Real-world data (RWD) and real-world evidence (RWE) have become increasingly important in clinical research, with clinical trials both producing real-world data and utilizing it to inform and guide research or as the basis for conducting observational studies. In this article, we will discuss what real-world data and real-world evidence are, how they are related, and how they fit into the landscape of clinical research.

Real world evidence (RWE) and real world data (RWD)

Real world data (RWD) refers to patient data collected through the delivery of routine care in the real-world setting. RWD can come from multiple sources, including:

• Electronic health records (EHR)
• Case report forms (CRFs)
• Medical claims and billing data
• Public health reports and government databases
• Patient-generated data, from patient-reported outcomes (PRO/ePRO), mobile apps, surveys

Real world evidence (RWE) refers to the clinical insights and evidence generated from this patient data, and can include information about the usage, therapeutic efficacy, side effects, and risks of a medical product. New therapeutic indications for a given product could also be suggested based on this data.

What is the difference between RWD and RWE?

The difference between real-world data (RWD) and real-world evidence (RWE) is that RWD is the raw data, whereas RWE refers to the real evidence and clinical insights obtained from the analysis of the data. RWD can be collected from the various sources listed above, whereas RWE is obtained upon analyzing that data, providing practical interpretations that can be relevant for informing decision-making in healthcare and clinical research.

The importance of real world evidence (RWE) and real world data (RWD) in healthcare

RWD and RWE are important in healthcare because they represent comprehensive insights into how a medical intervention fares under real-world conditions, and often in a larger group of people that more accurately reflects the characteristics of the general population. This lies in contrast to data collected under the controlled conditions in clinical trials; although randomization, blinding, and other design techniques are intended to minimize or eliminate potential bias, the study population and environment may still not be entirely representative of real-world conditions.

RWD represents a rich data set that can include unforeseen variables that may not have been considered in initial studies, and covers a wider range of patient subtypes, ages, and co-morbidities that would be difficult if not impossible to capture or account for completely in clinical study design.

RWE provides observable health outcomes from real-life scenarios. This context enhances the understanding about which medical interventions have true therapeutic benefit for different patient populations, and provides additional insight into long-term side-effects and treatment adherence, allowing for more informed decision-making in clinical research and health policy. HEOR, meaning health economics and outcomes research, is one prominent practical application of the use of RWE in informing healthcare policy, research directions, and treatment decisions.

The relationship between real-world evidence (RWE) and clinical trials

Clinical research and RWE/RWD are synergistically intertwined in various ways. Let’s explore the connection.

How do clinical trials generate RWD?

Many clinical trial designs, such as RCTs, aim to include some degree of variability in the study population and then apply certain statistical assumptions to attempt to mimic real-world conditions. This includes several research techniques such as using a multi-center or decentralized study design to increase demographic variability, randomization, and blinding. Nonetheless, early-phase clinical trial (phase I, II, and III) data is typically too limited by the study’s sample size and inclusion criteria to be considered real-world data. However, phase IV clinical trials (observational or post-marketing surveillance studies) become a direct source of RWD as the intervention is being observed under real-world conditions. Thus, certain clinical trial designs can generate RWD, and if this data is analyzed within the context of the study, the trial can also be said to generate RWE.

How are RWE and RWD used in clinical research studies?

Likewise, RWD and RWE can be funneled back into clinical research and leveraged in various ways, as discussed below.

Inform clinical research study design and direction

RWD and RWE can be used to inform research questions/directions and trial design, and help researchers identify potential participants and define proper eligibility criteria.

Identifying new indications for approved drugs

RWE can provide researchers with information about potential off-label uses of approved drugs that were not investigated in initial clinical trials. Health outcomes and trends identified through RWD and RWE can thus indicate new potential therapeutic indications for existing drugs, which can then be tested intentionally in clinical trials.

Fulfill post-marketing and surveillance study requirements

Once a medical intervention is approved and made available in the market, RWD can be gathered. RWE obtained from this data can then provide insight into the treatment’s effectiveness and safety in the general population, and can be used to compare its efficacy against standard care options. In some cases (i.e., for a new indication for a previously approved drug), RWE may already be available and could be used to fulfill the requirements for post-marketing surveillance (phase IV) study data.

Supplement clinical trial data

RWD can supplement data from controlled clinical trials by providing data from a larger and more diverse population and under conditions with higher variability. This real-world information could help researchers identify potential side effects, adverse reactions, and contraindications that might not have been evidenced in the clinical study data.

What types of studies can generate RWE?

Types of real world evidence (RWE) studies

There are many types of clinical trial designs, but only certain clinical studies generate real world evidence: observational studies, large simple trials, and pragmatic trials.

Observational studies (prospective and retrospective)

Observational studies observe the effects of a medical intervention on patients without attempting to affect the outcome by controlling any aspect of its use. They are also known as non-interventional studies, and can be divided into two types – prospective and retrospective observational studies.

Prospective observational studies follow patients over time and collect data about their health conditions. They are conducted to study the long-term effects of a medical intervention. Retrospective studies look back on patient data and outcomes from the past, comparing subpopulations and analyzing the data to identify patterns and aspects such as potential risk factors and preventative factors for a given condition. Retrospective study types include case series and case reports.

Pragmatic trials

Pragmatic trials are designed to resemble real-life medical routines. They have relatively relaxed inclusion criteria, are commonly decentralized, and involve assumptions that allow for better generalizations of study findings. These trials include more varied participants and provide more appropriate context for real world analysis.

Large simple trials

Large simple trials (LSTs) enroll significantly more participants, generally studying only one or two aspects of a medical intervention. Primarily used in phase IV study designs, LSTs tend to focus on delivering care and recording patient outcomes.

Differences and similarities between real-world evidence (RWE) studies and clinical trials

While RWE studies and clinical trials are both conducted to study the safety and effectiveness of medical interventions, they differ in several ways.

Clinical trials are experimental, focusing on accuracy and reliability. Therefore they are conducted under relatively controlled conditions and on participants who meet specific eligibility criteria. While this often compromises generalization, the findings are comparatively less subject to error.

RWE studies, on the other hand, are more observational, taking data from real-life clinical practice as healthcare practitioners care for their patients. There are very few inclusion or exclusion criteria and usually no specified protocol to be followed. RWE studies are particularly useful for determining rare adverse effects in larger populations and high-risk groups. Furthermore, RWE studies:

• Are generally more cost-effective, take less time, and require fewer resources
• Use more accessible data that can be retrieved rapidly
• Have the capacity to evaluate the history of a medical intervention and its indications
• Can be applied more generally to guiding healthcare decisions and policy

Current challenges with real world evidence

The use of RWD in clinical research, and particularly the implementation of studies based entirely on RWE, are still in their infancy, and there is still progress to be made toward a defined and regulated approach. Specific considerations include standardization of RWE study designs, coherence of RWD sources, and the scientific reliability of evidence collected using RWD/RWE in the context of FDA regulations/guidelines.

Sponsors conducting RWE studies therefore face several challenges, such as:

• Consolidation of real-world data from multiple sources, each derived from different clinical practice contexts and reporting standards
• Interoperability issues across numerous healthcare database systems that may be used for data collection
• Managing the therapeutic uses of a specific medical intervention can be complicated for drugs that have multiple indications
• Lack of oversight and defined frameworks can lead to significant differences in findings between RWE studies and clinical trials

Conclusions

Real-world data (RWD) and real-world evidence (RWE) are valuable sources of insight from the intersection of clinical research and clinical practice. RWE studies represent an opportunity for gaining deeper and broader knowledge about medical interventions as they are used in the real world, and RWD can be a valuable supplement to primary clinical trial data. Further, observational, pragmatic, and large simple trials provide an avenue for comprehensive health outcome conclusions to be drawn with relatively lower resource requirements as compared to controlled trials. There are still obstacles to be overcome in the uses of RWD and RWE, particularly regarding standardization and regulation, but RWD and RWE are increasingly important sources of data used to inform and guide healthcare policy and clinical research.