Suppr超能文献

与医疗信息技术故障相关的 2627 起患者安全事件的影响和可预防措施:对英格兰和威尔士 10 年来事件报告的回顾性分析。

The effects and preventability of 2627 patient safety incidents related to health information technology failures: a retrospective analysis of 10 years of incident reporting in England and Wales.

机构信息

National Institutes of Health Research Patient Safety Translational Research Centre, St Mary's Hospital, Imperial College London, London, UK.

Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, UK.

出版信息

Lancet Digit Health. 2019 Jul;1(3):e127-e135. doi: 10.1016/S2589-7500(19)30057-3. Epub 2019 Jun 27.

Abstract

BACKGROUND

The use of health information technology (IT) is rapidly increasing to support improvements in the delivery of care. Although health IT is delivering huge benefits, new technology can also introduce unique risks. Despite these risks, evidence on the preventability and effects of health IT failures on patients is scarce. In our study we therefore sought to evaluate the preventability and effects of health IT failures by examining patient safety incidents in England and Wales.

METHODS

We designed our study as a retrospective analysis of 10 years of incident reporting in England and Wales. We used text mining with the words "computer", "system", "workstation", and "network" to explore free-text incident descriptors to identify incidents related to health IT failures following a previously described approach. We then applied an n-gram model of searching to identify contiguous sequences of words and provide spatial context. We examined incident details, recorded harm, and preventability. Standard descriptive statistics were applied. Degree of harm was identified according to standardised definitions and preventability was assessed by two independent reviewers.

FINDINGS

We identified 2627 incidents related to health IT failures. 2557 (97%) of 2627 incidents were assessed for harm (70 incidents were excluded). 2106 (82%) of 2557 health IT failures caused no harm to patients, 331 (13%) caused low harm, 102 (4%) caused moderate harm, 14 (1%) caused severe harm, and four (<1%) contributed to the death of a patient. 1964 (75%) of 2627 incidents were deemed to be preventable.

INTERPRETATION

Health IT is fundamental to the delivery of high-quality care, yet there is a poor understanding of the effects of IT failures on patient safety and whether they can be prevented. Failures are complex and involve interlinked aspects of technology, people, and the environment. Health IT failures are undoubtedly a potential source of substantial harm, but they are likely to be under-reported. Worryingly, three-quarters of IT failures are potentially preventable. There is a need to see health IT as a fundamental tenet of patient safety, develop better methods for capturing the effects of IT failures on patients, and adopt simple measures to reduce their probability and mitigate their risk.

FUNDING

The National Institutes of Health Research Imperial Patient Safety Translational Research Centre at Imperial College London.

摘要

背景

为了支持医疗服务水平的提升,健康信息技术(Health Information Technology,简称 IT)的使用正在迅速增加。尽管健康 IT 带来了巨大的好处,但新技术也会带来独特的风险。尽管存在这些风险,但关于健康 IT 故障对患者的可预防性和影响的证据仍然很少。因此,在我们的研究中,我们试图通过检查英格兰和威尔士的患者安全事件来评估健康 IT 故障的可预防性和影响。

方法

我们将这项研究设计为对英格兰和威尔士 10 年事件报告的回顾性分析。我们使用了带有“computer”、“system”、“workstation”和“network”字样的文本挖掘技术,以探索自由文本事件描述符,以确定遵循先前描述的方法与健康 IT 故障相关的事件。然后,我们应用了 n-gram 模型搜索来识别连续的单词序列并提供空间上下文。我们检查了事件细节、记录的伤害和可预防性。应用了标准描述性统计。根据标准化定义确定伤害程度,由两名独立评审员评估可预防性。

结果

我们确定了 2627 起与健康 IT 故障相关的事件。在 2627 起事件中,有 2557 起(97%)评估了伤害程度(有 70 起事件被排除在外)。2557 起健康 IT 故障中有 2106 起(82%)未对患者造成伤害,331 起(13%)造成轻度伤害,102 起(4%)造成中度伤害,14 起(1%)造成严重伤害,4 起(<1%)导致患者死亡。2627 起事件中有 1964 起(75%)被认为是可预防的。

解释

健康 IT 是提供高质量医疗服务的基础,但人们对 IT 故障对患者安全的影响以及是否可以预防知之甚少。故障很复杂,涉及技术、人员和环境等方面的相互关联。健康 IT 故障无疑是一个潜在的重大伤害源,但很可能报告不足。令人担忧的是,四分之三的 IT 故障是可以预防的。需要将健康 IT 视为患者安全的基本原则,开发更好的方法来捕捉 IT 故障对患者的影响,并采取简单措施降低其发生概率并减轻其风险。

资助

英国帝国理工学院伦敦国家卫生研究院患者安全转化研究中心。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验