Getting Granular on Social Determinants of Health

Getting Granular on Social Determinants of Health


Social and environmental contexts are increasingly recognized as factors that impact health outcomes of patients. This team will have the opportunity to collaborate directly with clinicians and medical data in a real-world setting. They will examine the association between social determinants with risk prediction for hospital admissions, and to assess whether social determinants bias that risk in a systematic way. Applied methods will include machine learning, risk prediction, and assessment of bias. This Data+ project is sponsored by the Forge, Duke’s center for actionable data science.

Project Leads: Shelly RusincovitchRicardo HenaoAzalea Kim

Project Manager: Austin Talbot



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