Integrated real-world data: The key to accelerating innovation

Real-world data (RWD) have made a splash in the life sciences industry, accelerating learning and driving impact for patients. And meaningful incorporation of these data in decision-making has become table stakes for the development and commercialization of products. But the expansion of RWD use comes with growing expectations for high-quality, reliable data from a variety of stakeholders — namely providers, payers and regulators. 

However, not all types of RWD are created equal. Claims data, for instance, are a tried-and-true data source to understand and connect costs and utilization. But alone, they only hold so much power. They’re missing the clinical context found in electronic health record (EHR) data, such as lab values, provider notes and patient lifestyle factors. 

To truly leverage the power of evidence-generation and effectively move the needle on patient outcomes, you need integrated data (linked EHR and claims) to see the bigger picture of the patient care experience, the dynamics of your therapeutic market(s) and the impact or potential impact of your product(s). 

Think of using claims data alone as seeing only in black and white. There are still some black-and-white cinematic masterpieces out there, and black-and-white photos certainly have character. But seeing movies and photos in color has become popular for a reason. What’s in front of you becomes richer and clearer. You get an enhanced picture. 

It’s a similar dynamic when you move from analyzing claims data to integrated data. You start to see the deeper, richer, more “colorful” nuances of the patient journey that you may have missed when the picture was only in black and white. You glean market insights data that wouldn't be apparent without combining cost, clinical outcomes, adherence data and healthcare utilization information. 

Layering additional clinical detail onto claims data through compliant and secure data linkage will help your analyses capture a more holistic view of the patient experience. And with this expanded view comes the potential to identify more of your target population and achieve more of your business and research goals. 

To illustrate just how enhanced the picture can be with integrated data, consider the following real-world example* from Optum Life Sciences researchers. 

Optum researchers conducted a study to investigate the early symptoms that precede the onset of multiple sclerosis (MS), a chronic neurological condition, to determine their predictive value in identifying individuals at high risk for the disease. 

The literature review showed studies which used information from de-identified clinical notes to improve prediction models. To demonstrate the added insight gained from layering claims with clinical data, the researchers conducted their analyses twice, using 2 different RWD sources. First, they used claims data alone, then second, used claims data linked with notes derived from EHRs. 

Researchers employed a machine learning (ML) approach to predict incidence of MS based on: 

1. Claims data (documented MS diagnosis) 
2. Combined claims data (documented MS diagnosis) and signs and symptomology (SDS) derived from EHR notes 

The study findings suggest that symptoms could appear long before the diagnosis of the disease. The addition of EHR data improved the odds ratio of each predictor variable. Overall, analyzing SDS data along with claims significantly improved the accuracy of risk prediction. 

The benefits of utilizing SDS terms from EHR systems in addition to claims data highlight the potential of ML approaches for improving MS diagnosis — and possible applications for other diseases. 

This example sets the stage for generating the strongest, most impactful evidence you can have — something that is ever more critical as the rules of competition continue to intensify and evolve. 

To increase the chances that today’s pipeline therapies become tomorrow’s accessible treatments, you may not be able to count on the traditional data sources you’ve always used. 

But this isn’t just about “more data is better.” Because that’s not always true. As with the black-and-white versus color metaphor, there’s a time and place for black-and-white art. And there’s a time and place for leveraging a single claims data set that does the trick. 

 Here are some instances where integrated data can truly make a difference: 

• Product launch:  Launch is only getting harder in a competitive landscape, marked by new entrants, evolving regulatory guidelines and changing pricing structures. It’s in your company’s best interest — and patients’ best interests — to use every tool at your disposal to ensure your product makes it to market for every possible impactful indication. 
• Health plan coverage:  Payers want to see greater alignment between reimbursement and value, especially for emerging high-cost precision therapies. Anticipate extra scrutiny in formulary conversations and come prepared to bolster your value narrative amid rising drug spend. If plans turn to additional cost-control mechanisms to inflect drug utilization (such as prior authorization or step therapy), manufacturers will need strong evidence to counter the pressure and maintain formulary positions. 
• Clinical decision-making:  Physicians are showing a growing interest in real-world evidence (RWE) that can guide clinical decision-making. With medicine’s move toward expanded disease risk profiling (for example, for heart disease, cancer, etc.) to improve prevention and targeted treatment recommendations, layered data can help clinicians more fully understand patient populations —and subpopulations. It takes an added layer of insight to identify patients pre-diagnosis or in the early phases of disease progression — insights that you just can’t get with claims alone. 
   
  Plus, with the rise of risk-based payment models, there’s growing incentive to deliver care that is both high quality and cost-effective. Physicians need robust evidence to guide their prescribing choices, help patients thrive and ultimately maintain their financial performance under these evolving payment models. 
• Government drug price negotiations:  With the implementation of the Inflation Reduction Act (IRA) Medicare drug price negotiation program looming, evidence will be essential in grounding conversations with stakeholders on value. Not to mention, market evaluation opportunities may present themselves earlier as a result of drugs being included in price negotiations. 
   
  RWD and RWE are mentioned a dozen times in the latest memorandum from the Centers for Medicare & Medicaid Services on the drug price negotiation program. And while CMS may be setting the terms of those initial price negotiations slated to go into effect in 2026, RWE gives you the opportunity to take greater control of the value narrative across the whole product lifecycle. 

Given all the moving pieces at play, biopharma companies have some tough choices to make about R&D investments, market size and potential, clinical trial design and opportunity for clinical impact. 

To set yourself up for the greatest odds of success, you need the most robust information to analyze your product and the market from every angle. Developing the complete value story with integrated data will allow you to enrich research activity, strengthen go-to-market strategies and meet growing expectations from key stakeholders. 

Put simply, integrated claims and clinical data can help you see the colorful nuances needed to chart a clearer path forward. 

Regulators, payers and physicians all consume RWD for different reasons. But one thing these stakeholder groups have in common is that they’re all looking for meaningful evidence to inform their decision-making. 

That’s why you need to understand patients, populations and markets as holistically as possible. A situation in which seeing data in “color” and capturing a better view of the market and the diverse patient journeys that comprise it is crucial to maximizing the value of your clinical innovations. 

More than just knowing how many scripts were filled or how many patients have a given diagnosis, you want to see patient outcomes. And you want to connect those outcomes to costs, barriers to care, adherence, switching triggers and other details not resident in single-source data sets. 

In addition, true value, and the value upon which a growing number of contracts and formularies are based, is not just lower cost. It is the combination of improved clinical outcomes and reduced cost — the net value of the treatment. And to prove that value, we need to be able to answer questions using both cost and clinical data. 

Working with combined clinical and claims data can add a new layer of information, evaluation and complexity to your research studies. With mounting pressure to reduce costs and improve outcomes from all industry stakeholders, it’s vital that your organization employ any tools to help uncover the complete value story.  

Because those who can only see in black and white are at risk of not innovating in the way that patients need them to. 

Now that integrated data are available at scale — and can even be linked to additional sources (for example, social determinants of health or clinicogenomic data) to draw further insight — organizations of all sizes can get started where it makes sense for them. 

Take the next step toward making more precise business decisions, creating more comprehensive value stories and doing your part to deliver the lower cost, quality outcomes that the market demands. See things in color today.