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Automated surveillance systems for healthcare-associated infections: results from a European survey and experiences from real-life utilization.
Verberk, J D M; Aghdassi, S J S; Abbas, M; Nauclér, P; Gubbels, S; Maldonado, N; Palacios-Baena, Z R; Johansson, A F; Gastmeier, P; Behnke, M; van Rooden, S M; van Mourik, M S M.
  • Verberk JDM; Department of Medical Microbiology and Infection Prevention, University Medical Centre Utrecht, Utrecht, the Netherlands; Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; Department of Epidemiology and Surveillance, Centre for Infectiou
  • Aghdassi SJS; Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digi
  • Abbas M; Infection Control Programme, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
  • Nauclér P; Department of Medicine Solna, Division of Infectious Disease, Karolinska Institutet, Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden.
  • Gubbels S; Department of Infectious Disease Preparedness, Statens Serum Institut, Copenhagen, Denmark.
  • Maldonado N; Unit of Infectious Diseases, Clinical Microbiology and Preventive Medicine, Hospital Universitario Virgen Macarena, Institute of Biomedicine of Seville (IBIS), Sevilla, Spain.
  • Palacios-Baena ZR; Unit of Infectious Diseases, Clinical Microbiology and Preventive Medicine, Hospital Universitario Virgen Macarena, Institute of Biomedicine of Seville (IBIS), Sevilla, Spain.
  • Johansson AF; Department of Clinical Microbiology and the Laboratory for Molecular Infection Medicine (MIMS), Umeå University, Umeå, Sweden.
  • Gastmeier P; Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Behnke M; Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • van Rooden SM; Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; Department of Epidemiology and Surveillance, Centre for Infectious Diseases Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
  • van Mourik MSM; Department of Medical Microbiology and Infection Prevention, University Medical Centre Utrecht, Utrecht, the Netherlands.
J Hosp Infect ; 122: 35-43, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1615639
ABSTRACT

BACKGROUND:

As most automated surveillance (AS) methods to detect healthcare-associated infections (HAIs) have been developed and implemented in research settings, information about the feasibility of large-scale implementation is scarce.

AIM:

To describe key aspects of the design of AS systems and implementation in European institutions and hospitals.

METHODS:

An online survey was distributed via e-mail in February/March 2019 among (i) PRAISE (Providing a Roadmap for Automated Infection Surveillance in Europe) network members; (ii) corresponding authors of peer-reviewed European publications on existing AS systems; and (iii) the mailing list of national infection prevention and control focal points of the European Centre for Disease Prevention and Control. Three AS systems from the survey were selected, based on quintessential features, for in-depth review focusing on implementation in practice.

FINDINGS:

Through the survey and the review of three selected AS systems, notable differences regarding the methods, algorithms, data sources, and targeted HAIs were identified. The majority of AS systems used a classification algorithm for semi-automated surveillance and targeted HAIs were mostly surgical site infections, urinary tract infections, sepsis, or other bloodstream infections. AS systems yielded a reduction of workload for hospital staff. Principal barriers of implementation were strict data security regulations as well as creating and maintaining an information technology infrastructure.

CONCLUSION:

AS in Europe is characterized by heterogeneity in methods and surveillance targets. To allow for comparisons and encourage homogenization, future publications on AS systems should provide detailed information on source data, methods, and the state of implementation.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Urinary Tract Infections / Cross Infection Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Humans Language: English Journal: J Hosp Infect Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Urinary Tract Infections / Cross Infection Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Humans Language: English Journal: J Hosp Infect Year: 2022 Document Type: Article