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The purpose of this project is to evaluate maternal and infant outcomes based on race at UVA hospital. Health inequities are influenced by a combination of Social, Political, and Clinical determinants of health. Our hypothesis is that patients with minority status, particularly Black and Hispanic Americans, are more likely to have poor outcomes (based on various health metrics) compared to Non-Black, Non-Hispanic patients. We hypothesize further that it is likely not far off from national trends, which indicate that Black parturients are x4 more likely to die during childbirth, and Black children are 2.4x more likely to die before their first birthday than Non-Hispanic White children.
The EPIC database will be used on an institutional basis to obtain information and accessed by UVA statistician to perform the research described in this submission. The dataset does contain a few direct identifiers of medical record numbers, dates, and postal number. We anticipate that all statistical analysis will be performed at UVA by participating faculty/staff.
Full description
The purpose of this project is to evaluate maternal and infant outcomes based on race at UVA hospital. Health inequities are influenced by a combination of Social, Political, and Clinical determinants of health. Our hypothesis is that patients with minority status, particularly Black and Hispanic Americans, are more likely to have poor outcomes (based on various health metrics) compared to Non-Black, Non-Hispanic patients. We hypothesize further that it is likely not far off from national trends, which indicate that Black parturients are x4 more likely to die during childbirth, and Black children are 2.4x more likely to die before their first birthday than Non-Hispanic White children.
The EPIC database will be used on an institutional basis to obtain information and accessed by UVA statistician to perform the research described in this submission. The dataset does contain a few direct identifiers of medical record numbers, dates, and postal number. We anticipate that all statistical analysis will be performed at UVA by participating faculty/staff.
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1,000 participants in 1 patient group
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Emily Chuang, MA; Keita Ikeda, PhD
Data sourced from clinicaltrials.gov
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