风险评估体系在不同科室医院感染分类管理中的运用

Application of risk assessment system in classified management of healthcare-associated infection in different departments

摘要:

目的 在新型冠状病毒肺炎疫情常态化防控的形势下，建立一套全面、科学的风险评估体系，为医院管理决策提供支持。 方法 以山东省某综合性三级甲等医院为研究对象，首先进行全院整体层面的风险评估，由医院感染管理委员会成员采用头脑风暴的方法确定风险点和风险指标，通过风险评估矩阵计算出临床科室的风险分值，使用百分位数法对其进行风险等级评定，使用单因素方差分析或非参数检验比较不同风险组的差异，根据风险点的风险分值差异对临床科室进行分层聚类分析，再由评估出的极高风险科室使用失效模型和效应分析进行内部风险评估，最终根据两轮风险评估的结果进行风险应对。 结果 共61个临床科室参与评定。临床科室通过风险评估最终评定出8个风险点，24项风险指标。风险等级评估结果显示，神经外一科、神经外二科、神经重症监护病房、呼吸重症监护病房、重症医学科属于极高风险组，占8.20%；6个风险组的管理指标、过程指标和结局指标风险分值的比较，差异均有统计学意义(均P＜0.05)；层次聚类分析将临床科室分为3类，根据其特点分别定义为普通科室聚类组、重点科室聚类组和神经外科聚类组。极高风险科室通过内部风险评估评出7个高风险优先级问题，并有针对性地提出解决方案。 结论 本研究构建的风险评估体系可以对临床科室的风险等级进行有效的评定和分析，对极高风险科室的高风险优先级问题能进行有效风险应对，能明确下一步医院感染管理的重点。

Abstract:

Objective To establish a comprehensive and scientific risk assessment system under the normalized si-tuation of coronavirus disease 2019 (COVID -19) prevention and control, and provide support for decision-making of hospital management. Methods A comprehensive tertiary first-class hospital in Shandong Province was as the research object, risk assessment was carried out on hospital at overall level, risk points and risk indicators were determined with brainstorming method by members of healthcare-associated infection (HAI) management committee, risk scores of clinical departments were calculated through risk assessment matrix, risk grades were assessed with percentile method, differences among different risk groups were compared using one-way ANOVA or non-parame-tric test, clinical departments were performed stratified clustering analysis according to the difference of risk scores of risk points, the evaluated extremely high-risk departments were conduct internal risk assessment with failure model and effect analysis, and risk response was finally carried out according to results of two rounds of risk assessment. Results A total of 61 clinical departments participated in the assessment. Eight risk points and 24 risk indicators were ultimately determined by the risk assessment of the clinical departments. Risk grades assessment results indicated that the extremely high-risk departments were respectively as follows: neurosurgical departmentⅠ, neurosurgical departmentⅡ, neurological intensive care unit, respiratory intensive care unit and intensive care units, accounting for 8.20%; risk scores of management indicators, process indicators and outcome indicators of six risk groups were all significantly different (all P < 0.05); clinical departments were divided into 3 categories accor-ding to their characteristics with stratified cluster analysis, which were designated as general departments clustering group, key departments clustering group and neurosurgery department clustering group. Seven high-risk priority issues were assessed through internal risk assessment of extremely high-risk departments, targeted solutions were put forward. Conclusion The risk assessment system established in this study can effectively assess and analyze the risk grade of clinical departments, effectively respond to the high-risk priority issues of extremely high-risk departments, and clarify the key points of HAI management in the next step.