提高辐射瘤学的临床安全:以数据为导向的风险管理方法
Lukas Sölkner1, Dietmar Georg1, Uwe Wolff1
1Department of Radiation Oncology, Medical University of Vienna/University Hospital Vienna, Vienna, Austria.
Zeitschrift fur medizinische Physik
|March 9, 2025
概括
一个新的基于网络的系统通过使用实时数据来减少事故原因和检测之间的时间来改善放射性瘤风险管理. 这种数据驱动的方法提高了患者的安全性和治疗效率.
科学领域:
- 医学物理 医学物理
- 辐射瘤学 辐射瘤学
- 患者安全 患者安全
背景情况:
- 在放射性瘤学中,有效的风险管理 (RM) 是至关重要的.
- 传统的RM策略可能无法充分利用实时数据进行主动安全改进.
研究的目的:
- 在放射性瘤学中展示数据驱动的风险管理 (RM) 策略.
- 展示内部开发的基于Web的事件报告系统对实时分析的实用性.
- 通过加强临床风险优先级来提高患者安全和治疗效率.
主要方法:
- 开发并实施基于Web的事件报告系统,用于实时,匿名的事件捕获.
- 每月举行多学科RM团队会议,审查数据并决定干预措施.
- 分析了五年的事件数据,以评估安全障碍的有效性,并确定错误来源与检测点.
- 利用故障模式和影响分析 (FMEA) 进行有针对性的纠正行动.
主要成果:
- 该系统促进了响应性事件报告和定制的RM策略.
- 数据分析发现了绕过安全障碍的关键差距和错误,使得有针对性的对策成为可能.
- 自2019年以来实施的数据驱动的RM将事件原因和检测之间的平均流程步骤减半.
- 资源分析表明需要增加分配,开发需要约150小时,持续的RM平均占FTE的20%.
结论:
- 基于网络的系统在放射瘤学中推进了RM,通过实时分析确保了合规性并提高了安全性.
- 该系统有效地识别和减轻风险,加强质量保证 (QA) 的障碍.
- 适当的资源配置,包括增加RM的FTE,对于持续的改进至关重要.
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