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A method for empirically validating FMEA RPN scores in a radiation oncology clinic using physics QC data.

Leonard H KimBadal R JunejaNatalie N Viscariello
Published in: Journal of applied clinical medical physics (2024)
In failure modes and effects analysis (FMEA), the components of the risk priority number (RPN) for a failure mode (FM) are often chosen by consensus. We describe an empirical method for estimating the occurrence (O) and detectability (D) components of a RPN. The method requires for a given FM that its associated quality control measure be performed twice as is the case when a FM is checked for in an initial physics check and again during a weekly physics check. If instances of the FM caught by these checks are recorded, O and D can be computed. Incorporation of the remaining RPN component, Severity, is discussed. This method can be used as part of quality management design ahead of an anticipated FMEA or afterwards to validate consensus values.
Keyphrases
  • quality control
  • risk assessment
  • clinical practice
  • primary care
  • machine learning
  • magnetic resonance imaging
  • big data
  • quality improvement
  • deep learning
  • artificial intelligence