TY - JOUR
T1 - Information technology aspects of large-scale implementation of automated surveillance of healthcare-associated infections
AU - Behnke, Michael
AU - Valik, John Karlsson
AU - Gubbels, Sophie
AU - Teixeira, Daniel
AU - Kristensen, Brian
AU - Abbas, Mohamed
AU - van Rooden, Stephanie M.
AU - Gastmeier, Petra
AU - van Mourik, Maaike S.M.
AU - PRAISE network
AU - Reilly, Jacqui
N1 - Acceptance from VoR
OA article
PY - 2021/7/1
Y1 - 2021/7/1
N2 - 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.
AB - 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.
KW - automated, bloodstream infection, data, digital infection control, electronic HAI surveillance, electronic health record, healthcare-associated infection, quality, surgical site infection, surveillance
U2 - 10.1016/j.cmi.2021.02.027
DO - 10.1016/j.cmi.2021.02.027
M3 - Article
C2 - 34217465
VL - 27
SP - S29-S39
JO - Clinical Microbiology and Infection
JF - Clinical Microbiology and Infection
SN - 1198-743X
IS - Suppl 1
ER -