Why Real-World Evidence Matters in Healthcare

Zhifei Zeng
6 days ago
7 min read

Introduction

In medical research and healthcare decision-making, randomized controlled trials (RCTs) have traditionally been regarded as the “gold standard.” However, RCTs often face limitations such as restricted sample populations, short follow-up periods, and high costs. These constraints limit the generalizability of their findings to real-world clinical settings.

Real-World Evidence (RWE) has emerged in response to these challenges. RWE is scientific evidence generated from real-world data (RWD), sourced from electronic health records, insurance claims databases, patient registries, wearable devices, and other sources. It reflects the actual treatment outcomes, safety, and adherence observed in patients' daily care, providing a crucial complement to the limitations of RCTs. In recent years, RWE has played an increasingly vital role in drug development, regulatory decision-making, payment policies, and clinical practice. Whether accelerating new drug approvals, supporting drug reevaluations, or advancing personalized medicine and value-based payment systems, RWE is becoming an indispensable component of healthcare systems.

Therefore, gaining a deep understanding of RWE's value and application prospects is not only crucial for healthcare professionals but also directly impacts patients' ability to access safe and effective treatment options faster and more equitably.

The Limitations of Traditional Clinical Trials and Advantages of RWE

Although RCTs are an indispensable part of drug approval, they also have limitations that cannot be ignored. First, the enrollment criteria for RCTs are typically strictly limited, with stringent exclusion conditions regarding factors such as age, comorbidities, and concomitant medications. This often means the study results may not fully reflect the circumstances of patients in real-world clinical settings. For instance, many RCTs exclude patients who are too elderly or have too many comorbidities, yet these very populations may actually use the drugs after market approval. Second, RCTs are lengthy, costly, and limited in sample size, making it difficult to fully reveal a drug's long-term safety and efficacy. Furthermore, many adverse reactions that may occur in actual clinical practice are often not adequately captured during the RCT phase.

In contrast, RWE offers a crucial means to supplement the limitations of RCTs. RWE is derived from real-world data (RWD), such as electronic health records (EHR), health insurance claims databases, patient registries, wearable devices, and social media. Consequently, it better reflects the actual efficacy and risks of drugs across diverse populations and usage scenarios. For instance, research utilizing social media data identified novel skin adverse reactions to an anticancer drug months earlier than traditional literature, providing crucial leads for pharmacovigilance.

The value of RWE extends beyond drug safety monitoring, directly influencing regulatory and clinical decision-making. In recent years, both the FDA and EMA have repeatedly incorporated RWE data into drug approvals and indication expansions. For instance, the breast cancer drug palbociclib was initially approved only for women, but based on real-world usage data from male patients, its indication was ultimately expanded to include men. Such cases demonstrate that RWE can accelerate drug approvals and label updates, shortening the time patients wait for new therapies.

Furthermore, in studies of rare diseases and conditions with small patient populations, RCTs often face challenges such as enrollment difficulties and complex control group design. In these scenarios, RWE can provide comparative information through synthetic control designs or the application of registry data, and may even serve as a critical reference for regulatory approval. For instance, in non-small cell lung cancer research, RWE supplemented evidence from single-arm clinical trials, ultimately aiding drug approvals in both the United States and Europe.

More importantly, RWE also aids in optimizing RCT design and implementation. By analyzing real-world data, researchers can identify unmet clinical needs, determine optimal enrollment criteria and study sites, thereby enhancing trial efficiency and feasibility. Particularly in rare disease research, RWD registries serve as vital patient recruitment resources, driving the development of “registry-based RCT” models.

In summary, while RCTs remain the cornerstone of clinical research, RWE has become an indispensable complementary force in modern healthcare systems. It not only addresses the limitations of RCTs but also provides more comprehensive, authentic, and dynamic evidence support for drug development, regulatory approval, reimbursement decisions, and clinical practice.

Why RWE is Important: Stakeholders Perspectives

Within the healthcare ecosystem, various stakeholders have distinct focuses and application scenarios regarding the value of RWE. With the continuous advancement of healthcare big data and analytical tools, RWE is emerging as a key driver for propelling drug development, optimizing healthcare services, and enhancing patient health outcomes.

Pharmaceutical and Medical Device Companies

In recent years, pharmaceutical and medical device companies have significantly increased their reliance on RWE. RWE is now widely applied throughout the entire product lifecycle management process—from early clinical trial design and refinement of clinical guidelines and disease understanding, to drug pricing, reimbursement, and regulatory approval. For instance, a 2020 RWE study demonstrated significantly higher patient adherence and persistence with dulaglutide injections compared to other similar drugs in type 2 diabetes treatment. Such findings help companies better understand drug performance in real-world clinical settings and provide robust support for their market strategies.

Healthcare Providers

Healthcare providers are also actively leveraging RWE to improve the quality of diagnosis and treatment. With the widespread adoption of EHRs, clinicians can conduct research based on vast real-world patient data to explore optimal treatment pathways. For instance, the UK's National Health Service introduced a value-based drug pricing model. A study grounded in RWE even facilitated an agreement between the NHS and pharmaceutical companies: if patients remain untreated for hepatitis C after 12 weeks of remdesivir therapy, related costs would be reimbursed. Additionally, advanced data analytics tools provide personalized decision support for both clinicians and patients. For instance, the Michigan Bariatric Surgery Consortium developed predictive tools to help patients select surgical approaches best suited to their individual characteristics.

Patients

In the digital era, patients have increasingly become key contributors to RWE generation and application. They proactively record and share health data through social media, health communities, and wearable devices, driving patient-led research and health management. In the UK, RWE collected from social media has been used for product promotion and approved by regulators, such as in the marketing of Infacol and Sudocrem. Furthermore, with the application of de-identification techniques and federated data networks, patients can securely share—and even monetize—their health data while preserving privacy and data ownership.

Payers

Payers increasingly rely on RWE to develop outcome-based payment models, enhancing healthcare affordability and equity. In the United States, insurers are contracting with physicians and healthcare providers based on treatment efficacy. In the UK, the National Institute for Health and Care Excellence uses real-world data in health technology assessments to inform treatment selection and reimbursement decisions. The UK's Systematic Anticancer Therapy database, established in 2011, collects nationwide chemotherapy data. It not only helps clinicians optimize treatment plans but also reveals significant trends and outcomes in disease management.

Regulator

Regulatory bodies also utilize RWE as a critical tool for assessing drug safety and efficacy. Beyond traditional pharmacovigilance methods like Periodic Safety Update Reports, the U.S. Food and Drug Administration established the Sentinel Initiative for real-time monitoring of post-marketing drug safety. Today, regulators not only demand higher-quality RWE but are also exploring how to integrate multi-source data into unified monitoring and decision-making systems. For example, the National Institutes of Health has established a joint fund aimed at strengthening practical research capacity building and promoting the utilization of integrated data from multiple channels in research design and clinical applications.

Future Directions

Despite the expanding application of RWE in healthcare and its growing acceptance among stakeholders, it still faces significant challenges, particularly stemming from the diversity and inconsistent quality of RWD sources. This makes data standardization, integration, and analysis central tasks for the future development of RWE.

Application of Artificial Intelligence and Data Analytics Technologies

In recent years, the rise of artificial intelligence (AI) technologies has brought new opportunities to address the complexity of RWD. Methods such as natural language processing, machine learning, and deep learning are being applied to unstructured data sources, including electronic health records, social media, and patient-generated data. For instance, studies have demonstrated that machine learning algorithms can successfully predict various clinical events and identify abnormal health parameters—such as heart rate variability and seizure risk—from wearable devices. These tools not only enhance data processing efficiency but also open new possibilities for disease prediction and personalized treatment. A particularly representative example is the Trial Pathfinder framework, which analyzed EHR data from over 60,000 non-small cell lung cancer patients. It revealed limitations in trial eligibility criteria, demonstrating that many patients who could potentially benefit from new therapies are excluded from traditional RCTs. Such technological advancements hold promise for driving more inclusive and universal clinical trial designs.

Accelerated Adoption Amid Public Health Emergencies

The COVID-19 pandemic further highlighted the value of RWE. Confronted with a global crisis, traditional drug development and approval processes proved excessively slow. The U.S. FDA launched initiatives leveraging RWE to support the rapid development and emergency use authorization of COVID-19-related drugs, vaccines, and diagnostic tools. This not only demonstrated RWE's immediate utility during public health emergencies but also provided critical lessons for addressing similar challenges in the future.

New Initiatives to Ensure Credibility

Despite RWE's expanding applications, concerns persist about potential biases in non-randomized studies when evaluating drug efficacy. To address this, the RCT DUPLICATE project was launched. This initiative enhances the reliability of RWD-based analyses by structurally designing RWE studies to replicate and validate results from RCTs. Such efforts suggest a future where RWE and RCTs may complement each other, jointly underpinning the advancement of evidence-based medicine.

Future Strategic Direction

Looking ahead, RWE will play an increasingly significant role in cross-system healthcare decision-making, with potential benefits spanning drug development, healthcare payment systems, and public health strategies. Achieving this requires pharmaceutical and medical device companies to further explore deep integration of RWE across R&D, medical affairs, commercialization, and Health Economics and Outcomes Research. Simultaneously, cross-regional data-sharing and risk-management mechanisms must be established to create high-quality, accessible, and comprehensive databases. Collaboration among researchers, regulators, and data scientists will also be crucial, leveraging rapid, low-cost technologies to enhance the generation and application quality of RWE. Through these initiatives, a culture of continuous innovation in RWE is expected to emerge, driving healthcare systems toward more efficient and patient-centered development.