Related Experiment Video
Updated: Mar 5, 2026
07:56
Transient Middle Cerebral Artery Occlusion Model of Neonatal Stroke in P10 Rats
Published on: April 21, 2017
11.1K
Network analysis: a novel method for mapping neonatal acute transport patterns in California
S N Kunz1,2, J A F Zupancic1,2, J Rigdon3
1Division of Newborn Medicine, Harvard Medical School, Boston, MA, USA.
Summary
Network analysis mapped neonatal transfers in California, revealing patterns that align with referral regions. Transfers outside these networks were linked to congenital anomalies, surgery needs, and insurance issues.
Area of Science:
- Healthcare systems analysis
- Medical informatics
- Network science
Background:
- Neonatal transfer patterns are complex and influence care quality.
- Understanding regional referral networks is crucial for efficient healthcare delivery.
- Previous analyses often lacked quantitative precision in mapping transfer dynamics.
Purpose of the Study:
- To apply network analysis to delineate neonatal transfer patterns in California.
- To compare empirically derived sub-networks with established state referral regions.
- To identify factors driving transfers outside of established sub-networks.
Main Methods:
- Cross-sectional database study of 6546 infants transported within California in 2012.
- Graph generation of 6696 acute hospital transfers.
- Community detection techniques to identify sub-networks and logistic regression for factor analysis.
Main Results:
- Empirically derived sub-networks showed significant overlap with regulatory regions (P<0.001).
- Transfers outside empirical sub-networks were associated with major congenital anomalies (P<0.001), need for surgery (P=0.01), and insurance reasons (P<0.001).
Conclusions:
- Network analysis provides an accurate, quantitative method for assessing neonatal transfer patterns.
- This approach can enhance the analysis of regionalized healthcare delivery systems.
- Findings highlight specific factors influencing out-of-network neonatal transfers.
