Clinical Analytics for Real-World Evidence (CARE) Platform

What is the CARE Project

The University of Waterloo in partnership with Hoffmann-La Roche Limited (Roche Canada) and the University Health Network (UHN) is developing the Clinical Analytics for Real-World Evidence (CARE) Platform to help produce data-driven insights in order to deliver the right care to the right patient at the right time through scientific innovation and research excellence.

Real World Evidence (RWE) in healthcare is data derived from numerous sources, measuring both objective and subjective outcomes from patients' home environment, clinical settings and workplace. These data are recorded and stored in different systems and formats, limiting our current ability to integrate, analyze and use the data to support treatment, as well as research decisions.

The CARE Platform is a holistic, cloud-based data analytics solution, featuring a large central repository, which consolidates data from disparate data systems (including data from electronic medical records, lab data, physician transcriptions, patient monitoring devices, and self-reported surveys). The CARE Platform will serve as a central hub for researchers and clinicians that includes integrated and sophisticated data analytics, access control, security, as well as study management tools to curate data for research and clinical purposes.

The current project is proposed as an initial proof-of-concept to address relevant research objectives in cancer research by providing the tools and infrastructure required to process and analyze the enormous amount of scattered oncology datasets within an institution. By making it possible for researchers and clinicians to mine currently slowed and/or unstructured data across the system to produce data-driven insights, the CARE Platform will help deliver the right care to the right patient at the right time through scientific innovation and research excellence.

Real world data

Vision

The CARE Project has a long-term vision of realizing the value of health data by transforming clinical practice and revolutionizing research by:

- improving the speed of clinical research (observational, interventional);

- assisting with clinical decision-making via readily available datasets in a common data model that allows for research analysis;

- utilizing real-world evidence and creating a critical mass of data that clinicians can pull from to make decisions on the patient who is directly in front of them; and

- creating a transferable prototype that can be used by other institutions either directly or conceptually for data discovery.