ArticleJournal of applied clinical medical physics2020
Integration of automation into an existing clinical workflow to improve efficiency and reduce errors in the manual treatment planning process for total body irradiation (TBI).
Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Optimised conformal total body irradiation: a heterogeneous practice, so where next?The British journal of radiology · 2023Review
- Automation and integration of a novel restricted single-isocenter stereotactic body radiotherapy (a-RESIST) method for synchronous two lung lesions.Journal of applied clinical medical physics · 2021Article
- A Probability-Based Investigation on the Setup Robustness of Pencil-beam Proton Radiation Therapy for Skull-Base Meningioma.International journal of particle therapy · 2021Article
- Mitigation of Intensity Modulated Radiation Therapy and Stereotactic Body Radiation Therapy Treatment Planning Errors on the Novel RefleXion X1 System Using Failure Mode and Effect Analysis Within Six Sigma Framework.Advances in radiation oncologyArticle
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Authors and funding
8 authors.
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Abstract
purposeTo identify causes of error, and present the concept of an automated technique that improves efficiency and helps to reduce transcription and manual data entry errors in the treatment planning of total body irradiation (TBI).
methodsAnalysis of incidents submitted to incident learning system (ILS) was performed to identify potential avenues for improvement by implementation of automation of the manual treatment planning process for total body irradiation (TBI). Following this analysis, it became obvious that while the individual components of the TBI treatment planning process were well implemented, the manual 'bridging' of the components (transcribing data, manual data entry etc.) were leading to high potential for error. A C#-based plug-in treatment planning script was developed to remove the manual parts of the treatment planning workflow that were contributing to increased risk.
resultsHere we present an example of the implementation of "Glue" programming, combining treatment planning C# scripts with existing spreadsheet calculation worksheets. Prior to the implementation of automation, 35 incident reports related to the TBI treatment process were submitted to the ILS over a 6-year period, with an average of 1.4 ± 1.7 reports submitted per quarter. While no incidents reached patients, reports ranged from minor documentation issues to potential for mistreatment if not caught before delivery. Since the implementation of automated treatment planning and documentation, treatment planning time per patient, including documentation, has been reduced; from an average of 45 min pre-automation to <20 min post-automation.
conclusionsManual treatment planning techniques may be well validated, but they are time-intensive and have potential for error. Often the barrier to automating these techniques becomes the time required to "re-code" existing solutions in unfamiliar computer languages. We present the workflow here as a proof of concept that automation may help to improve clinical efficiency and safety for special procedures.
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