Getting Real About Real-World Data

The terms “Real-World Data” (RWD) and “Real-World Evidence” (RWE) are often thrown around in the life science industry, but what do they really mean? For our latest vlog, we spoke with Bill Saunders, PhD, MPH, from Integra Connect to learn about RWD and RWE in the context of value-based care and precision medicine for specialty care.

As an HEOR Expert, what do RWD and RWE mean to you?

Real-World Data are collected outside of a traditional clinical trial setting from sources such as electronic medical records (EMRs), payer claims, electronic patient-reported outcomes, imaging scans, and disease registries. Real-World Evidence refers to the analysis of RWD to gain valuable insights into a drug’s usage, benefits, and risk factors. While those sources are a start, we need to realize that very few databases bring together clinical and claims data to create complete, longitudinal patient journeys, which we will discuss later.

Having the right kind of data is critical. Companies may look at claims data, for example, but that is just one part of the story. To truly understand the drug, you must first put the patient at the center. Therefore, you need the most complete dataset so that you can get a complete picture of the patient, uncover their longitudinal journeys, and gain deeper insights to produce better treatment pathways. Additionally, organizations need to make sure that they aren’t just tapping into one source of data (e.g., one set of EMR data), but multiple sources so that they get a truly representative view of how people respond to the deck.

 

In your opinion, what has been the impact of RWD and RWE thus far?

For life science companies, RWD can complement and expand on data that are gathered in clinical trials. Though clinical trials are still considered to be the gold standard, RWD can be incorporated across every stage in a drug’s lifecycle and can offer a broader scope than clinical trials alone. Additionally, RWD reflects actual usage in everyday care settings, as well as real-world patient experience. Market access, research, and commercial teams can use RWD to inform clinical trial design, off-label usage, safety signals, treatment switching, costs, and more.

 

That’s interesting. What about across a drug’s entire life cycle?

Data should not stem solely from the drug’s efficacy; life science companies should be tapping into RWD to get a comprehensive view throughout the drug’s life cycle. From research and development (R&D) to commercialization and post-surveillance, RWD can help pinpoint gaps in care to build a highly effective, evidence-based commercial strategy, drive decisions on market feasibility, and refine patient sub-populations. In terms of post-market activities, RWD allows for the study of safety and efficacy in real-world settings, and also provides insights into drug adherence. These examples are true for any disease area, but especially in oncology, where disease heterogeneity necessitates precision or personalized medicine.

 

 

 

 

There are five characteristics you should consider when evaluating the right kind of RWD:

1. Multiple sources: Layering different datasets (e.g., claims data, EMRs, prescription data, patient registries) can enable the insights needed to understand how a treatment is performing in the real world.

2. Structured and unstructured: While clinical data includes structured data contained in EMRs, there are significant, rich clinical data that live in unstructured narratives. Having a complete picture requires taking structured and unstructured data and applying natural language processing to further uncover longitudinal journeys. Once a critical mass of data points is accumulated, the data can begin to be predictive, which becomes more insightful for users.

3. Integrated: Simultaneously, the ability to see data aggregated and in detail is needed to surface powerful insights. We need to take all the data from different datasets to get a unified, complete view of what is truly happening.

4. Accessible: Many times, data is trapped in silos. It’s important to ensure that data are available and usable across stakeholders.

5. Complete: We are only as good as our data. The more complete the data are, the better we can understand what is happening to patients on an individual and cohort level.

 

What do we need to do to shift the conversation from the price of the drug to the overall cost of care?

Since healthcare stakeholders are increasingly emphasizing value-based care, especially in oncology, you need to have that in mind when evaluating data sources. For value-based care, most companies tap into claims data, but you also need to compile clinical data so that it is actionable when it goes to oncology providers. You need differentiated data to get differentiated insights. You also need data from providers at the point of care to help deliver the right drug to the right patient at the right time, dose, and price. To view the complete benefits of the drug and its potential, you need to partner with a leading RWD expert who can optimize the entire R&D process from start to finish. If you are specializing in oncology, you would need a leading expert in oncology.

For success in specialties such as oncology drug development, the ideal RWD/RWE partner should be a domain expert with strong links to community practices, an in-depth understanding of how to customize a platform to the drug’s lifecycle, and the ability to identify unmet needs in underrepresented patient populations.

 

What makes you excited for RWD in the next year?

We are now starting to merge rich clinical data with input from experienced oncologists to make real-time changes in treatment pathways and improve patient outcomes. That’s what makes me excited. When I started in this business, this was a dream… Now it is our reality!

Click here to learn more about how Integra Connect solutions can accelerate the adoption of value-based, precision medicine efforts across the care continuum.