Using Big Data to Solve Big Problems – Leoson Hoay, MS, MA

How does big data help make large public health decisions? How do we set up the collection, the analysis, and interoperate the data to create infrastructure? Leoson Hoay serves as a Research Analyst and Data Steward at the University of Chicago Urban Labs, working with the Health Lab team to support the creation of data-driven solutions to public health problems. Prior to joining the Urban Labs, he had worked in various fields spanning data engineering, mental health counseling, and environmental remediation with organizations in the US, Singapore, and Australia. Leoson received his MA in Computational Social Science from the University of Chicago, and his undergraduate degree in Psychology from the National University of Singapore. He is currently pursuing an MS in Computer Science at the Georgia Institute of Technology.

In this episode we discuss many big questions invovling the use of big data to solve large problems. We dive into two projects Leoson has contributed to and generally discuss what big data means in the context of health decisions. Check it out!

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1. Tell us a little bit about what lead you to this path and what you do on a day to day basis?
2. What does preventive medicine mean to you?
3. How are large amounts of data able to be used to solve problems? What does the process look like? What are the challenges with this process?
4. You have done research into the homeless population cycling between the streets, hospitals, and jails. Can you tell us about this project?
5. Can you tell us a little bit more about your research with insurance backed psychiatric placement and providers?
6. How do you measure the impact of these projects?
7. What impact does the collection of data make on these projects and what changes were or could be made? How does data lead to infrastructure?
8. Do you think that community social services can help prevent problems from occurring or are they most active at solving acute problems?
9. Healthcare adds on a level of complexity for data collection with HIPPA and insurance companies. Are hospitals and insurance companies willing partners?
10. What are some of the protective measures to safeguard privacy when working with healthcare data?
11. If someone asks you how data contributes to health, what do you tell them?

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