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SCHOLAR Project

SCHOLAR PROJECT

In Collaboration with Sinai Urban Health Institute

SCHOLAR (Smart, Connected, and Healthy Outcomes from Leveraging Assets and Research) aims to enhance community health programs by integrating emerging technologies. Focused on under-resourced neighborhoods in Chicago, the project partners with Sinai Chicago to strengthen the connection between Community Health Workers (CHWs) and health systems.

The SCHOLAR project aims to design, develop, and evaluate a smart dashboard that will empower CHWs to interact with and interpret data leading to improved computational prediction modeling for Emergency Department (ED) readmission rates, improved health system risk stratification and resource allocation, and strengthening of the smart connection between the health system and the communities it serves.

This research is supported by the National Science Foundation (NSF) under grant number 2326676.

For more information on the project, contact the Principal Investigator (PI) Dr. Daniela Stan Raicu.

People

Faculty

Students

  • Navika Maglani, MS Data Science
  • Ankita Mishra, MS Data Science
  • Minh Nguyen, BS Data Science
  • Charmi Patel, PhD Computer Vision
  • Naveen Kumar Veeramreddy, MS Data Science

Publications

  • Hernandez N., Karam K., Baugh N., Musale S., Mosca A.P., Raicu DS., Frust JD., McCabe K., Tchoua R., ‘Leveraging Community Health Workers for Predicting Emergency Department Readmissions’. International Journal of Semantic Computing, 2024
  • Karam K., McCabe K., Tchoua R.,‘Leveraging Community Health Workers and Social Determinants of Health for Predicting Emergency Department Readmissions’. Fifth International Conference on Transdisciplinary AI (TransAI), 2023

Activities

  • Focus Groups

    • Focus Groups aim to gather detailed insights and feedback from CHWs on various aspects of patient engagement and readmission. This would help us understand what factors contribute to patient engagement, identify key data points for predicting readmission, and pinpoint which factors are essential for follow-up care.

  • Educational Workshops for CHWs

    • The workshops are designed to provide Community Health Workers (CHWs) with essential data science skills and knowledge. They cover topics like data integration, preprocessing, selection, modeling, and evaluation. Additionally, these sessions focus on fostering collaboration between CHWs and technology to refine predictive models and create connected, community-driven solutions.

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