Real-World Evidence 1: Routinely collected data for clinical research
Routinely collected data (RCD) and data from cohorts are increasingly used in clinical research to generate real-world evidence (RWE) for health care decision-making. Traditionally used for non-randomized observational analyses, this data type is increasingly used to facilitate randomized clinical trials. This approach has been described as disruptive technology for clincial research. Indeed, merging the «magic of randomization» with the promises of routinely data offers solutions to many challenges, while it comes with novel challenges and emerging biases.
The course is designed as introduction to the concepts of RWE with non-randomized and randomized study designs. We will evaluate the promises, barriers, and implications of using these emerging resources for clinical research. You will learn about classic pitfalls and novel biases. You will get an overview of cutting-edge developments in the conception, design, conduct, analysis and reporting of RWE. You will be introduced to the concept of routinely collected data for randomized trials (RCD-RCTs) to support decision-making in the real world. The course is based on the most recent meta-research in the field to provide an evidence-based understanding of this emerging research approach.
The course aims to be highly interactive, intensive, and experiential. It targets those with an intention to conduct a randomized trial to inform medical decisions under real world conditions, soon or at some time in their future career.
This 2-week course requires students to:
- complete weekly assignments (three assignments; related to the specific topic of the week) and
- attend two 4-hour in-person sessions (interactive lectures, tutorials and discussion of assignment responses).
Wednesdays, 7.2. and 14.2.2024, 13.00 - 17.00h, raised ground floor, right, Spitalstr. 8, Basel.
Clinical researchers and PhD students enrolled at the University of Basel (Faculty of Medicine, Biomedical Engineering, Biomedical Ethics, Medicines Development, Nursing Science, Public Health/ Epidemiology or Sport Science) are eligible to register for the course. Please contact us if you are interested, but enrolled in another PhD programme. In general, all persons interested in these topics are welcome.
Minimum 8 and maximum 15 registered participants.
Prerequisites for attending
Intention to conduct clinical research to inform medical decisions under real world conditions soon or at some time in the future career.
Basic theoretical or practical knowledge of observational study designs and of randomized trial design is required, e.g., from an introductory course in epidemiology.
Upon successful completion of this course, the students will be able to
- Understand key concepts of using routinely collected data for clinical research
- Interpret study design decisions and their implications for real-world evidence
- Critically assess relevance of real world evidence for health-care decision making
- Identify clinical trial design options for using routinely collected data to provide randomized real-world evidence.
- 10 hours of workload distributed over 2 weeks
- Written response to all weekly assignments related to the course content
- Active participation in weekly discussions
- Attendance to all sessions is required
Note for PhD students: The workload of this course will be tranfered into ECTS credits automatically if the course is listed in your approved learning agreement.
PD Dr. med. Lars G Hemkens
PD Dr. med. Lars G Hemkens
Lead Pragmatic Trials and Real World Evidence at RC2NB
Senior Scientist Department of Clinical Research
Perrine Janiaud, PhD
Clinical Researcher at RC2NB
Research Fellow at the Department of Clinical Research
Cathrine Axfors, MD PhD
Pragmatic Evidence Lab RC2NB
Training and Education, Department of Clinical Research
The course is free of charge.
Course language is English
Certificates will be issued after successful course completion
This course is already fully booked. If you are interested to participate in the next course cycle, please register here.