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.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.