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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.

Journal of Perinatology : Official Journal of the California Perinatal Association
|March 24, 2017
PubMed
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.

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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.