Using Multi-Stage LASSO Methods to Predict Racial-Ethnic Disparity Reductions in Severe Maternal Morbidity in Maryland
Associate Name: Andreea Creanga
Funding Source/Period of the Grant: 1/1/2018-8/31/2018
Marked and persistent racial-ethnic disparities exist in maternal health in the United States – black women are 3-4 times more likely to die from pregnancy complications and 3 times more likely to experience severe, life-threatening maternal morbidity (SMM) than white women. Reasons behind these disparities are not fully understood, and in no other field of medicine than in obstetrics, do they play out so dramatically. The overarching goal of the proposed pilot study is to use of machine learning techniques to develop prediction-intervention models to assess potential reductions in racialethnic disparities in severe maternal morbidity in Maryland.