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Using failure mode and effects analysis (FMEA) to generate an initial plan check checklist for improved safety in radiation treatment.
Rassiah, Prema; Su, Fan-Chi Frances; Huang, Y Jessica; Spitznagel, Dan; Sarkar, Vikren; Szegedi, Martin W; Zhao, Hui; Paxton, Adam B; Nelson, Geoff; Salter, Bill J.
Afiliação
  • Rassiah P; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Su FF; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Huang YJ; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Spitznagel D; Avera Cancer Institute, Sioux Falls, SD, USA.
  • Sarkar V; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Szegedi MW; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Zhao H; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Paxton AB; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Nelson G; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
  • Salter BJ; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
J Appl Clin Med Phys ; 21(8): 83-91, 2020 Aug.
Article em En | MEDLINE | ID: mdl-32583912
ABSTRACT

PURPOSE:

To apply failure mode and effect analysis (FMEA) to generate an effective and efficient initial physics plan checklist.

METHODS:

A team of physicists, dosimetrists, and therapists was setup to reconstruct the workflow processes involved in the generation of a treatment plan beginning from simulation. The team then identified possible failure modes in each of the processes. For each failure mode, the severity (S), frequency of occurrence (O), and the probability of detection (D) was assigned a value and the risk priority number (RPN) was calculated. The values assigned were based on TG 100. Prior to assigning a value, the team discussed the values in the scoring system to minimize randomness in scoring. A local database of errors was used to help guide the scoring of frequency.

RESULTS:

Twenty-seven process steps and 50 possible failure modes were identified starting from simulation to the final approved plan ready for treatment at the machine. Any failure mode that scored an average RPN value of 20 or greater was deemed "eligible" to be placed on the second checklist. In addition, any failure mode with a severity score value of 4 or greater was also considered for inclusion in the checklist. As a by-product of this procedure, safety improvement methods such as automation and standardization of certain processes (e.g., dose constraint checking, check tools), removal of manual transcription of treatment-related information as well as staff education were implemented, although this was not the team's original objective. Prior to the implementation of the new FMEA-based checklist, an in-service for all the second checkers was organized to ensure further standardization of the process.

CONCLUSION:

The FMEA proved to be a valuable tool for identifying vulnerabilities in our workflow and processes in generating a treatment plan and subsequently a new, more effective initial plan checklist was created.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise do Modo e do Efeito de Falhas na Assistência à Saúde Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise do Modo e do Efeito de Falhas na Assistência à Saúde Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article