Featured Module (Archived)
(Week of November 12, 2024)
A new educational offering from the Data section of the curriculum wheel has been posted (1-1.5 hours of primary open access content).
This website will be updated every Monday (by 12:00 PM Eastern) or Tuesday (if Monday is a holiday). Given that the design, implementation, and management of pragmatic trials is a non-linear process, featured modules will relate to various sections of the curriculum wheel over time.
Data Section
Use of routinely collected data in randomized trials: an introduction
Primary content:
Cadarette SM, Wong L. An Introduction to Health Care Administrative Data. Can J Hosp Pharm. 2015 May-Jun;68(3):232-7. (6-page paper)
Summary: Introduces administrative health data (i.e., data generated at every encounter with the health care system, whether through a visit to a physician’s office, a diagnostic procedure, an admission to hospital, or receipt of a prescription). Describes common sources of admin health data (e.g., the pan-Canadian Discharge Abstract Database) and follows through an example of research using administrative data. Briefly touches on the variability and timeliness of data access across Canada. (*Note that administrative health data are one type of routinely collected data, alongside clinical information from electronic health records, disease registries, and epidemiologic data from surveillance systems.)
Accelerating Randomized Trials (ART) Virtual Workshop (April 30, 2022), Schulich School of Medicine & Dentistry, Western University. Presentation #3 - Leveraging routinely collected health data for trials (Dr. Stephanie Dixon): 13-min webinar.
Summary: Dr. Stephanie Dixon introduces the use of routinely collected health data (i.e., electronic health records, administrative data, disease registries, and epidemiologic data from surveillance systems) for clinical trials. Uses of routinely collected data during the planning of the trial are discussed: 1. To understand current practice, 2. To assess availability and validity of outcomes, 3. To obtain estimates for improved power/sample size calculations, 4. To understand cluster composition and movement (if doing a cluster randomized trial). Overviews use of such data during the implementation and analysis stage of a trial. Lastly, introduces the RegisterNow-1* pragmatic trial. (*RegisterNow-1 will be posted as an exemplar trial later in the program.)
Mc Cord KA, et al. Routinely collected data for randomized trials: promises, barriers, and implications. Trials. 2018 Jan 11;19(1):29. (9-page paper)
Summary: Overviews benefits of using routinely collected data within trials: increasing value through better feasibility (reducing costs, time, and resources), expanding the research agenda (performing trials for research questions otherwise not amenable to trials), and offering novel design and data collection options (e.g., point-of-care trials and other designs directly embedded in routine care). Further, discusses potential regulatory, ethical, and data-related barriers, as well as the costs of setting up the routinely collected health data infrastructure*. (*Discussions of infrastructure for routinely collected health data, in Canada, will be the focus of future modules.)
Optional content:
NIH Pragmatic Trials Collaboratory (Living Textbook): Section 2 - Common Real-World Data Sources (Chapter: Data, Tools & Conduct - Acquiring Real-World Data): 1-page website.
Summary: Describes electronic health records (EHRs), administrative claims data, patient-reported outcomes data, patient-generated health data, medical product/device registries, condition-specific or disease registries, and datasets related to environmental factors and social determinants of health. Further, provides advice for identifying the appropriate source of “real-world” data for a trial. (As described in this resource, routinely collected data are sometimes referred to as “real-world” data, although this term is non-specific in nature.)