基于故障树方法的非计划再次手术风险评估

目的 探索一种适合于在过程复杂、环境多变、风险多样的手术治疗系统中，对术前准备、术中操作、术后医疗护理及管理等贯穿围手术期全过程进行风险评估的方法。方法 通过危险事件的风险影响因子识别、定性分析与定量分析、基本事件综合风险等级评价，绘制具有实践操作意义的风险矩阵图，全面识别手术治疗系统风险、科学分析危险事件与风险影响因子，有效评价风险等级与可容忍度。结果 构建包括7个中间事件、29个基本事件、9个逻辑或门和1个逻辑与门的非计划再次手术故障树模型，故障树由8个一阶割集和104个二阶割集组成。当所有最小割集均存在时，被调查医院非计划再次手术的发生概率为0.950 10，同时确定25个基本事件在该医院的综合风险重要性等级，并根据绘制的风险图谱进一步确定风险应对的优先顺序。结论 基于故障树的手术治疗系统风险评估方法，可以全面识别手术治疗系统风险，科学分析风险影响因子，有效评价风险等级。

Risk Evaluation of Unplanned Return to Operation Room by Fault Tree Analysis

Objective To explore a risk evaluation method applicable to the surgical treatment system with complex process, volatile environment and diverse risks which spans the whole perioperative surgical period from preoperative preparation, intraoperative operation to postoperative medical nursing and management. Methods Formulation of risk matrix by identification of risk influential factors of hazards, qualitative and quantitative analysis and evaluation of the risk grades of basic events could offer a comprehensive view about systematic risks of surgical treatment, scientific analysis of hazards and risk influential factors and effective evaluation of risk levels and tolerance. Results A fault tree model for unplanned return to operation room was constructed which encompassed 7 intermediate events, 29 basic events, 9 OR gates and 1 AND gate. Qualitative analysis in phase two revealed that afore fault tree was made up by 8 one-level cutsets and 104 two- level cutsets. Meanwhile, quantitative analysis derived that the probability of unplanned return to operation room in the investigated hospital was 0.95010. The probability and probability significance were determined for the remaining 25 basic events. Besides, the priority of response to risks was further determined in light of the risk spectrum. Conclusion The measure for risk evaluation of surgical treatment system based on fault tree proposed in the study could comprehensively identify systematic risks of surgical treatment, scientifically analyze risk influential factors, and effectively evaluate risk grades.