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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01qr46r366g
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dc.contributor.advisorMassey, William-
dc.contributor.authorBridges, Connor-
dc.date.accessioned2019-08-16T13:15:19Z-
dc.date.available2019-08-16T13:15:19Z-
dc.date.created2019-04-15-
dc.date.issued2019-08-16-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01qr46r366g-
dc.description.abstractWhile infant mortality rates have stabilized in recent years, maternal mortality rates have been steadily increasing since the 1980s. Due to the difficultly of directly studying these mortality rates, this thesis focuses on three clinical outcomes that have been shown to be strongly correlated: cesarean sections, preterm births, and low birthweight births. A step-up approach was used to develop logistic regression models for these clinical outcomes and to determine the most significant patient demographics. K-means clustering was then used to determine which hospitals in the Sutter Health network have the most similar relationships between patient demographics and clinical outcomes. Race/ethnicity, payment type, and hospital location classification were all found to have consistently strong impacts on the risks of the clinical outcomes of interest. The cluster analysis revealed that outcomes worsen at hospitals further away from the center of mass of the Sutter Health hospital network.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleMaternal and Infant Health in the United States: An Investigation of Pregnancy Outcomesen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2019en_US
pu.departmentOperations Research and Financial Engineering*
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid961167495-
pu.certificateApplications of Computing Programen_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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