CRII:SCH:RUI: A Digital Identity System for Accelerating Medical Communications within Rare Disease Communities

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 objective of this project is to address this need by developing an interoperable and efficient identity system to support necessary communications around rare diseases, while simultaneously providing interdisciplinary research experience to computer science undergraduate students.

This project will design, deploy, and evaluate a digital identity system driven by interoperability across data management systems. The goal of the proposed approach is to accelerate the patient identification process by creating unique representations of patient identities and a supporting platform that facilitate the management and exchanges of those identities to ensure interoperability.

The technical aims of the project are divided into three threads. The first thread creates a standardized digital identity model for rare diseases, which aims to uniquely represent patients without directly exposing sensitive, ambiguous patient identifying information to significantly reduce patient mismatching rate. The second thread develops a Rare Disease Identity System (RDIS) infrastructure, which will enable uniform and interoperable representations and transactions of patient identity to accelerate clinical communications.

The third thread focuses on integrated evaluation of RDIS with the use of the digital identity model created in the first thread. In particular, the overall effectiveness of the system will be evaluated based on the ease of identity collection and verification process, the scalability of the system in terms of the overall and average throughput of transacted synthetic patient profiles, and the average turnaround time it takes to identify a subset of patient profiles.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.