NCSI: Mixed Methods Analysis of Maternal Morbidity and Mortality

Status	Completed
Mentor Name	Kelly Gaither
Mentor's XSEDE Affiliation	co-PI and L2 Area lead of CEE
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Mixed Methods Analysis of Maternal Morbidity and Mortality
Summary	The U.S. has one of the highest rates of maternal mortality and morbidity. There is a significant disparity in maternal outcomes for women of color, particularly for Black and African American women and Indigenous Alaskan Native women. Traditional data collection is limited to clinical encounters and labor/delivery. This data, however, does not provide a sufficient view into factors that may contribute to adverse outcomes in maternal health. This project will use machine learning and advanced computational analytics to examine 10 years of birth and death data in the U.S. provided through the public repository curated by the National Vital Statistics System. Additionally, interviews, news articles and obituary data collected through ProPublica's "Lost Mothers" project will be used to integrate with traditional electronic health records data to examine the value of information collected from this mixed methods analysis.
Job Description	The student will work alongside me and will develop a set of methods/algorithms to do both supervised and unsupervised learning from 10 years of birth and death data provided by NVSS. The student will work in R and Python to have access to the latest in both machine learning and statistical methods for high-dimensional data. The student will also work with me to develop a publication from the work that will be submitted to a journal in maternal fetal medicine. Dr. Radek Bukowski, a practicing maternal fetal medicine physician will also participate and provide oversight on the medical aspects of the project.
Computational Resources	We will use both Stampede2 and Frontera for all computations using both the Vis portals and Jupyter Notebooks. All computations will be done in R and Python. We will also use dashboarding to
Contribution to Community	The outcomes of this work will provide valuable contributions to the state of the art in maternal health.
Position Type	Intern
Training Plan	The student will be gaining hands-on experience in all aspects of the project and will work directly with me in the research.
Student Prerequisites/Conditions/Qualifications	Computational experience in maternal health data and computational skills in R/RStudio, Python, and modern washboarding technologies.
Duration	Semester
Start Date	01/15/2022
End Date	05/01/2022