Title | Network analysis: a novel method for mapping neonatal acute transport patterns in California. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Kunz SN, Zupancic JAF, Rigdon J, Phibbs CS, Lee HC, Gould JB, Leskovec J, Profit J |
Journal | J Perinatol |
Volume | 37 |
Issue | 6 |
Pagination | 702-708 |
Date Published | 2017 06 |
ISSN | 1476-5543 |
Keywords | California, Cross-Sectional Studies, Humans, Infant, Newborn, Intensive Care Units, Neonatal, Logistic Models, Models, Statistical, Patient Transfer |
Abstract | OBJECTIVE: The objectives of this study are to use network analysis to describe the pattern of neonatal transfers in California, to compare empirical sub-networks with established referral regions and to determine factors associated with transport outside the originating sub-network. STUDY DESIGN: This cross-sectional database study included 6546 infants <28 days old transported within California in 2012. After generating a graph representing acute transfers between hospitals (n=6696), we used community detection techniques to identify more tightly connected sub-networks. These empirically derived sub-networks were compared with state-defined regional referral networks. Reasons for transfer between empirical sub-networks were assessed using logistic regression. RESULTS: Empirical sub-networks showed significant overlap with regulatory regions (P<0.001). Transfer outside the empirical sub-network was associated with major congenital anomalies (P<0.001), need for surgery (P=0.01) and insurance as the reason for transfer (P<0.001). CONCLUSION: Network analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems. |
DOI | 10.1038/jp.2017.20 |
Alternate Journal | J Perinatol |
PubMed ID | 28333155 |
PubMed Central ID | PMC5446293 |
Grant List | R01 HD083368 / HD / NICHD NIH HHS / United States T32 HD075727 / HD / NICHD NIH HHS / United States U54 EB020405 / EB / NIBIB NIH HHS / United States |