five

Reducing the Frequency of Errors in Medicine Using Information Technology

收藏
PubMed Central2026-05-16 收录
下载链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC130074/
下载链接
链接失效反馈
官方服务:
资源简介:
Background: Increasing data suggest that error in medicine is frequent and results in substantial harm. The recent Institute of Medicine report (LT Kohn, JM Corrigan, MS Donaldson, eds: To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press, 1999) described the magnitude of the problem, and the public interest in this issue, which was already large, has grown. Goal: The goal of this white paper is to describe how the frequency and consequences of errors in medical care can be reduced (although in some instances they are potentiated) by the use of information technology in the provision of care, and to make general and specific recommendations regarding error reduction through the use of information technology. Results: General recommendations are to implement clinical decision support judiciously; to consider consequent actions when designing systems; to test existing systems to ensure they actually catch errors that injure patients; to promote adoption of standards for data and systems; to develop systems that communicate with each other; to use systems in new ways; to measure and prevent adverse consequences; to make existing quality structures meaningful; and to improve regulation and remove disincentives for vendors to provide clinical decision support. Specific recommendations are to implement provider order entry systems, especially computerized prescribing; to implement bar-coding for medications, blood, devices, and patients; and to utilize modern electronic systems to communicate key pieces of asynchronous data such as markedly abnormal laboratory values. Conclusions: Appropriate increases in the use of information technology in health care— especially the introduction of clinical decision support and better linkages in and among systems, resulting in process simplification—could result in substantial improvement in patient safety.
提供机构:
Oxford University Press
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作