Lesson series

Mastering Real-World Evidence

5 CME
The Real-World Evidence (RWE) Course is designed for academics, healthcare providers, and researchers, focusing on RWE's role in healthcare. It addresses the limitations of traditional clinical trials and highlights RWE's advantages. Key topics include data sources like electronic health records, designing robust RWE studies, managing biases and confounders, and practical aspects such as data cleaning and statistical methods.
The course also explores big data analytics, machine learning, AI, and real-world case studies. Precision public health, technological advancements, as well as ethical and privacy issues are discussed, concluding with RWE's future trajectory and the Target Trial Framework's relevance.

  • 40 videos

    Always up to date

  • 42 reading materials

    Free of charge
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      Aims

    • Understand the Basics of RWE: Introduce participants to the significance, historical context, and key concepts of RWE.
    • Evaluate Traditional Clinical Trials vs. RWE: Limitations of traditional RCTs and illustrate how RWE could provide additional insights in real-world settings.
    • Master RWE Study Design: The steps and considerations necessary for designing robust RWE studies, addressing biases, confounders, and ensuring data quality.
    • Leverage Big Data Analytics: The application of big data, machine learning, and AI in RWE, supported by real-world case studies
    • Future Trends: Discuss precision public health, technological advancements, ethical and legal considerations, and Target Trial Framework.

      Content

    • Overview of RWE's significance, historical context, and key concepts.
    • Fundamentals of RWE: significance, evolution, key definitions and epidemiological methods.
    • Traditional Clinical Trials vs. RWE: challenges of RCTs and comparison with RWE.
    • Designing and Conducting RWE Studies: mitigating biases and ensuring data quality.
    • Application of Big Data in RWE: methodologies and outcomes 
    • RWE in shaping public health policy and future trends:  technologies, and precision public health.
    • Advanced Topics and Future Directions: Causal inference techniques and effective communication of findings, Ethical challenges and privacy concerns 

      Methods

    The introduction to the topic takes place via online video lectures, literature reading, practical exercises and tests. In individual work, various steps in the desinging and application of RWE are carried out using concrete case studies. At the end of each section, a test is provided to assess your knowledge.

      Target audience

    Healthcare and public health professionals, as well as researchers with an interest in the topic.

    Meet our lecturer

    Mostafa Dianati, PhD

    In 2013, I successfully completed the BSc in Public Health, and then I started my MSc in Epidemiology at Shiraz University of Medical Sciences in Iran. After my Master, I started working as a faculty member and was responsible for study execution, teaching, and student supervision. After that, I moved to the Netherlands, where I did my PhD in epidemiology at Maastricht University.
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