Discovering health disparities: Designing a secure multiparty architecture for social health research

Discovering health disparities: Designing a secure multiparty architecture for social health research

Kolar, Brontë (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems)

Erkin, Z. (mentor)
Urbano, Julián (graduation committee)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2021-07-02

Social determinants such as a person’s race, level of education, and income can be responsible for their health outcomes. Consequently, we see that discrimination along the social spectrum results in health disparities. In an effort to close the gaps in healthcare systems, these determinants have been heavily researched. Open questions remain regarding their underlying mechanisms, which can potentially be answered by combining government data from social sectors with healthcare data. Under modern data legislation, such as the General Data Protection Regulation in the European Union, it is challenging to combine these government datasets for such research purposes. Multiparty computation (MPC), a cryptographic technique that allows for two or more parties to securely compute a function over data, opens the door for siloed government datasets to be combined and analyzed in a manner compliant with data legislation. This paper presents survey data from experts that supports the feasibility of using MPC to securely investigate the social determinants of health, as well as a potential architecture based on additive secret sharing that could be utilized by governments to investigate these determinants. This is the first formal research into this application of MPC and it aims to evaluate how new developments in cryptography can be leveraged to advance health equity and bring justice to those systemically discriminated against.

Multi-Party Computation
Healthcare
MPC architectures

http://resolver.tudelft.nl/uuid:d22b37ca-983d-47e1-bad9-b02dae2107cd

Student theses

bachelor thesis

© 2021 Brontë Kolar