Interoperable Sharing of Healthcare Data Using Distributed Ledger Technologies
Brief Description of Project:
Patient identity matching is a process that locates a patient in a healthcare database using a unique set of personal information. Rare diseases are conditions that affect fewer than 200,000 people in the US, and due to the small patient populations, they receive significantly less scientific and commercial attention compared to more commonly studied medical conditions. As a result, highly motivated and active patient communities often form around rare diseases, creating and maintaining patient registries for patients to share data and knowledge about their conditions to promote disease discovery. However, many registries have been one-off solutions that identify patients in disparate ways, creating a major barrier to linking patients across multiple highly centralized registries. The main objective of this project is to address this need by developing an interoperable and efficient identity system using distributed ledger technologies to support necessary communications around rare diseases.
CS/CmpE/EE majors with strong interest in blockchain/distributed ledger technologies and concepts and knowledge of a programming language such as Java/Python. Experience with Git/GitHub, cloud technologies is a plus.
Nature of Supervision:
The undergraduate researcher will work closely with the PI and other undergraduate researchers. The intern will be given weekly tasks and report on them during the project meetings.
A Brief Research Plan (period is for 10 weeks):
Week 1: Background research and overview of software packages used
Week 2-4: Learning relevant tools and standards used in the project
Week 5-9: Development of a prototypical framework and a decentralized web/mobile app
Week10: Project report and poster presentation preparation. The researcher will also deliver an oral presentation on their research work.
Number of Open Slots: 1
Name: Dana Zhang
Department: Computer Science