PRAISE: providing a roadmap for automated infection surveillance in Europe
van Mourik, Maaike S.M.; van Rooden, Stephanie M.; Abbas, Mohamed; Aspevall, Olov; Astagneau, Pascal; Bonten, Marc J.M.; Carrara, Elena; Gomila-Grange, Aina; de Greeff, Sabine C.; Gubbels, Sophie; Harrison, Wendy; Humphreys, Hilary; Johansson, Anders; Koek, Mayke B.G.; Kristensen, Brian; Lepape, Alain; Lucet, Jean Christophe; Mookerjee, Siddharth; Naucler, Pontus; Palacios-Baena, Zaira R.; Presterl, Elisabeth; Pujol, Miquel; Reilly, Jacqui; Roberts, Christopher; Tacconelli, Evelina; Teixeira, Daniel; Tängdén, Thomas; Valik, John Karlsson; Behnke, Michael; Gastmeier, Petra
(2021) Clinical Microbiology and Infection, volume 27, pp. S3 - S19
(Article)
Abstract
Introduction: Healthcare-associated infections (HAI) are among the most common adverse events of medical care. Surveillance of HAI is a key component of successful infection prevention programmes. Conventional surveillance – manual chart review – is resource intensive and limited by concerns regarding interrater reliability. This has led to the development and
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use of automated surveillance (AS). Many AS systems are the product of in-house development efforts and heterogeneous in their design and methods. With this roadmap, the PRAISE network aims to provide guidance on how to move AS from the research setting to large-scale implementation, and how to ensure the delivery of surveillance data that are uniform and useful for improvement of quality of care. Methods: The PRAISE network brings together 30 experts from ten European countries. This roadmap is based on the outcome of two workshops, teleconference meetings and review by an independent panel of international experts. Results: This roadmap focuses on the surveillance of HAI within networks of healthcare facilities for the purpose of comparison, prevention and quality improvement initiatives. The roadmap does the following: discusses the selection of surveillance targets, different organizational and methodologic approaches and their advantages, disadvantages and risks; defines key performance requirements of AS systems and suggestions for their design; provides guidance on successful implementation and maintenance; and discusses areas of future research and training requirements for the infection prevention and related disciplines. The roadmap is supported by accompanying documents regarding the governance and information technology aspects of implementing AS. Conclusions: Large-scale implementation of AS requires guidance and coordination within and across surveillance networks. Transitions to large-scale AS entail redevelopment of surveillance methods and their interpretation, intensive dialogue with stakeholders and the investment of considerable resources. This roadmap can be used to guide future steps towards implementation, including designing solutions for AS and practical guidance checklists.
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Keywords: Automated, Bloodstream infection, Data, Electronic health record, Healthcare-associated infection, Quality, Surgical site infection, Surveillance, Microbiology (medical), Infectious Diseases
ISSN: 1198-743X
Publisher: Elsevier Limited
Note: Funding Information: This network has been supported under the 7th transnational call within the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR), Network Call on Surveillance (2018) and was thereby funded by ZonMw (grant 549007001 ). This project also received support from the COMBACTE MAGNET EPI-Net project funded by the Innovative Medicines Initiative Joint Undertaking under grant agreement 115523 | 115620 | 115737 | 777362, resources of which are composed of financial contribution from the European Union Seventh Framework Programme ( FP7/2007-2013 ) and EFPIA companies in kind contribution. J.K.V. was supported by grants from Region Stockholm and Vinnova. H.H. reports grants from Pfizer and Astellas as well as personal fees from Pfizer outside the submitted work. All other authors report no conflicts of interest relevant to this article. Funding Information: This roadmap was written by the PRAISE network (Providing a Roadmap for Automated Infection Surveillance in Europe), which is funded by the Joint Programming Initiative Antimicrobial Resistance (JPIAMR) Network Call on Surveillance (2018). This network brings together 30 experts from ten European countries working in the field of HAI surveillance (mainly northern, western and southern Europe), with the majority working in university hospitals and some in public health institutes. The network included representatives of the COMBACTE-Magnet EPI-Net network, which provides barrier-free, timely access to data on the emergence and spread of antimicrobial resistance in humans and animals ( https://epi-net.eu/ ). Funding Information: This article is part of a supplement entitled Implementing Automated Surveillance of Healthcare-Associated Infections (HAI) sponsored by the PRAISE network (supported under 7th transnational call within the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR), Network Call on Surveillance (2018) and funded by ZonMw (grant number 549007001 )), the COMBACTE MAGNET EPI-Net project (funded by the Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115523 | 115620 | 115737 | 777362 resources of which are composed of financial contribution from the European Union Seventh Framework Programme ( FP7/2007-2013 ) and EFPIA companies in kind contribution) and Charité University Hospital. Publisher Copyright: © 2021
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