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

Copyright © 2021. Published by Elsevier Ltd..

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:27 Suppl 1

Enthalten in:

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases - 27 Suppl 1(2021) vom: 15. Juli, Seite S29-S39

Sprache:

Englisch

Beteiligte Personen:

Behnke, Michael [VerfasserIn]
Valik, John Karlsson [VerfasserIn]
Gubbels, Sophie [VerfasserIn]
Teixeira, Daniel [VerfasserIn]
Kristensen, Brian [VerfasserIn]
Abbas, Mohamed [VerfasserIn]
van Rooden, Stephanie M [VerfasserIn]
Gastmeier, Petra [VerfasserIn]
van Mourik, Maaike S M [VerfasserIn]
PRAISE network [VerfasserIn]
van Mourik, Maaike S M [Sonstige Person]
van Rooden, Stephanie M [Sonstige Person]
Abbas, Mohamed [Sonstige Person]
Aspevall, Olov [Sonstige Person]
Astagneau, Pascal [Sonstige Person]
Bonten, Marc J M [Sonstige Person]
Carrara, Elena [Sonstige Person]
Gomila-Grange, Aina [Sonstige Person]
de Greeff, Sabine C [Sonstige Person]
Gubbels, Sophie [Sonstige Person]
Harrison, Wendy [Sonstige Person]
Humphreys, Hilary [Sonstige Person]
Johansson, Anders [Sonstige Person]
Koek, Mayke B G [Sonstige Person]
Kristensen, Brian [Sonstige Person]
Lepape, Alain [Sonstige Person]
Lucet, Jean-Christophe [Sonstige Person]
Mookerjee, Siddharth [Sonstige Person]
Naucler, Pontus [Sonstige Person]
Palacios-Baena, Zaira R [Sonstige Person]
Presterl, Elisabeth [Sonstige Person]
Pujol, Miquel [Sonstige Person]
Reilly, Jacqui [Sonstige Person]
Roberts, Christopher [Sonstige Person]
Tacconelli, Evelina [Sonstige Person]
Teixeira, Daniel [Sonstige Person]
Tängdén, Thomas [Sonstige Person]
Valik, John Karlsson [Sonstige Person]
Behnke, Michael [Sonstige Person]
Gastmeier, Petra [Sonstige Person]

Links:

Volltext

Themen:

Automated
Bloodstream infection
Data
Digital infection control
Electronic HAI surveillance
Electronic health record
Healthcare-associated infection
Journal Article
Quality
Surgical site infection
Surveillance

Anmerkungen:

Date Completed 01.11.2021

Date Revised 01.11.2021

published: Print

Citation Status MEDLINE

doi:

10.1016/j.cmi.2021.02.027

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM327641258