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)
| Autor: | Rachel Rabinovitch, Leah Schubert, Brian W. Miller, Brian D. Kavanagh, David Thomas, Quentin Diot, Sarah A. Milgrom, Moyed Miften |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
government.form_of_government computer.software_genre Workflow 030218 nuclear medicine & medical imaging Automation 03 medical and health sciences 0302 clinical medicine Documentation TBI Humans Radiation Oncology Physics Radiology Nuclear Medicine and imaging Operations management Radiation treatment planning Instrumentation Risk Management Radiation business.industry Radiotherapy Planning Computer-Assisted Treatment process Scripting language Proof of concept 030220 oncology & carcinogenesis government business computer Whole-Body Irradiation incident learning systems Incident report |
| Zdroj: | Journal of Applied Clinical Medical Physics |
| ISSN: | 1526-9914 |
| Popis: | Purpose To 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). Methods Analysis 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. Results Here 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 |
| Databáze: | OpenAIRE |
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