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Thesis Defense: Data-Driven Methods for Health Equity

Speaker

Hammaad Adam

Host

Marzyeh Ghassemi

June 06 2025

10:00A - 2:00P

Location

TBD
E18-304

Title: Data-Driven Methods for Health Equity

Speaker: Hammaad Adam

Abstract: Significant research has established that data-driven methods can exacerbate existing inequity in healthcare. However, relatively little work has studied the potential of these methods to actively mitigate health disparities. In this thesis, I present a series of case studies that investigate how data-driven methods can be used to improve health equity. My work demonstrates this potential in two specific contexts: clinical trials and organ procurement. Clinical trials are an integral part of the health system, as they test the efficacy and safety of new medical treatments. However, past trials have perpetuated several inequities against racial minorities and other underserved groups. In the first half of this thesis, I propose two data-driven methods that target specific disparities in current practice. The second half of this thesis focuses on organ procurement, a key component in the current system of organ transplantation. Organ transplantation is a life-saving treatment for patients with advanced diseases, but there is a severe shortage of organs donated for transplant in the United States. Using a novel econometric model, I audit past OPO decisions, identify structural barriers that limit procurement, and evaluate policy changes that can improve efficiency and equity. I also describe the development of ORCHID, the first publicly-available, multi-center dataset on organ procurement. Collectively, this work can significantly increase the number of recovered organs, improving access to transplantation for thousands of patients in need.

Date: Friday, 6 June 2025
Time: 10AM
Room: E18-304
Zoom: https://mit.zoom.us/j/96951848838

Committee: Marzyeh Ghassemi, Nikhil Agarwal, Dean Eckles, Lester Mackey

Add to Calendar 2025-06-06 10:00:00 2025-06-06 14:00:00 America/New_York Thesis Defense: Data-Driven Methods for Health Equity Title: Data-Driven Methods for Health EquitySpeaker: Hammaad AdamAbstract: Significant research has established that data-driven methods can exacerbate existing inequity in healthcare. However, relatively little work has studied the potential of these methods to actively mitigate health disparities. In this thesis, I present a series of case studies that investigate how data-driven methods can be used to improve health equity. My work demonstrates this potential in two specific contexts: clinical trials and organ procurement. Clinical trials are an integral part of the health system, as they test the efficacy and safety of new medical treatments. However, past trials have perpetuated several inequities against racial minorities and other underserved groups. In the first half of this thesis, I propose two data-driven methods that target specific disparities in current practice. The second half of this thesis focuses on organ procurement, a key component in the current system of organ transplantation. Organ transplantation is a life-saving treatment for patients with advanced diseases, but there is a severe shortage of organs donated for transplant in the United States. Using a novel econometric model, I audit past OPO decisions, identify structural barriers that limit procurement, and evaluate policy changes that can improve efficiency and equity. I also describe the development of ORCHID, the first publicly-available, multi-center dataset on organ procurement. Collectively, this work can significantly increase the number of recovered organs, improving access to transplantation for thousands of patients in need.Date: Friday, 6 June 2025Time: 10AMRoom: E18-304Zoom: https://mit.zoom.us/j/96951848838Committee: Marzyeh Ghassemi, Nikhil Agarwal, Dean Eckles, Lester Mackey TBD

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