Beyond the binary: integrating “real-world evidence” with randomized trials in contemporary health care

Key findings We suggest developing an integrated framework combining randomized controlled trials (RCTs) and real-world evidence (RWE), emphasizing their complementary strengths in health-care research. Currently, this integration is often ad hoc, not systematically planned or embedded within existing methodological or regulatory frameworks. We outline specific strategies focusing on prospective planning, methodological transparency (such as preregistration of RWE observational studies), and robust governance frameworks to systematically integrate these complementary evidence types. What this adds to what is known? This paper promotes evolving beyond traditional binary perspectives on evidence types (RCT vs RWE), clarifying how innovative hybrid designs, adaptive randomized trials, and pragmatic RCTs can systematically integrate RWE to enhance generalizability without sacrificing methodological rigor. We suggest approaches for integrating RWE and randomized trials (eg, external control arms, pragmatic RCTs), addressing existing knowledge gaps and reducing redundancy or fragmented integration practices. What is the implication, what should change now? Stakeholders across the health-care research ecosystem, including regulatory bodies, industry, academia, and patient communities, should adopt harmonized methodological standards and robust governance frameworks for integrating randomized trials with RWE data. Most importantly, prospective planning of integrated randomized trial and RWE approaches—rather than retrospective data assembly—must become standard practice in health-care research. Immediate priorities include developing comprehensive frameworks and prospective protocols for systematic integration, enhancing methodological transparency, and ensuring robust data governance, alongside systematic evaluation of stakeholder engagement to ensure research relevance and applicability. In addition, there must be concerted efforts to develop better methodological approaches for synthesizing different data types across diverse study designs, enabling more reliable integration of evidence from heterogeneous sources.