一种数据驱动的方法来解决RT调度问题
Mruga Gurjar1, Jesper Lindberg1,2,3, Thomas Björk-Eriksson3,4
1Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sweden.
Technical innovations & patient support in radiation oncology
|November 5, 2024
概括
一个自动化放射治疗调度算法减少了10%的患者延迟,并将平均等待时间缩短了两周. 该策略通过根据个体需求对患者进行优先排序,优化资源配置,从而提高放射治疗工作流程的效率.
科学领域:
- 在瘤学瘤学.
- 医学物理 医学物理
- 医疗信息学 医疗信息学
背景情况:
- 放射治疗 (RT) 的需求正在增加,由于其时间关键和相互依存的工作流程,它提出了复杂的调度挑战.
- 调度延误是RT部门普遍存在的全球问题,影响患者护理和运营效率.
研究的目的:
- 开发和评估一个自动化策略,用于生成患者分配列表,以改善放射治疗安排.
- 帮助安排人员创建一个更有效和更及时的放射治疗治疗过程.
主要方法:
- 利用来自一个大型瑞典RT部门 (2022) 的历史数据,使用了11-13个线性加速器.
- 开发了一个C#算法,结合了患者特定的因素:时间表,预订类别,诊断和治疗意图,以确定个体优先级.
主要成果:
- 算法生成了一个优先级的每周患者安排列表.
- 与手动分配相比,该算法减少了10%的患者延迟,平均延迟减少了2周.
- 算法驱动的优先级改进了不同诊断组之间的平衡.
结论:
- 通过快速评估患者资料,自动化算法可以显著减少RT工作人员的调度时间.
- 实施这些算法可以加快RT调度决策,提高部门的整体绩效,从而避免组织发生重大变化.
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