JCO global oncology · 2025
Implementing Customized Electronic Quality Checklists to Reduce Errors and Improve Workflow in Radiotherapy.
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Mulla Zaheeda, Joseph John Victor J, Hashem Rania, Almarzouki Hatim Z, Almohamad Abdullah, Attar Mohammad, Muamenah Hane, Habibullah Hanadi F, Hijazi Hussam
Аннотация
PURPOSE: Advancements in radiation oncology have improved treatment precision and effectiveness but increased procedural complexity and error risk because of higher patient volumes. This study aimed to implement and evaluate automated quality checklists (QCLs) to reduce errors and enhance patient safety in radiotherapy (RT) workflows.
METHODS: This prospective quality improvement study was conducted at the RT unit of King Faisal Specialist Hospital and Research Centre and King Abdulaziz University Hospital, Jeddah, Saudi Arabia, from January to March 2023. Automated QCLs were developed in the electronic patient files using MOSAIQ. These QCLs comprised various tasks assigned to RT staff, with each task including a customized electronic assessment checklist. Errors were assessed using the Radiation Error Scoring System. The effectiveness of QCLs was evaluated through an audit assessing compliance and efficacy.
RESULTS: A total of 20 QCLs and 20 assessments were created. Compared with preimplementation, the implementation of QCL helped streamline the work process and reduce patient delays resulting from tasks not assigned previously and errors caused by verification checks by 50%. Sufficient time was allocated for checks in each area, particularly for the RT chart checks because more than 50% of the errors were detected in the RT chart checks. The audit revealed a reduction in planning delays from 42 (8.3%) of 503 cases before intervention to 25 (4.2%) of 590 cases after intervention. With the implementation of QCL, potential misses were identified, and a reduction in level three and four errors was observed.
CONCLUSION: Automated QCLs significantly improved RT workflow efficiency and safety and reduced errors in our practices.
METHODS: This prospective quality improvement study was conducted at the RT unit of King Faisal Specialist Hospital and Research Centre and King Abdulaziz University Hospital, Jeddah, Saudi Arabia, from January to March 2023. Automated QCLs were developed in the electronic patient files using MOSAIQ. These QCLs comprised various tasks assigned to RT staff, with each task including a customized electronic assessment checklist. Errors were assessed using the Radiation Error Scoring System. The effectiveness of QCLs was evaluated through an audit assessing compliance and efficacy.
RESULTS: A total of 20 QCLs and 20 assessments were created. Compared with preimplementation, the implementation of QCL helped streamline the work process and reduce patient delays resulting from tasks not assigned previously and errors caused by verification checks by 50%. Sufficient time was allocated for checks in each area, particularly for the RT chart checks because more than 50% of the errors were detected in the RT chart checks. The audit revealed a reduction in planning delays from 42 (8.3%) of 503 cases before intervention to 25 (4.2%) of 590 cases after intervention. With the implementation of QCL, potential misses were identified, and a reduction in level three and four errors was observed.
CONCLUSION: Automated QCLs significantly improved RT workflow efficiency and safety and reduced errors in our practices.