ArticleJournal of perinatology : official journal of the California Perinatal Association2017
Network analysis: a novel method for mapping neonatal acute transport patterns in California.
Article in Journal of perinatology : official journal of the California Perinatal Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Differential transport patterns by race and ethnicity in very low birth weight infants.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- Examining perinatal regionalization in practice: a network analysis of maternal transport in Georgia.BMC health services research · 2025Article
- Application of Community Detection Methods to Identify Emergency General Surgery-Specific Regional Networks.JAMA network open · 2024Article
- Transfer Patterns Among Infants Born at 28 to 34 Weeks' Gestation.Pediatrics · 2024Observational
- A Conceptual Framework for Optimizing the Equity of Hospital-Based Emergency Care: The Structure of Hospital Transfer Networks.The Milbank quarterly · 2023Article
- Regionalization of neonatal care: benefits, barriers, and beyond.Journal of perinatology : official journal of the California Perinatal Association · 2022Review
- Prevalence and Predictors of Back-Transport Closer to Maternal Residence After Acute Neonatal Care in a Regional NICU.Maternal and child health journal · 2019Article
- A scoping review of patient-sharing network studies using administrative data.Translational behavioral medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
objectiveThe 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
designThis 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.
resultsEmpirical 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).
conclusionNetwork analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.