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大规模实施医疗保健相关感染自动化监测的信息技术方面。

Information technology aspects of large-scale implementation of automated surveillance of healthcare-associated infections.

机构信息

National Reference Center for Surveillance of Nosocomial Infections, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Hygiene and Environmental Medicine, Berlin, Germany.

Department of Medicine Solna, Division of Infectious Diseases, Karolinska Institutet and Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden.

出版信息

Clin Microbiol Infect. 2021 Jul;27 Suppl 1:S29-S39. doi: 10.1016/j.cmi.2021.02.027.

Abstract

INTRODUCTION

Healthcare-associated infections (HAI) are a major public health concern. Monitoring of HAI rates, with feedback, is a core component of infection prevention and control programmes. Digitalization of healthcare data has created novel opportunities for automating the HAI surveillance process to varying degrees. However, methods are not standardized and vary widely between different healthcare facilities. Most current automated surveillance (AS) systems have been confined to local settings, and practical guidance on how to implement large-scale AS is needed.

METHODS

This document was written by a task force formed in March 2019 within the PRAISE network (Providing a Roadmap for Automated Infection Surveillance in Europe), gathering experts in HAI surveillance from ten European countries.

RESULTS

The document provides an overview of the key e-health aspects of implementing an AS system of HAI in a clinical environment to support both the infection prevention and control team and information technology (IT) departments. The focus is on understanding the basic principles of storage and structure of healthcare data, as well as the general organization of IT infrastructure in surveillance networks and participating healthcare facilities. The fundamentals of data standardization, interoperability and algorithms in relation to HAI surveillance are covered. Finally, technical aspects and practical examples of accessing, storing and sharing healthcare data within a HAI surveillance network, as well as maintenance and quality control of such a system, are discussed.

CONCLUSIONS

With the guidance given in this document, along with the PRAISE roadmap and governance documents, readers will find comprehensive support to implement large-scale AS in a surveillance network.

摘要

简介

医疗保健相关感染(HAI)是一个主要的公共卫生关注点。监测 HAI 发生率并提供反馈是感染预防和控制计划的核心组成部分。医疗保健数据的数字化为自动监测 HAI 的过程创造了新的机会,在不同程度上实现了自动化。然而,方法尚未标准化,在不同的医疗保健机构之间差异很大。大多数当前的自动化监测(AS)系统仅限于本地设置,需要关于如何实施大规模 AS 的实用指南。

方法

本文件由 2019 年 3 月在 PRAISE 网络(为欧洲自动化感染监测提供路线图)内成立的一个工作组撰写,该工作组汇集了来自十个欧洲国家的 HAI 监测专家。

结果

本文概述了在临床环境中实施 HAI 自动监测系统的关键电子健康方面,以支持感染预防和控制团队以及信息技术(IT)部门。重点是了解医疗保健数据存储和结构的基本原理,以及监测网络和参与医疗保健机构的 IT 基础设施的一般组织。涵盖了与 HAI 监测相关的数据标准化、互操作性和算法的基本原理。最后,讨论了在 HAI 监测网络中访问、存储和共享医疗保健数据的技术方面和实际示例,以及此类系统的维护和质量控制。

结论

有了本文提供的指导,以及 PRAISE 路线图和治理文件,读者将在监测网络中实施大规模 AS 方面找到全面的支持。

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