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Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment
BACKGROUND: Technological advancements have made it possible to improve patient outcomes in radiotherapy, sparing both normal tissues and increasing tumour control. However, these advancements have resulted in an increase in the number of software systems used, which each require data inputs to func...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113690/ https://www.ncbi.nlm.nih.gov/pubmed/36527239 http://dx.doi.org/10.1002/acm2.13868 |
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author | Donahue, William P. Draeger, Emily Han, Dae Yup Chen, Zhe |
author_facet | Donahue, William P. Draeger, Emily Han, Dae Yup Chen, Zhe |
author_sort | Donahue, William P. |
collection | PubMed |
description | BACKGROUND: Technological advancements have made it possible to improve patient outcomes in radiotherapy, sparing both normal tissues and increasing tumour control. However, these advancements have resulted in an increase in the number of software systems used, which each require data inputs to function. For institutions with multiple vendors for their treatment planning systems and oncology information systems, the transfer of data between them is potentially error prone and can lead to treatment errors. PURPOSE: The goal of this work was to determine the frequency of errors in data transfers between the Varian Eclipse treatment planning system and the Elekta Mosaiq oncology information system. METHODS: An in‐house program was used to quantify the number of errors for 2700 unique plans over an 8‐month period. Using this information, the frequency of the errors were calculated. A risk priority number was calculated using the calculated frequencies to determine the impact on the clinic. RESULTS: The most common errors discovered were backup timer settings (10.7%), Field label (8.5%), DRR associations (3.3%), imaging field types (3.1%), dose rate (1%), Field Id (0.8%), imaging isocenter (0.7% and SSD (0.7%). Based on the risk priority numbers, the DRR association error was ranked as having the highest potential impact on the patient. CONCLUSIONS: The results of the work show that the most effort should be focused on checking the manual steps performed in the transfer process, while items that are imported directly from DICOM‐RT without modification are highly likely to be transferred accurately. The data can be used to help guide the implementation of future automated tools and process improvement in the clinic. |
format | Online Article Text |
id | pubmed-10113690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101136902023-04-20 Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment Donahue, William P. Draeger, Emily Han, Dae Yup Chen, Zhe J Appl Clin Med Phys Radiation Oncology Physics BACKGROUND: Technological advancements have made it possible to improve patient outcomes in radiotherapy, sparing both normal tissues and increasing tumour control. However, these advancements have resulted in an increase in the number of software systems used, which each require data inputs to function. For institutions with multiple vendors for their treatment planning systems and oncology information systems, the transfer of data between them is potentially error prone and can lead to treatment errors. PURPOSE: The goal of this work was to determine the frequency of errors in data transfers between the Varian Eclipse treatment planning system and the Elekta Mosaiq oncology information system. METHODS: An in‐house program was used to quantify the number of errors for 2700 unique plans over an 8‐month period. Using this information, the frequency of the errors were calculated. A risk priority number was calculated using the calculated frequencies to determine the impact on the clinic. RESULTS: The most common errors discovered were backup timer settings (10.7%), Field label (8.5%), DRR associations (3.3%), imaging field types (3.1%), dose rate (1%), Field Id (0.8%), imaging isocenter (0.7% and SSD (0.7%). Based on the risk priority numbers, the DRR association error was ranked as having the highest potential impact on the patient. CONCLUSIONS: The results of the work show that the most effort should be focused on checking the manual steps performed in the transfer process, while items that are imported directly from DICOM‐RT without modification are highly likely to be transferred accurately. The data can be used to help guide the implementation of future automated tools and process improvement in the clinic. John Wiley and Sons Inc. 2022-12-16 /pmc/articles/PMC10113690/ /pubmed/36527239 http://dx.doi.org/10.1002/acm2.13868 Text en © 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Donahue, William P. Draeger, Emily Han, Dae Yup Chen, Zhe Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title | Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title_full | Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title_fullStr | Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title_full_unstemmed | Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title_short | Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
title_sort | frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113690/ https://www.ncbi.nlm.nih.gov/pubmed/36527239 http://dx.doi.org/10.1002/acm2.13868 |
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