Automated surveillance systems for healthcare-associated infections: results from a European survey and experiences from real-life utilization.
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 i...
| Publicado en: | Journal of Hospital Infection Vol. 122; pp. 35 - 44 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
Apr2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=155905107&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155905107 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01956701 4C3 jtl: Journal of Hospital Infection issn: 01956701 maglogo: N pubinfo: dt: Apr2022 vid: 122 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 155905107 155905107 NLM35031393 155905107 10.1016/j.jhin.2021.12.021 NLM35031393 155905107 ppf: 35 ppct: 9 formats: tig: atl: Automated surveillance systems for healthcare-associated infections: results from a European survey and experiences from real-life utilization. aug: au: 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. affil: Department of Medical Microbiology and Infection Prevention, University Medical Centre Utrecht, Utrecht, the Netherlands sug: subj: Cross Infection Epidemiology Cross Infection Prevention and Control Urinary Tract Infections Prevention and Control Urinary Tract Infections Epidemiology Health Care Delivery Infection Control Methods Hospitals ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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