Accès ouvert déclaré 2024 article

A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread

Meghan A. Baker, Edward Joel Septimus, KEN P. KLEINMAN, Julia A. Moody, Kenneth Sands, Neha Varma, Amanda Isaacs, Laura E. McLean, Micaela H. Coady, E. Jackie Blanchard, Russell E. Poland, Deborah S. Yokoe, John M. Stelling, Katherine Haffenreffer, Adam Clark, Taliser R. Avery, Selsebil Sljivo, Robert A. Weinstein, Kimberly Smith, Brandon Carver, Brittany Meador, Michael Y. Lin, Sarah S. Lewis, Chamaine Washington, Megha Bhattarai, Lauren Shimelman, Martin Kulldorff, Sujan C Reddy, John A. Jernigan, Jonathan B. Perlin, Richard Platt, Susan S. Huang

4Citations signalées, ce qui n’est pas une note de qualité

12Institutions déclarées

1Pays d’affiliation déclarés

Rattachement africain : us. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

BACKGROUND: Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown. METHODS: We conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre-coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods. RESULTS: Real-time alerts did not significantly reduce the number of additional outbreak cases (intervention period versus baseline: statistical surveillance relative rate [RR]=1.41, control RR=1.81; difference-in-differences, 0.78; 95% confidence interval [CI], 0.40 to 1.52; P=0.46). Comparing only the prepandemic intervention with baseline periods, the statistical outbreak surveillance group was associated with a 64.1% reduction in additional cases (statistical surveillance RR=0.78, control RR=2.19; difference-in-differences, 0.36; 95% CI, 0.13 to 0.99). There was no similarly observed association between the pandemic versus baseline periods (statistical surveillance RR=1.56, control RR=1.66; difference-in-differences, 0.94; 95% CI, 0.46 to 1.92). CONCLUSIONS: Automated detection of hospital outbreaks using statistical surveillance did not reduce overall outbreak size in the context of an ongoing pandemic. (Funded by the Centers for Disease Control and Prevention; ClinicalTrials.gov number, NCT04053075. Support for HCA Healthcare's participation in the study was provided in kind by HCA.).

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref: A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread
Date Crossref: 23/04/2024
Éditeur: Massachusetts Medical Society
Type: journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

Brigham and Women's Hospital Department of Medicine pays non établi dans la notice
Établissement de santé
Harvard University pays non établi dans la notice
Université ou école supérieure
Harvard Pilgrim Health Care Department of Population Medicine pays non établi dans la notice
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Memorial Hermann Texas A&amp pays non établi dans la notice
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University of Massachusetts Amherst Department of Biostatistics and Epidemiology pays non établi dans la notice
Université ou école supérieure
HCA Healthcare pays non établi dans la notice
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University of California Department of Medicine pays non établi dans la notice
Université ou école supérieure
Rush University Medical Center pays non établi dans la notice
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Jr. Hospital of Cook County John H. Stroger pays non établi dans la notice
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Duke University Hospital pays non établi dans la notice
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Joint Commission pays non établi dans la notice
Organisation à but non lucratif
John Stroger Hospital of Cook County pays non établi dans la notice
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Department of Medicine — Brigham and Women's Hospital, Harvard University et Department of Population Medicine — Harvard Pilgrim Health Care, avec 9 autres affiliations.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Data-Driven Disease SurveillanceSepsis Diagnosis and TreatmentViral Infections and Outbreaks Research

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