3246 - Customized Electronic Quality Checklists to Reduce Errors and Improve Radiotherapy Workflow

Z. Mulla¹, R. Hashem², V. Arputharaj², H. Almarzouki³, A. AlMohamad¹, H. M. Muamenah¹, H. A. Hijazi³, H. Habibullah¹, and M. Attar³; ¹Department of Oncology, King Faisal Specialist Hospital and Research Center-Jeddah, Jeddah, Saudi Arabia, ²Department of Radiology, King Abdul-Aziz University Hospital, Jeddah, Saudi Arabia, ³Department of Radiology, Faculty of Medicine, King Abdul-Aziz University, Jeddah, Saudi Arabia

Purpose/Objective(s): Quality checklists (QCL) before delivery of radiotherapy are important for patient safety. Our aim was to develop automated QCL within MOSAIQ record and verify system to reduce errors and improve patient safety. Further, to facilitate the workflow by improving staff efficiency and mindfulness thereby providing effective, efficient timely radiotherapy (RT) treatment with all checks documented online. Materials/

Methods: A prospective quality improvement (QI) project was conducted at the radiation therapy unit, from January to May 2023. A dedicated team developed an automated QCL in the electronic patient file using MOSAIQ. These checklists, comprising various tasks assigned to RT department staff, map the flow of information and enable processing, confirmation, and documentation of essential patient data from treatment start to end. Each task includes a checklist based on the recommendations of American Association of Physicists in Medicine (AAPM) Task Groups 275 and 315, verified and signed off by responsible staff, facilitating tracking, auditing, and error identification. Errors were assessed using the Radiation Error Scoring System (RESS). The effectiveness of QCLs was evaluated through an audit assessing compliance and efficacy.

Inclusion Criteria: All patients treated with radiotherapy.
Results: Within our workflow, we have 20 QCL and 20 assessments in MOSAIQ from beginning of treatment to the end.

Compared to pre-implementation time, the QCL implementation helped streamline our work process by reducing, patient delays resulting from tasks not assigned previously. Additionally, it enabled reducing errors caused by demographic checks (from four to none) and failed verification of field parameters (from six to three). Overall, the number of errors due to verification checks was reduced by more than 50%. Additionally, timeout was included as an assessment before beam on with patient ID photo as a verification check to ensure a smooth workflow with minimal risk to patient. The timeout included patient identification by two therapists, site and laterality, monitor units, phase, position and accessories, and read out of all parameters. With the implementation of QCL we identified potential misses and observed a reduction in the number of level three and four errors.
Conclusion: The introduction of automated QCLs significantly improved RT workflow efficiency, error reduction, and safety in our practices as identified by ASTRO Accreditation Program for Excellence (APEX).Future research should focus on extending the evaluation period and including diverse cancer types for a more comprehensive understanding of the QCL models impact.