From Real-World Data to Real-World Evidence: why and how

Data-driven advancements are revolutionizing healthcare. However, using this data effectively remains a challenge, especially when transitioning from tightly controlled clinical trials to real-world applications. Real-world data (RWD) and real-world evidence (RWE) offer immense potential to address this gap, transforming how the pharma industry approaches research, development, and patient outcomes. This article explores the challenges, opportunities, and practical steps for leveraging RWE to bridge the gap while keeping patients at the heart of every decision.

Definitions and applications

What Are Real-World Data and Real-World Evidence?

To establish a foundation, it’s important to define the terms. Real-world data (RWD) refers to information about patient health and healthcare delivery collected outside of clinical trials. This includes electronic health records (EHRs), insurance claims, wearable devices, and patient-reported outcomes (PROs).
Real-world evidence (RWE), on the other hand, is the clinical analysis of this data. It generates actionable insights about safety, efficacy, and the value of treatments under real-world conditions.
RWE has the potential to answer questions clinical trials often leave unanswered. Yet, collecting, interpreting, and applying this data to its fullest remains complicated.

Critical Applications of RWE in Pharma

RWE is already making a profound impact across the pharma industry, addressing key priorities like:
• Regulatory and Label Expansion: Regulatory bodies increasingly accept RWE to support label expansions, particularly for rare diseases or underrepresented populations in clinical trials.
• Market Access and Reimbursement: RWE strengthens value propositions by demonstrating how treatments perform in the real world, helping pharma companies secure favourable reimbursement agreements.
• Personalized Medicine: Analysing diverse datasets enables pharma to identify treatment pathways tailored to specific patient subgroups, improving efficacy and adherence.
By addressing these practical needs, RWE proves itself as an essential tool for the pharmaceutical value chain, in a “pay for performance context”. However, utilizing it effectively demands bridging gaps between limited clinical trial data and the messy, nuanced realities of real-world healthcare.

The Challenges of Collecting RWD

Collecting RWD comes with several obstacles. Data is often scattered across fragmented systems, creating inconsistency in structure and quality. Privacy regulations enhance the protection and confidentiality of patient data, which sometimes makes them more complicated to share and use. Lastly, encouraging participation from patients and clinicians can be difficult, slowing down the process of data acquisition and integration.

These hurdles highlight the need for innovative tools and frameworks that not only simplify the data collection process but also ensure the data is meaningful and actionable. This is where tools like SPUR can provide invaluable support.

Closing the Clinical Delta

Clinical trials are the gold standard for evaluating treatments, offering controlled environments to assess efficacy and safety. However, they are not made to capture the unpredictability of real-world settings. This gap, which we call the “clinical delta,” affects the applicability of trial findings in everyday clinical practice. Closing this gap requires not only more data but smarter, more nuanced data collection.

Improving Clinical RWD Collection

To promote the acquisition of more accurate and actionable clinical RWD, the pharma industry can implement several strategies:
• Establish robust partnerships with healthcare providers, leveraging electronic health records (EHRs) to access comprehensive patient data (e.g partnering with integrated delivery networks (IDNs))
• Implement data standardization protocols across all collection points to ensure consistency and compatibility (e.g fast healthcare interoperability resources (FHIR)).
• Utilize advanced analytics and machine learning algorithms to derive insights from large datasets effectively (e.g natural language processing (NLP) tools, to extract insights from unstructured clinical notes).
• Encourage patient engagement through digital health platforms and wearables to gather continuous and real-time data (e.g patient-reported outcome (PRO) or symptom tracker)
• Adhere strictly to data privacy regulations and ethical guidelines, and explain how to maintain trust and compliance throughout the data collection process (e.g using GDPR- and HIPAA-compliant cloud platforms, describing the use of each collected data point).

Beyond Clinical Data

The key difference between a controlled clinical trial and real life is the influence of daily life factors — things like a patient’s environment, social support, personal constraints, and individual behaviors. In real-world settings, each patient experiences a unique and evolving context that goes far beyond the standardized conditions of a clinical trial. While this adds complexity, it doesn’t make it unmeasurable.

Behavioral science provides additional data, complementary to clinical metrics, by exploring factors such as adherence, motivation, and barriers to access. These insights extend beyond the clinical lens, offering a more complete and actionable view of patient experiences to fully understand health outcomes in real-life.

Introducing SPUR: Revolutionizing Behavioral Data Collection

To address this need, Observia’s behavioral diagnostic tool SPURTM now makes it possible to capture and quantify these real-life influences. By focusing on Social, Psychological, Usage, and Rational behaviors, SPUR dives into the causes behind patient actions, offering a holistic understanding of their choices and challenges outside the trial setting.

This multidimensional approach yields insights you can’t derive from clinical or demographic data alone and supports pharma companies in demonstrating real-world value, strengthening market positioning and payer negotiations.

Live the SPUR experience

The Business Value of Behavioral Data

SPUR is a dynamic and predictive digital-by-design questionnaire that enhances patient engagement with digital tools. With answers to a few questions, SPUR™ creates a holistic behavioral profile that describes patients’ health behaviors in any therapeutic area or cultural context. Personalized messaging strategies and adaptable patient portals built on SPUR’s insights not only improve data collection but also encourage healthier habits, further closing the clinical delta.

Conclusion

RWE is on the brink of transforming what’s possible in healthcare. It has the power to bridge the gap between the controlled realm of clinical trials and the complexities of real life. By using advanced data collection strategies, adopting patient-centric approaches and leveraging behavioral insights through tools like SPUR, the pharma industry is better positioned than ever to enrich lives and improve outcomes.

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