Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Department of Oncology Biostatistics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Int J Radiat Oncol Biol Phys. 2016 Apr 1;94(5):993-9. doi: 10.1016/j.ijrobp.2015.11.041. Epub 2015 Dec 14.
To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents.
We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons.
The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents.
We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.
描述自愿报告事件的放射治疗病例;并确定使患者面临更高风险的患者或治疗特异性因素。
我们使用机构的事件学习系统建立了一个数据库,其中包含 2011 年 1 月至 2013 年 12 月期间提交报告的患者。对所有报告事件的患者进行回顾性分析,根据流程和根本原因对患者进行分类。为比较生成了一个无事件患者的对照组。使用汇总统计,似然比和混合效应逻辑回归模型进行组间比较。
事件组和对照组分别包含 794 例和 499 例患者。常见的根本原因包括文件记录错误(26.5%),沟通(22.5%),技术治疗计划(37.5%)和技术治疗实施(13.5%)。与成人患者(0.4%)相比,未成年人(年龄<18 岁)更频繁地报告事件(37.7%)。头颈部(16%比 8%,P<.001)和乳房(20%比 15%,P=.03)的患者更频繁地发生事件,而脑(18%比 24%,P =.008)的患者则不太常见。较大的肿瘤(17%比 10%有 T4 病变,P=.02),且按方案治疗(9%比 5%,P=.005)或采用调强放疗/图像引导调强放疗的患者(52%比 43%,P<.001)更有可能发生事件。
我们发现了几个与事件相关的治疗和患者特异性变量。在同行评审时,这些因素应被治疗团队考虑,以确定风险较高的患者。需要更大的数据集来建议改变护理过程标准,以最大程度地降低安全风险。