Kunz S N, Zupancic J A F, Rigdon J, Phibbs C S, Lee H C, Gould J B, Leskovec J, Profit J
Division of Newborn Medicine, Harvard Medical School, Boston, MA, USA.
Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
J Perinatol. 2017 Jun;37(6):702-708. doi: 10.1038/jp.2017.20. Epub 2017 Mar 23.
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.
本研究的目的是使用网络分析来描述加利福尼亚州新生儿转运模式，将实证子网与既定转诊区域进行比较，并确定与原发子网之外转运相关的因素。
这项横断面数据库研究纳入了2012年在加利福尼亚州境内转运的6546名28日龄以下婴儿。在生成一个表示医院之间急性转运的图表（n = 6696）后，我们使用社区检测技术来识别联系更紧密的子网。将这些通过实证得出的子网与州定义的区域转诊网络进行比较。使用逻辑回归评估实证子网之间转运的原因。
实证子网与监管区域显示出显著重叠（P < 0.001）。实证子网之外的转运与重大先天性异常（P < 0.001）、手术需求（P = 0.01）以及作为转运原因的保险情况（P < 0.001）相关。
网络分析准确反映了实证新生儿转运模式，可能有助于对区域化医疗服务提供系统进行定量而非定性分析。
