Evidence map›Paper›PMID 42596053›Full record

ArticleJournal of applied clinical medical physics2026

Application of an updated severity-based FMEA approach to Radiation Therapy QA: A multi-institutional exercise.

Alejandra Rangel, Ryan Studinski, Ady Abdellatif, Leigh Conroy, Jenna King, Humza Nusrat, Michael Oliver

Abstract readMulticenter Study
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alejandra RangelMedical Physics Department, Trillium Health Partners - Credit Valley Hospital, Mississauga, Ontario, Canada.
Ryan StudinskiDepartment of Physics, Juravinski Hospital and Cancer Centre at Hamilton Health Sciences, Hamilton, Ontario, Canada.
Ady AbdellatifMedical Physics Department, R. S. McLaughlin Durham Regional Cancer Centre, Lakeridge Health, Oshawa, Ontario, Canada.
Leigh ConroyRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Jenna KingMedical Physics Department, Hudson Regional Cancer Program (North Simcoe Muskoka), Royal Victoria Regional Health Centre, Barrie, Ontario, Canada.
Humza NusratDepartment of Radiation Oncology, Henry Ford Health, Detroit, Michigan, USA.ORCID https://orcid.org/0009-0000-0562-0127
Michael OliverMedical Physics Department, Shirley and Jim Fielding Northeast Cancer Center, Health Sciences North, Sudbury, Ontario, Canada.

Funding

Ontario Health
6 · The paper itself

Abstract

backgroundExternal beam radiation therapy (RT) involves many complex steps to safely and reliably treat patients. The radiation oncology community has adopted process maps and failure modes and effects analysis (FMEA) to analyze risk using the TG‑100 methodology, but the traditional TG‑100-endorsed risk priority number (RPN) has recognized limitations. An updated risk‑profile introduced by the automotive industry, action priority (AP), offers a severity‑weighted alternative that may better support risk‑based decision‑making in RT. PURPOSE: To compare the traditional RPN-based FMEA approach with the updated AP-based approach for identifying high-risk potential failure modes (PFMs) in a representative external beam RT workflow across multiple institutions, and to assess whether the AP framework provides additional value to the radiation oncology community.

methodsNine physicists from different cancer centers in Ontario, Canada collaboratively developed and refined a list of 63 PFMs associated with a generic RT workflow requiring data transfer. Each PFM was scored for occurrence (O), severity (S), and detectability (D) using TG‑100 recommendations. Three scoring scenarios were evaluated: average, worst‑case, and a severity‑focused score. High‑risk PFMs were identified using the traditional (top RPN quartile and/or S ≥ 8) and the updated (High or Medium AP categories) FMEA criteria.

resultsSeven high‑risk PFMs were selected using the updated FMEA, and an additional 23 were selected using the traditional FMEA. All PFMs identified by the updated FMEA approach were also selected by the traditional FMEA approach; however, the traditional FMEA approach identified many additional PFMs due to its quartile‑based and severity-threshold criteria. The updated AP approach appeared less affected by the scoring variability which may reduce the need for consensus discussion, it was generally easier to apply, showed more consistent behaviour across FMEA iterations and provided a clearer action guidance.

conclusionsThe use of the updated AP approach in this study suggests a clearer, severity-driven, and more streamlined strategy to prioritize high-risk PFMs, potentially reducing the burden of multi‑institutional FMEA while maintaining consistent identification of critical risks.

Indexed as

Healthcare Failure Mode and Effect AnalysisNeoplasmsQuality Assurance, Health CareRadiotherapy Planning, Computer-AssistedHumansRadiotherapy Dosageaction priorityFMEAmulti‑institutional studyquality managementrisk priority number

Identifiers

PMID42596053
PMCPMC13473695

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.