Health Learning System with Real World Evidence

Although the gold standard for supportive clinical evidence has historically been randomized controlled trials, given their rigid and constrained nature, they rarely describe the effectiveness of an intervention or drug in real-life practice. Therefore, regulators, payers, healthcare providers, and institutions are turning towards real-world data collected at the interface of the patient and the health care system. However, there are 3 challenges to be addressed, including (1) lack of high-quality real-world data from health information systems or electronic medical records in Canadian hospitals; (2) lack of trust and collaborations amongst key stakeholders; and (3) lack of a future working model to facilitate the design and implementation of programs that address the major barriers for the generation of decision-grade real-world evidence in Canada. Therefore, this project aims to co-design solutions from the University of Waterloo’s intern and the partner organization to demonstrate a health learning system using Chimeric Antigen Receptor modified T cells treatment as a case study. Both the intern and the partner organization will benefit from this proposed project to learn strategies and technologies of a learning health system enabled by real-world data and evidence.

Faculty Supervisor:

Helen Chen

Student:

Partner:

Canadian Personalized Healthcare Innovation Network

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program: