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dc.contributor.authorvan Mourik, Maaike S M
dc.contributor.authorPerencevich, Eli N
dc.contributor.authorGastmeier, Petra
dc.contributor.authorBonten, Marc J M
dc.date.accessioned2018-03-13T11:53:59Z
dc.date.available2018-03-13T11:53:59Z
dc.date.issued2018-03-05
dc.identifier.citationDesigning Surveillance of Healthcare-Associated Infections in the Era of Automation and Reporting Mandates. 2018, 66 (6):970-976 Clin. Infect. Dis.en
dc.identifier.issn1537-6591
dc.identifier.pmid29514241
dc.identifier.doi10.1093/cid/cix835
dc.identifier.urihttp://hdl.handle.net/10029/621599
dc.description.abstractSurveillance and feedback of infection rates to clinicians and other stakeholders is a cornerstone of healthcare-associated infection (HAI) prevention programs. In addition, HAIs are increasingly included in public reporting and payment mandates. Conventional manual surveillance methods are resource intensive and lack standardization. Developments in information technology have propelled a movement toward the use of standardized and semiautomated methods.When developing automated surveillance systems, several strategies can be chosen with regard to the degree of automation and standardization and the definitions used. Yet, the advantages of highly standardized surveillance may come at the price of decreased clinical relevance and limited preventability. The choice among (automated) surveillance approaches, therefore, should be guided by the intended aim and scale of surveillance (eg, research, in-hospital quality improvement, national surveillance, or pay-for-performance mandates), as this choice dictates subsequent methods, important performance characteristics, and suitability of the data generated for the different applications.
dc.language.isoenen
dc.rightsinfo:eu-repo/semantics/closedAccessen
dc.titleDesigning Surveillance of Healthcare-Associated Infections in the Era of Automation and Reporting Mandates.en
dc.typeArticleen
dc.identifier.journalClin Infect Dis 2018; 66(6):970-6en
html.description.abstractSurveillance and feedback of infection rates to clinicians and other stakeholders is a cornerstone of healthcare-associated infection (HAI) prevention programs. In addition, HAIs are increasingly included in public reporting and payment mandates. Conventional manual surveillance methods are resource intensive and lack standardization. Developments in information technology have propelled a movement toward the use of standardized and semiautomated methods.When developing automated surveillance systems, several strategies can be chosen with regard to the degree of automation and standardization and the definitions used. Yet, the advantages of highly standardized surveillance may come at the price of decreased clinical relevance and limited preventability. The choice among (automated) surveillance approaches, therefore, should be guided by the intended aim and scale of surveillance (eg, research, in-hospital quality improvement, national surveillance, or pay-for-performance mandates), as this choice dictates subsequent methods, important performance characteristics, and suitability of the data generated for the different applications.


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