Informatics in Medicine Unlocked (Jan 2022)
CRID - A unique, universal, patient-generated identifier to facilitate collaborative rare disease clinical research
Abstract
Background: Knowledge about rare diseases is often lacking due to the low prevalence of each disease. A challenge to increasing knowledge about rare diseases is the plethora of data silos being generated, which create barriers to information sharing, collaboration and coordination between researchers. The inability to share and reuse research data contributes to inefficient data collection, increased patient burden and possibly decelerates the path to better treatments. A unique, universal identifier would have the ability to link the same patient across research datasets and eliminate data silos. Methods: We present CRID (clinical research ID), a unique, universal, patient-generated identifier that can be used to facilitate collaborative rare disease clinical research. The identifier consists of 8 random alphanumeric characters, and can uniquely identify a patient. The CRID website [https://TheCRID.org] is available in multiple languages to support patients globally, and is installed on a secure, cloud-based server platform. All patient data are encrypted in-transit, at rest and within the application. We field-tested the CRID identifier across 6 rare disease research studies to demonstrate its ability to connect a patient across multiple research studies. Results: The CRID website allows a patient to create their unique identifier quickly and share it with researchers easily. Field tested across multiple disease research studies, this identifier has helped to reduce the burden on the patient by reusing their documents and transposing form data from the patient's original study into subsequent studies. Conclusion: A unique, universal, patient-generated identifier can be used to facilitate collaborative rare disease clinical research. With patients’ data connected using the CRID identifier and shared across study protocols, better insights can be gained into how a disease develops that is not possible with inaccessible data silos.
