放射線腫瘍学における自動乳房放射線療法計画の臨床統合のための品質改善とプロセス再設計

To improve breast radiotherapy clinical workflows through a quality improvement approach rooted in implementation and improvement science methodologies. This study aims to demonstrate the effectiveness of these data-driven, multidisciplinary processes in optimizing complex clinical processes within radiation oncology.

A multidisciplinary stakeholder team applied an improvement science methodology to identify the root cause inefficiencies in a pre-treatment breast radiotherapy workflow. The intervention involved redesigning the task sequence and implementing an automated breast treatment planning solution to replace manual planning. The study evaluated the outcome measure of the target contouring time by the radiation oncologist and treatment planning time by the medical dosimetrist. The outcome measures for three cohorts were analyzed: (i) the initial cohort with manual planning prior to any process change, (ii) the pilot cohort with a limited stakeholder team for rapid change cycles with the modified clinical workflow and automated planning solution, and (iii) comprehensive roll-out with the entire clinical team. The balancing quality measures of dosimetric compliance to dose-volume histogram planning objectives were also assessed across the three cohorts.

From 2020 to 2022, 515 patients were included in the analysis. The task times from the initial cohort to the comprehensive roll-out cohort were 0.2 (± 0.07) hours and 0.2 (± 0.03) hours for radiation oncologist contouring time and 8 (± 4) hours and 4 (± 1) hours for medical dosimetrist planning time, respectively. At the conclusion of the comprehensive roll-out, total professional task time was decreased, and treatment plan quality was maintained. The approach successfully scaled from the smaller stakeholder team to the entire clinical workforce, demonstrating the effectiveness of implementation and improvement science methodologies.

This study provides a comprehensive description and evaluation of a data-driven, sustainable process change in a multidisciplinary breast radiotherapy workflow. The methodology utilized serves as a model for clinical workflow optimization across radiation oncology settings.