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通过深入分析确定由自动触发工具检测到的不良事件的原因。

Identifying causes of adverse events detected by an automated trigger tool through in-depth analysis.

作者信息

Muething S E, Conway P H, Kloppenborg E, Lesko A, Schoettker P J, Seid M, Kotagal U

机构信息

Division of Health Policy and Clinical Effectiveness, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio 45229, USA.

出版信息

Qual Saf Health Care. 2010 Oct;19(5):435-9. doi: 10.1136/qshc.2008.031393. Epub 2010 Aug 25.

Abstract

OBJECTIVES

To describe how in-depth analysis of adverse events can reveal underlying causes.

METHODS

Triggers for adverse events were developed using the hospital's computerised medical record (naloxone for opiate-related oversedation and administration of a glucose bolus while on insulin for insulin-related hypoglycaemia). Triggers were identified daily. Based on information from the medical record and interviews, a subject expert determined if an adverse drug event had occurred and then conducted a real-time analysis to identify event characteristics. Expert groups, consisting of frontline staff and specialist physicians, examined event characteristics and determined the apparent cause.

RESULTS

30 insulin-related hypoglycaemia events and 34 opiate-related oversedation events were identified by the triggers over 16 and 21 months, respectively. In the opinion of the experts, patients receiving continuous-infusion insulin and those receiving dextrose only via parenteral nutrition were at increased risk for insulin-related hypoglycaemia. Lack of standardisation in insulin-dosing decisions and variation regarding when and how much to adjust insulin doses in response to changing glucose levels were identified as common causes of the adverse events. Opiate-related oversedation events often occurred within 48 h of surgery. Variation in pain management in the operating room and post-anaesthesia care unit was identified by the experts as potential causes. Variations in practice, multiple services writing orders, multidrug regimens and variations in interpretation of patient assessments were also noted as potential contributing causes.

CONCLUSIONS

Identification of adverse drug events through an automated trigger system, supplemented by in-depth analysis, can help identify targets for intervention and improvement.

摘要

目的

描述对不良事件进行深入分析如何揭示潜在原因。

方法

利用医院的计算机化病历确定不良事件的触发因素(用于阿片类药物相关过度镇静的纳洛酮以及胰岛素治疗期间因胰岛素相关低血糖给予葡萄糖推注)。每日识别触发因素。根据病历信息和访谈,一名专家确定是否发生了药物不良事件,然后进行实时分析以确定事件特征。由一线工作人员和专科医生组成的专家组检查事件特征并确定表面原因。

结果

在16个月和21个月期间,分别通过触发因素识别出30例胰岛素相关低血糖事件和34例阿片类药物相关过度镇静事件。专家认为,接受持续输注胰岛素的患者以及仅通过肠外营养接受葡萄糖的患者发生胰岛素相关低血糖的风险增加。胰岛素剂量决策缺乏标准化以及在根据血糖水平变化调整胰岛素剂量的时间和剂量方面存在差异被确定为不良事件的常见原因。阿片类药物相关过度镇静事件通常发生在手术后48小时内。专家们确定手术室和麻醉后护理单元疼痛管理的差异是潜在原因。实践中的差异、多个科室开具医嘱、多药治疗方案以及患者评估解读的差异也被指出是潜在的促成原因。

结论

通过自动触发系统识别药物不良事件,并辅以深入分析,有助于确定干预和改进的目标。

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