2 Introduction to Real-World Data (RWD) and Real-World Evidence (RWE)
2.1 Overview
This chapter introduces the foundational concepts of real-world data (RWD) and real-world evidence (RWE), including definitions, significance, key applications, and major sources. This sets the stage for understanding how RWD can be responsibly and effectively used in clinical and translational research.
2.2 What is Real-World Data (RWD)?
Real-world data refers to data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Common types include:
- Electronic Health Records (EHRs)
- Medical claims and billing data
- Product and disease registries
- Patient-generated data (e.g., through mobile devices or surveys)
- Data from digital health technologies
Each have their distinct advantages and drawbacks and must be carefully evaluated for their fit to answer the research question at hand.
2.3 What is Real-World Evidence (RWE)?
Real-world evidence is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD. It can support:
- Regulatory decision-making
- Clinical guideline development
- Health technology assessments
- Quality improvement
2.4 Why is RWD Important?
- Complements traditional clinical trials by reflecting broader and more diverse patient populations
- Offers insights into real-world effectiveness, safety, and utilization
- Enables learning health systems to continuously improve care
2.5 Applications of RWD and RWE
- Drug safety monitoring and post-market surveillance
- Comparative effectiveness research
- Observational studies to support hypothesis generation
- Pragmatic clinical trials
- Health equity research
2.6 Limitations and Considerations
- Data quality and completeness
- Potential biases and confounding
- Privacy and governance issues
- Varying data structures and lack of standardization