Understanding the Ethical and Privacy Concerns with Suicide Risk Prediction Algorithms

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Student Researcher: Sarah Logan

Mentor: Dr. Michael Zimmer

Project Description

Suicide is currently one of the leading causes of death in the United States and suicide rates have continued to increase in recent years. Many suicide decedents have contact with the healthcare system in the month before their death, indicating that there is a significant opportunity to identify patients who are at risk for a suicide attempt when they visit their healthcare provider. Current algorithms for predicting suicide risk use data only from electronic health records. It is proposed that these algorithms could be improved through the incorporation of publicly available socioeconomic data, in addition to electronic health record data. We will be investigating the ethical implications of accessing and utilizing this socioeconomic data in the suicide risk prediction algorithms by measuring public opinion on the potential privacy threats of such efforts.

Project Milestones

  • Week 2: Conduct literature review
  • Week 3: Build survey
  • Week 4: Finalize survey questions and deploy survey
  • Week 6 or 7: Close survey and begin data analysis
  • Week 7 - Week 10: Data analysis, create poster, write research paper
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