Big Data for Reproductive Health (2019-2020)

This Bass Connections project improved access to family planning by providing stakeholders with necessary data to inform their advocacy and policymaking efforts.

The 2019-2020 project team built on the work produced by the 2018-2019 Bass Connections team and the 2018 and 2019 Data+ summer projects. During the 2019-2020 academic year, the particular focus of the project was to examine the feasibility of implementing a precision medicine family planning counseling tool to support healthcare workers in low-income settings around the world.

The stakeholder engagement sub-team assessed the digital family planning landscape and interviewed relevant stakeholders to determine how our team could proceed ethically in this research space. Meanwhile, the machine learning sub-team reviewed and tested big data algorithms for their predictive tool to minimize data quality issues and maximize data accessibility.

They discovered from stakeholder feedback their tool suite’s niche as educational apps predominantly suited for decision makers who want to understand what contraceptive data is and what contraceptive discontinuation and switching look like in a dynamic format. Additionally, they learned the costs and benefits of different big data algorithms, including neural networks, decision trees, support vector machines and K-nearest neighbors, in modeling such data.


Fall 2019 – Spring 2020

Team Outputs

Developing Tools for Contraceptive Data Tracking (Fortin Foundation Bass Connections Virtual Showcase 2020)

This Team in the News

Finding Solutions Together

Team Mines Big Data to Uncover Trends in Contraceptive Use

Faculty Perspectives: Megan Huchko

Our Favorite Global Health Stories from 2019

Study Explores How to Get More Men Involved in Their Pregnant Partners’ Healthcare

Graduate and Professional Student Spotlight: Reflections from the Class of 2023

See related teams, Big Data for Reproductive Health (2020-2021) and Big Data for Reproductive Health (2018-2019), and related Data+ summer project, Big Data for Reproductive Health (2019).

Big Data logo.

Team Leaders

  • Amy Finnegan, IntraHealth International
  • Megan Huchko, School of Medicine-Obstetrics and Gynecology

/graduate Team Members

  • Stephanie Skove, Medicine MD Fourth Year
  • Kelly Hunter, Public Policy Studies-PHD

/undergraduate Team Members

  • Anna Hirsch, Computer Science (BS)
  • Qintian Zhang, Statistical Science (BS)
  • Zhixue Wang, Computer Science (BS)
  • Eugene Wang, Computer Science (BS)
  • Elizabeth Shulman, Interdepartmental Major
  • Saumya Sao, Gender Sexuality & Fem St(AB)
  • Janel Ramkalawan, English (AB)
  • Dennis Harrsch Jr., Computer Science (BS)

/yfaculty/staff Team Members

  • Amy Herring, Arts & Sciences-Statistical Science

/zcommunity Team Members

  • RTI International
  • Ipas
  • MEASURE Evaluation
  • FHI 360
  • UNC-Chapel Hill, Carolina Population Center
  • IntraHealth International