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PRAISE: providing a roadmap for automated infection surveillance in Europe. | LitMetric

AI Article Synopsis

  • Healthcare-associated infections (HAI) are common issues in medical care, and automated surveillance (AS) presents a way to improve monitoring over conventional manual methods, which can be resource-intensive and inconsistent.
  • The PRAISE network, consisting of 30 experts from ten European countries, has created a roadmap to help implement AS effectively across healthcare networks, ensuring data consistency for quality improvement.
  • The roadmap outlines key aspects like selecting surveillance targets, designing AS systems, maintaining them, and identifying further research needs, all while providing additional documents on governance and technology for a successful transition.

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 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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Source
http://dx.doi.org/10.1016/j.cmi.2021.02.028DOI Listing

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