Network analysis: a novel method for mapping neonatal acute transport patterns in California.
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.



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.



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).



Network analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems.
Division of Newborn Medicine, Harvard Medical School, Boston, MA, USA.|Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
S N
SN
Kunz
Division of Newborn Medicine, Harvard Medical School, Boston, MA, USA.|Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
J A F
JAF
Zupancic
Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.
J
J
Rigdon
Department of Pediatrics-Neonatal and Developmental Medicine, Stanford University School of Medicine, Stanford, CA, USA.|Health Economics Resource Center, Veterans Affairs Palo Alto Healthcare System, Menlo Park, CA, USA.
C S
CS
Phibbs
Department of Pediatrics-Neonatal and Developmental Medicine, Stanford University School of Medicine, Stanford, CA, USA.|California Perinatal Quality Care Collaborative, Stanford, CA, USA.
H C
HC
Lee
Department of Pediatrics-Neonatal and Developmental Medicine, Stanford University School of Medicine, Stanford, CA, USA.|California Perinatal Quality Care Collaborative, Stanford, CA, USA.
J B
JB
Gould
Department of Computer Science, Stanford University, Stanford, CA, USA.
J
J
Leskovec
Department of Pediatrics-Neonatal and Developmental Medicine, Stanford University School of Medicine, Stanford, CA, USA.|California Perinatal Quality Care Collaborative, Stanford, CA, USA.
J
J
Profit
D002140:California; D003430:Cross-Sectional Studies; D006801:Humans; D007231:Infant, Newborn; D007363:Intensive Care Units, Neonatal / Q000706:statistics & numerical data*; D016015:Logistic Models; D015233:Models, Statistical; D010360:Patient Transfer / Q000379:methods* / Q000592:standards