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人工智能在识别预防导致严重或中度伤害的用药差错中的应用:基于不良事件报告者观点的分析。

Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters' Views.

机构信息

Department of Nursing Science/Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland.

Kuopio University Hospital, 70210 Kuopio, Finland.

出版信息

Int J Environ Res Public Health. 2021 Aug 31;18(17):9206. doi: 10.3390/ijerph18179206.

Abstract

The purpose of this study was to describe incident reporters' views identified by artificial intelligence concerning the prevention of medication incidents that were assessed, causing serious or moderate harm to patients. The information identified the most important risk management areas in these medication incidents. This was a retrospective record review using medication-related incident reports from one university hospital in Finland between January 2017 and December 2019 (n = 3496). Of these, incidents that caused serious or moderate harm to patients (n = 137) were analysed using artificial intelligence. Artificial intelligence classified reporters' views on preventing incidents under the following main categories: (1) treatment, (2) working, (3) practices, and (4) setting and multiple sub-categories. The following risk management areas were identified: (1) verification, documentation and up-to-date drug doses, drug lists and other medication information, (2) carefulness and accuracy in managing medications, (3) ensuring the flow of information and communication regarding medication information and safeguarding continuity of patient care, (4) availability, update and compliance with instructions and guidelines, (5) multi-professional cooperation, and (6) adequate human resources, competence and suitable workload. Artificial intelligence was found to be useful and effective to classifying text-based data, such as the free text of incident reports.

摘要

本研究旨在描述人工智能识别的、与预防对患者造成严重或中度伤害的用药事件相关的报告者观点。这些观点确定了这些用药事件中最重要的风险管理领域。这是一项回顾性病历审查,使用了芬兰一所大学医院 2017 年 1 月至 2019 年 12 月期间(n = 3496)的与药物相关的不良事件报告。在这些报告中,对造成患者严重或中度伤害的事件(n = 137)使用人工智能进行了分析。人工智能将报告者对预防事件的看法分为以下主要类别:(1)治疗,(2)工作,(3)实践,和(4)环境以及多个子类别。确定了以下风险管理领域:(1)核对、记录和更新药物剂量、药物清单和其他用药信息,(2)谨慎准确地管理药物,(3)确保药物信息的信息流通和沟通,以及保护患者护理的连续性,(4)指令和指南的可用性、更新和合规性,(5)多专业合作,以及(6)充足的人力资源、能力和适当的工作量。人工智能被发现对分类基于文本的数据(如不良事件报告的自由文本)非常有用和有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8466/8431329/2ef5c6e3ca74/ijerph-18-09206-g001.jpg

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