubyshin5, Carlos Ferrer-Albiach6. 1. Servicio de Radiofísica y Protección Radiológica, Consorcio Hospitalario Provincial de Castellón, Castellón de la Plana, Spain. Electronic address: lopez_juatar@gva.es. 2. Servicio de Oncología Radioterápica, Consorcio Hospitalario Provincial de Castellón, Castellón de la Plana, Spain. 3. Servicio de Radiofísica y Protección Radiológica, Consorcio Hospitalario Provincial de Castellón, Castellón de la Plana, Spain. 4. Departamento de Oncología, Hospital General Universitario Gregorio Marañón Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, Spain. 5. Instituto de Técnicas Energéticas, Universidad Politécnica de Cataluña, Barcelona, Spain. 6. Servicio de Oncología Radioterápica, Consorcio Hospitalario Provincial de Castellón, Castellón de la Plana, Spain; Facultad de Medicina, Universidad Cardenal Herrera-CEU, Castellón de la Plana, Spain.
Abstract
BACKGROUND AND PURPOSE: Industrial companies use failure mode and effect analysis (FMEA) to improve quality. Our objective was to describe an FMEA and subsequent interventions for an automated intraoperative electron radiotherapy (IOERT) procedure with computed tomography simulation, pre-planning, and a fixed conventional linear accelerator. MATERIAL AND METHODS: A process map, an FMEA, and a fault tree analysis are reported. The equipment considered was the radiance treatment planning system (TPS), the Elekta Precise linac, and TN-502RDM-H metal-oxide-semiconductor-field-effect transistor in vivo dosimeters. Computerized order-entry and treatment-automation were also analyzed. RESULTS: Fifty-seven potential modes and effects were identified and classified into 'treatment cancellation' and 'delivering an unintended dose'. They were graded from 'inconvenience' or 'suboptimal treatment' to 'total cancellation' or 'potentially wrong' or 'very wrong administered dose', although these latter effects were never experienced. Risk priority numbers (RPNs) ranged from 3 to 324 and totaled 4804. After interventions such as double checking, interlocking, automation, and structural changes the final total RPN was reduced to 1320. CONCLUSIONS: FMEA is crucial for prioritizing risk-reduction interventions. In a semi-surgical procedure like IOERT double checking has the potential to reduce risk and improve quality. Interlocks and automation should also be implemented to increase the safety of the procedure.
BACKGROUND AND PURPOSE: Industrial companies use failure mode and effect analysis (FMEA) to improve quality. Our objective was to describe an FMEA and subsequent interventions for an automated intraoperative electron radiotherapy (IOERT) procedure with computed tomography simulation, pre-planning, and a fixed conventional linear accelerator. MATERIAL AND METHODS: A process map, an FMEA, and a fault tree analysis are reported. The equipment considered was the radiance treatment planning system (TPS), the Elekta Precise linac, and TN-502RDM-H metal-oxide-semiconductor-field-effect transistor in vivo dosimeters. Computerized order-entry and treatment-automation were also analyzed. RESULTS: Fifty-seven potential modes and effects were identified and classified into 'treatment cancellation' and 'delivering an unintended dose'. They were graded from 'inconvenience' or 'suboptimal treatment' to 'total cancellation' or 'potentially wrong' or 'very wrong administered dose', although these latter effects were never experienced. Risk priority numbers (RPNs) ranged from 3 to 324 and totaled 4804. After interventions such as double checking, interlocking, automation, and structural changes the final total RPN was reduced to 1320. CONCLUSIONS: FMEA is crucial for prioritizing risk-reduction interventions. In a semi-surgical procedure like IOERT double checking has the potential to reduce risk and improve quality. Interlocks and automation should also be implemented to increase the safety of the procedure.
Authors: B Ibanez-Rosello; J A Bautista; J Bonaque; J Perez-Calatayud; A Gonzalez-Sanchis; J Lopez-Torrecilla; L Brualla-Gonzalez; T Garcia-Hernandez; A Vicedo-Gonzalez; D Granero; A Serrano; B Borderia; C Solera; J Rosello Journal: Clin Transl Oncol Date: 2017-08-04 Impact factor: 3.405
Authors: Juan López-Tarjuelo; Ana Bouché-Babiloni; Virginia Morillo-Macías; Agustín Santos-Serra; Carlos Ferrer-Albiach Journal: Rep Pract Oncol Radiother Date: 2016-10-19
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: Juan López-Tarjuelo; Virginia Morillo-Macías; Ana Bouché-Babiloni; Enrique Boldó-Roda; Rafael Lozoya-Albacar; Carlos Ferrer-Albiach Journal: Radiat Oncol Date: 2016-03-15 Impact factor: 3.481
Authors: Blanca Ibanez-Rosello; Juan Antonio Bautista-Ballesteros; Jorge Bonaque; Francisco Celada; Françoise Lliso; Vicente Carmona; Jose Gimeno-Olmos; Zoubir Ouhib; Joan Rosello; Jose Perez-Calatayud Journal: J Contemp Brachytherapy Date: 2016-12-20
Authors: Prema Rassiah; Fan-Chi Frances Su; Y Jessica Huang; Dan Spitznagel; Vikren Sarkar; Martin W Szegedi; Hui Zhao; Adam B Paxton; Geoff Nelson; Bill J Salter Journal: J Appl Clin Med Phys Date: 2020-06-25 Impact factor: 2.102
Authors: Verónica García-Vázquez; Felipe A Calvo; María J Ledesma-Carbayo; Claudio V Sole; José Calvo-Haro; Manuel Desco; Javier Pascau Journal: PLoS One Date: 2020-01-10 Impact factor: 3.240