An automated electronic system for managing radiation treatment plan peer review reduces missed reviews at a large, high-volume academic center

Gabriel, Peter; Woodhouse, Kristina D.; Lin, Alexander; Finlay, Jarod C.; Young, Richard B.; Volz, Edna; Hahn, Stephen M.; Metz, James M.; Maity, Amit

doi:10.1016/j.prro.2016.03.004

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…We expect that clinical use of our chart review solution will provide data on the frequency of different types of errors encountered as has been reported in other studies 12,13,24,23 . This will permit subsequent data mining for a more complete risk assessment, and concomitant risk reduction 25 . This can take the form of a systematic review of where most errors are generated and training to reduce these errors.…”

Section: Discussionmentioning

confidence: 88%

Graph‐based risk assessment and error detection in radiation therapy

2021

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Purpose The objective of this study was to formalize and automate quality assurance (QA) in radiation oncology. Quality assurance in radiation oncology entails a multistep verification of complex, personalized radiation plans to treat cancer involving an interdisciplinary team and high technology, multivendor software and hardware systems. We addressed the pretreatment physics chart review (TPCR) using methods from graph theory and constraint programming to study the effect of dependencies between variables and automatically identify logical inconsistencies and how they propagate. Materials and methods We used a modular approach to decompose the TPCR process into tractable units comprising subprocesses, modules and variables. Modules represented the main software entities comprised in the radiation treatment planning workflow and subprocesses grouped the checks to be performed by functionality. Module‐associated variables served as inputs to the subprocesses. Relationships between variables were modeled by means of a directed graph. The detection of errors, in the form of inconsistencies, was formalized as a constraint satisfaction problem whereby checks were encoded as logical formulae. The sequence in which subprocesses were visited was described in an activity diagram. Results The comprehensive model for the TPCR process comprised 5 modules, 19 subprocesses and 346 variables, 225 of which were distinct. Modules included “Treatment Planning System” and “Record and Verify System.” Subprocesses included “Dose Prescription,” “Documents,” “CT Integrity,” “Anatomical Contours,” “Beam Configuration,” “Dose Calculation,” “3D Dose Distribution Quality,” and “Treatment Approval.” Variable inconsistencies, and their source and propagation were determined by checking for constraint violation and through graph traversal. Impact scores, obtained through graph traversal, combined with severity scores associated with an inconsistency, allowed risk assessment. Conclusions Directed graphs combined with constraint programming hold promise for formalizing complex QA processes in radiation oncology, performing risk assessment and automating the TPCR process. Though complex, the process is tractable.

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Section: Discussionmentioning

confidence: 88%

Graph‐based risk assessment and error detection in radiation therapy

2021

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“…Once the department has committed to the performance of this process, the challenge then moves to reduction of the burden on the staff. Solutions to this vary, but may include automation of data collection and presentation, reasonable expectations for timely patient starts based on optimal timetables for patient outcomes, and defined criteria for the performance of pre-treatment peer review, even going so far as to allow some portions of the peer review to occur separately such as reviewing contours first and the treatment plan later (18, 74, 75). Ultimately, human capabilities are limited and we may see this type of peer review become more and more automated through the use of tools like machine learning and artificial intelligence.…”

Section: Discussionmentioning

confidence: 99%

Chasing Zero Harm in Radiation Oncology: Using Pre-treatment Peer Review

et al. 2019

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Purpose: The Joint Commission has encouraged the healthcare industry to become “High Reliability Organizations” by “Chasing Zero Harm” in patient care. In radiation oncology, the time point of quality checks determines whether errors are prevented or only mitigated. Thus, to “chase zero” in radiation oncology, peer review has to be implemented prior to treatment initiation. A multidisciplinary group consensus peer review (GCPR) model is used pre-treatment at our institution and has been successful in our efforts to “chase zero harm” in patient care. Methods: With the GCPR model, policy-defined complex cases go through a treatment planning conference, which includes physicians, residents, physicists, and dosimetrists. Three major plan aspects are reviewed: target volumes, target and normal tissue dose coverage, and dose distributions. During the review, any team member can ask questions and afterwards a group consensus is taken regarding plan approval. Results: The GCPR model has been implemented through a commitment to peer review and creative conference scheduling. Automated analysis software is used to depict color-coded results for department approved target coverage and dose constraints. About 8% of plans required re-planning while about 23% required minor changes. The mean time for review of each plan was 8 min. Conclusions: Catching errors prior to treatment is the only way to “chase zero” in radiation oncology. Various types of errors may exist in treatment plans and our GCPR model succeeds in preventing many errors of all shapes and sizes in target definition, dose prescriptions, and treatment plans from ever reaching the patients.

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“…The 2019 revision of the PRAT was designed considering the results of the survey, the ASTRO 2013 white paper on peer review, 43 the RCR 2017 document on target volume delineation and peer review 42 and other peer review tools used in practice and described in the literature. [14][15][16][17]19,29 It simplified the documentation requirements and focused on radiation therapy management and plan review, with a 'major/minor changes recommended system introduced. A draft was sent to RANZCR members in September 2019 for feedback, with the revised version subsequently approved by the RANZCR Council in December 2019 and public release in January 2020.…”

Section: Prat Revisionmentioning

confidence: 99%

“…Various peer review tools have been reported in the literature, [14][15][16][17]19,29,37 such as the UK Royal College of Radiologists (RCR) guidelines on target volume definition and peer review. 42 Recognising the importance of peer review in radiation oncology, the RANZCR Post-Fellowship Education Committee (PFEC) in 1999 developed the RANZCR Peer Review Audit Tool for Radiation Oncology (PRAT) for use as a revalidation and quality improvement instrument.…”

Section: Ranzcr Peer Review Audit Tool (Prat)mentioning

confidence: 99%

“…In Australia and internationally, peer review has been reported to improve patient care both directly and indirectly and be feasible within radiation oncology facilities 6–35 . The American Society for Radiation Oncology (ASTRO) surveyed members in 2013 to establish peer review practice patterns, 36 with the majority of the 572 participating physicians supporting formal recommendation and guidance on peer review.…”

Section: Introductionmentioning

confidence: 99%

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Radiation oncology peer review in Australia and New Zealand

Chin

Ong

et al. 2022

J Med Imag Rad Onc

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Summary Peer review is a part of high quality care within radiation oncology, designed to achieve the best outcomes for patients. We discuss the importance of and evidence for peer review in clinical practice. The Royal Australia and New Zealand College of Radiologists (RANZCR) has evolved a Peer Review Assessment Tool (PRAT) since 1999. We report the results of a RANZCR faculty survey conducted in radiation oncology facilities across Australia and New Zealand to guide the 2019 PRAT revision process, and discuss the development and implementation of the 2019 PRAT. Peer‐review processes are now mandated as a component of Australian and International Quality Standards. Several practical recommendations might address challenges for effective implementation of peer review process in routine clinical practice. This includes prioritising tumour sites and treatment techniques for peer review within the time and resources constraints of each institution, improving resource allocation, ensuring optimal timing and duration for peer review meetings, and adopting multi‐centre virtual peer review meeting where necessary.

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An automated electronic system for managing radiation treatment plan peer review reduces missed reviews at a large, high-volume academic center

Cited by 6 publications

References 10 publications

Graph‐based risk assessment and error detection in radiation therapy

Graph‐based risk assessment and error detection in radiation therapy

Chasing Zero Harm in Radiation Oncology: Using Pre-treatment Peer Review

Radiation oncology peer review in Australia and New Zealand

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