Centre for Health Informatics, University of New South Wales, Sydney, Australia.
J Am Med Inform Assoc. 2010 Nov-Dec;17(6):663-70. doi: 10.1136/jamia.2009.002444.
To analyze patient safety incidents associated with computer use to develop the basis for a classification of problems reported by health professionals.
Incidents submitted to a voluntary incident reporting database across one Australian state were retrieved and a subset (25%) was analyzed to identify 'natural categories' for classification. Two coders independently classified the remaining incidents into one or more categories. Free text descriptions were analyzed to identify contributing factors. Where available medical specialty, time of day and consequences were examined.
Descriptive statistics; inter-rater reliability.
A search of 42,616 incidents from 2003 to 2005 yielded 123 computer related incidents. After removing duplicate and unrelated incidents, 99 incidents describing 117 problems remained. A classification with 32 types of computer use problems was developed. Problems were grouped into information input (31%), transfer (20%), output (20%) and general technical (24%). Overall, 55% of problems were machine related and 45% were attributed to human-computer interaction. Delays in initiating and completing clinical tasks were a major consequence of machine related problems (70%) whereas rework was a major consequence of human-computer interaction problems (78%). While 38% (n=26) of the incidents were reported to have a noticeable consequence but no harm, 34% (n=23) had no noticeable consequence.
Only 0.2% of all incidents reported were computer related. Further work is required to expand our classification using incident reports and other sources of information about healthcare IT problems. Evidence based user interface design must focus on the safe entry and retrieval of clinical information and support users in detecting and correcting errors and malfunctions.
分析与计算机使用相关的患者安全事件,为卫生专业人员报告的问题分类奠定基础。
从澳大利亚一个州的自愿事件报告数据库中检索事件,并对其中的一个子集(25%)进行分析,以确定分类的“自然类别”。两名编码员独立地将其余事件分类为一个或多个类别。分析自由文本描述以确定促成因素。在有可用医疗专业、时间和后果的情况下进行检查。
描述性统计;组内一致性。
对 2003 年至 2005 年的 42616 起事件进行搜索,共发现 123 起与计算机相关的事件。在删除重复和不相关的事件后,有 99 起事件描述了 117 个问题。开发了一种包含 32 种计算机使用问题的分类。问题分为信息输入(31%)、传输(20%)、输出(20%)和一般技术(24%)。总体而言,55%的问题与机器有关,45%归因于人机交互。机器相关问题主要导致临床任务的启动和完成延迟(70%),而人机交互问题主要导致返工(78%)。虽然 38%(n=26)的事件报告有明显后果但无伤害,但 34%(n=23)无明显后果。
报告的所有事件中只有 0.2%与计算机有关。需要进一步使用事件报告和其他有关医疗保健信息技术问题的信息来源来扩展我们的分类。基于证据的用户界面设计必须侧重于安全地输入和检索临床信息,并支持用户检测和纠正错误和故障。