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      Quantifying the variation in neonatal transport referral patterns using network analysis

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          Abstract

          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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          Most cited references42

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          Modularity and community structure in networks

          M. Newman (2006)
          Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as "modularity" over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.
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            Efficient Behavior of Small-World Networks

            We introduce the concept of efficiency of a network as a measure of how efficiently it exchanges information. By using this simple measure, small-world networks are seen as systems that are both globally and locally efficient. This gives a clear physical meaning to the concept of "small world," and also a precise quantitative analysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.
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              A new status index derived from sociometric analysis

              Leo Katz (1953)
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                Author and article information

                Journal
                8501884
                5061
                J Perinatol
                J Perinatol
                Journal of perinatology : official journal of the California Perinatal Association
                0743-8346
                1476-5543
                12 May 2021
                December 2021
                25 May 2021
                13 January 2022
                : 41
                : 12
                : 2795-2803
                Affiliations
                [1 ]Division of Newborn Medicine, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
                [2 ]Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
                [3 ]Department of Pediatrics – Division of Neonatal and Developmental Medicine, Stanford University School of Medicine, Palo Alto, California, USA
                [4 ]California Perinatal Quality Care Collaborative, Palo Alto, California, USA
                [5 ]Department of Biomedical Informatics, Harvard University, Boston, Massachusetts, USA
                [6 ]Health Economics Resource Center, Veterans Affairs Palo Alto Healthcare Systm, Menlo Park, California, USA
                [7 ]Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
                Author notes
                Corresponding Author Sarah N. Kunz, MD MPH, Department of Neonatology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Rose 313, Boston, MA 02215, Tel: 617-667-3276, skunz@ 123456bidmc.harvard.edu

                Contributors’ Statement

                Dr. Kunz conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript.

                Drs. Zupancic and Profit conceptualized and designed the study, and reviewed and revised the manuscript.

                Drs. Zitnik and Rigdon and Mr. Helkey carried out the analyses, and reviewed and revised the manuscript.

                Dr. Phibbs conceptualized and designed the study, and critically reviewed the manuscript for important intellectual content.

                All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

                Article
                HHSPA1699398
                10.1038/s41372-021-01091-w
                8613294
                34035453
                9637ead1-fadc-4835-8593-602e8a70c068

                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

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                Pediatrics
                Pediatrics

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