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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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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. |
format | Online Article Text |
id | pubmed-8613294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
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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