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Quantifying the variation in neonatal transport referral patterns using network analysis

OBJECTIVE: Regionalized care reduces neonatal morbidity and mortality. This study evaluated the association of patient characteristics with quantitative differences in neonatal transport networks. STUDY DESIGN: We retrospectively analyzed prospectively-collected data for infants <28 days of age a...

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Autores principales: Kunz, Sarah N., Helkey, Daniel, Zitnik, Marinka, Phibbs, Ciaran S., Rigdon, Joseph, Zupancic, John A. F., Profit, Jochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613294/
https://www.ncbi.nlm.nih.gov/pubmed/34035453
http://dx.doi.org/10.1038/s41372-021-01091-w
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author Kunz, Sarah N.
Helkey, Daniel
Zitnik, Marinka
Phibbs, Ciaran S.
Rigdon, Joseph
Zupancic, John A. F.
Profit, Jochen
author_facet Kunz, Sarah N.
Helkey, Daniel
Zitnik, Marinka
Phibbs, Ciaran S.
Rigdon, Joseph
Zupancic, John A. F.
Profit, Jochen
author_sort Kunz, Sarah N.
collection PubMed
description OBJECTIVE: Regionalized care reduces neonatal morbidity and mortality. This study evaluated the association of patient characteristics with quantitative differences in neonatal transport networks. STUDY DESIGN: We retrospectively analyzed prospectively-collected data for infants <28 days of age acutely transported within California from 2008-2012. We generated graphs representing bidirectional transfers between hospitals, stratified by patient attribute, and compared standard network analysis metrics. RESULT: We analyzed 34 708 acute transfers, representing 1 594 unique transfer routes between 271 hospitals. Density, centralization, efficiency, and modularity differed significantly among networks drawn based on different infant attributes. Compared to term infants and to those transported for medical reasons, network metrics identify greater degrees of regionalization for preterm and surgical patients (more centralized and less dense, respectively [p<0.001]). CONCLUSION: Neonatal interhospital transport networks differ by patient attributes as reflected by differences in network metrics, suggesting that regionalization should be considered in the context of a multi-dimensional system.
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spelling pubmed-86132942022-01-13 Quantifying the variation in neonatal transport referral patterns using network analysis Kunz, Sarah N. Helkey, Daniel Zitnik, Marinka Phibbs, Ciaran S. Rigdon, Joseph Zupancic, John A. F. Profit, Jochen J Perinatol Article OBJECTIVE: Regionalized care reduces neonatal morbidity and mortality. This study evaluated the association of patient characteristics with quantitative differences in neonatal transport networks. STUDY DESIGN: We retrospectively analyzed prospectively-collected data for infants <28 days of age acutely transported within California from 2008-2012. We generated graphs representing bidirectional transfers between hospitals, stratified by patient attribute, and compared standard network analysis metrics. RESULT: We analyzed 34 708 acute transfers, representing 1 594 unique transfer routes between 271 hospitals. Density, centralization, efficiency, and modularity differed significantly among networks drawn based on different infant attributes. Compared to term infants and to those transported for medical reasons, network metrics identify greater degrees of regionalization for preterm and surgical patients (more centralized and less dense, respectively [p<0.001]). CONCLUSION: Neonatal interhospital transport networks differ by patient attributes as reflected by differences in network metrics, suggesting that regionalization should be considered in the context of a multi-dimensional system. 2021-12 2021-05-25 /pmc/articles/PMC8613294/ /pubmed/34035453 http://dx.doi.org/10.1038/s41372-021-01091-w Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Kunz, Sarah N.
Helkey, Daniel
Zitnik, Marinka
Phibbs, Ciaran S.
Rigdon, Joseph
Zupancic, John A. F.
Profit, Jochen
Quantifying the variation in neonatal transport referral patterns using network analysis
title Quantifying the variation in neonatal transport referral patterns using network analysis
title_full Quantifying the variation in neonatal transport referral patterns using network analysis
title_fullStr Quantifying the variation in neonatal transport referral patterns using network analysis
title_full_unstemmed Quantifying the variation in neonatal transport referral patterns using network analysis
title_short Quantifying the variation in neonatal transport referral patterns using network analysis
title_sort quantifying the variation in neonatal transport referral patterns using network analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613294/
https://www.ncbi.nlm.nih.gov/pubmed/34035453
http://dx.doi.org/10.1038/s41372-021-01091-w
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