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

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.