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Electronically assisted surveillance systems of healthcare-associated infections: a systematic review
- H Roel A Streefkerk1,2 , Roel PAJ Verkooijen3 , Wichor M Bramer4 , Henri A Verbrugh1
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View Affiliations Hide AffiliationsAffiliations: 1 Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands 2 Albert Schweitzer Hospital/Rivas group Beatrix hospital/Regionaal Laboratorium medische Microbiologie, Dordrecht/Gorinchem, the Netherlands 3 Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands 4 Medical Library, Erasmus MC University Medical Center Rotterdam, Rotterdam, the NetherlandsRoel Streefkerkr.streefkerk asz.nl
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Citation style for this article: Streefkerk H Roel A, Verkooijen Roel PAJ, Bramer Wichor M, Verbrugh Henri A. Electronically assisted surveillance systems of healthcare-associated infections: a systematic review. Euro Surveill. 2020;25(2):pii=1900321. https://doi.org/10.2807/1560-7917.ES.2020.25.2.1900321 Received: 22 May 2019; Accepted: 04 Dec 2019
Abstract
Surveillance of healthcare-associated infections (HAI) is the basis of each infection control programme and, in case of acute care hospitals, should ideally include all hospital wards, medical specialties as well as all types of HAI. Traditional surveillance is labour intensive and electronically assisted surveillance systems (EASS) hold the promise to increase efficiency.
To give insight in the performance characteristics of different approaches to EASS and the quality of the studies designed to evaluate them.
In this systematic review, online databases were searched and studies that compared an EASS with a traditional surveillance method were included. Two different indicators were extracted from each study, one regarding the quality of design (including reporting efficiency) and one based on the performance (e.g. specificity and sensitivity) of the EASS presented.
A total of 78 studies were included. The majority of EASS (n = 72) consisted of an algorithm-based selection step followed by confirmatory assessment. The algorithms used different sets of variables. Only a minority (n = 7) of EASS were hospital-wide and designed to detect all types of HAI. Sensitivity of EASS was generally high (> 0.8), but specificity varied (0.37–1). Less than 20% (n = 14) of the studies presented data on the efficiency gains achieved.
Electronically assisted surveillance of HAI has yet to reach a mature stage and to be used routinely in healthcare settings. We recommend that future studies on the development and implementation of EASS of HAI focus on thorough validation, reproducibility, standardised datasets and detailed information on efficiency.
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