Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections

Abstract Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospita...

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Autores principales:	Juan Fernández-Gracia, Jukka-Pekka Onnela, Michael L. Barnett, Víctor M. Eguíluz, Nicholas A. Christakis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f626bb4a3ff541d18adc660f30d15cf8
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spelling	oai:doaj.org-article:f626bb4a3ff541d18adc660f30d15cf82021-12-02T15:18:54ZInfluence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections10.1038/s41598-017-02245-72045-2322https://doaj.org/article/f626bb4a3ff541d18adc660f30d15cf82017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-02245-7https://doaj.org/toc/2045-2322Abstract Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006–2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility’s C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting “sensor” hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as “sensors” could be a cost-effective mechanism to monitor emerging nosocomial infections.Juan Fernández-GraciaJukka-Pekka OnnelaMichael L. BarnettVíctor M. EguíluzNicholas A. ChristakisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Juan Fernández-Gracia Jukka-Pekka Onnela Michael L. Barnett Víctor M. Eguíluz Nicholas A. Christakis Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
description	Abstract Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006–2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility’s C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting “sensor” hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as “sensors” could be a cost-effective mechanism to monitor emerging nosocomial infections.
format	article
author	Juan Fernández-Gracia Jukka-Pekka Onnela Michael L. Barnett Víctor M. Eguíluz Nicholas A. Christakis
author_facet	Juan Fernández-Gracia Jukka-Pekka Onnela Michael L. Barnett Víctor M. Eguíluz Nicholas A. Christakis
author_sort	Juan Fernández-Gracia
title	Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
title_short	Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
title_full	Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
title_fullStr	Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
title_full_unstemmed	Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections
title_sort	influence of a patient transfer network of us inpatient facilities on the incidence of nosocomial infections
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/f626bb4a3ff541d18adc660f30d15cf8
work_keys_str_mv	AT juanfernandezgracia influenceofapatienttransfernetworkofusinpatientfacilitiesontheincidenceofnosocomialinfections AT jukkapekkaonnela influenceofapatienttransfernetworkofusinpatientfacilitiesontheincidenceofnosocomialinfections AT michaellbarnett influenceofapatienttransfernetworkofusinpatientfacilitiesontheincidenceofnosocomialinfections AT victormeguiluz influenceofapatienttransfernetworkofusinpatientfacilitiesontheincidenceofnosocomialinfections AT nicholasachristakis influenceofapatienttransfernetworkofusinpatientfacilitiesontheincidenceofnosocomialinfections
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Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections

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