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An automated retrospective VAE-surveillance tool for future quality improvement studies.
Wolffers, Oliver; Faltys, Martin; Thomann, Janos; Jakob, Stephan M; Marschall, Jonas; Merz, Tobias M; Sommerstein, Rami.
Afiliação
  • Wolffers O; Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland. oliver.wolffers@insel.ch.
  • Faltys M; Department of Internal Medicine, Bern University Hospital, University of Bern, Bern, Switzerland. oliver.wolffers@insel.ch.
  • Thomann J; Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Jakob SM; Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Marschall J; Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Merz TM; Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Sommerstein R; Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.
Sci Rep ; 11(1): 22264, 2021 11 15.
Article em En | MEDLINE | ID: mdl-34782637
Ventilator-associated pneumonia (VAP) is a frequent complication of mechanical ventilation and is associated with substantial morbidity and mortality. Accurate diagnosis of VAP relies in part on subjective diagnostic criteria. Surveillance according to ventilator-associated event (VAE) criteria may allow quick and objective benchmarking. Our objective was to create an automated surveillance tool for VAE tiers I and II on a large data collection, evaluate its diagnostic accuracy and retrospectively determine the yearly baseline VAE incidence. We included all consecutive intensive care unit admissions of patients with mechanical ventilation at Bern University Hospital, a tertiary referral center, from January 2008 to July 2016. Data was automatically extracted from the patient data management system and automatically processed. We created and implemented an application able to automatically analyze respiratory and relevant medication data according to the Centers for Disease Control protocol for VAE-surveillance. In a subset of patients, we compared the accuracy of automated VAE surveillance according to CDC criteria to a gold standard (a composite of automated and manual evaluation with mediation for discrepancies) and evaluated the evolution of the baseline incidence. The study included 22'442 ventilated admissions with a total of 37'221 ventilator days. 592 ventilator-associated events (tier I) occurred; of these 194 (34%) were of potentially infectious origin (tier II). In our validation sample, automated surveillance had a sensitivity of 98% and specificity of 100% in detecting VAE compared to the gold standard. The yearly VAE incidence rate ranged from 10.1-22.1 per 1000 device days and trend showed a decrease in the yearly incidence rate ratio of 0.96 (95% CI, 0.93-1.00, p = 0.03). This study demonstrated that automated VAE detection is feasible, accurate and reliable and may be applied on a large, retrospective sample and provided insight into long-term institutional VAE incidences. The surveillance tool can be extended to other centres and provides VAE incidences for performing quality control and intervention studies.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade da Assistência à Saúde / Pneumonia Associada à Ventilação Mecânica / Melhoria de Qualidade Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Risk_factors_studies / Screening_studies Limite: Humans País como assunto: Europa Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade da Assistência à Saúde / Pneumonia Associada à Ventilação Mecânica / Melhoria de Qualidade Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Risk_factors_studies / Screening_studies Limite: Humans País como assunto: Europa Idioma: En Ano de publicação: 2021 Tipo de documento: Article