Real-world evidence and its role in healthcare and life sciences

Data is integral to what the life sciences industry does. To establish and run clinical trials, companies depend on data about the disease state, the molecule they are working with, similar products on the market and, most crucially, the patient.

Aside from advancing clinical trial recruitment, access to real-world evidence (RWE) helps life sciences companies in a number of other ways. For example, it enables companies to compare drug pricing to determine how to competitively price their drug on the market. It also helps companies to assess outcomes of similar drugs and consider ways in which they might tweak their drugs to perform better.

But companies have had difficulty getting the data they need. Historical market scans of real-world environments don’t provide enough depth of information. And finding the right patients for clinical trials has long been a struggle. Under HIPAA and other privacy laws, life sciences companies are excluded from mining data that would give them pertinent patient insight. So, they go through laborious informed-consent processes to enroll patients and conduct follow-up studies into the use of their drug.

If they were able to have that process managed from a central bank or database, whereby a third party would gain consent from the patient and provider to share information, the process of identifying patients for clinical trials would be simplified significantly. The outcome is the same as going through traditional channels — but far less laborious and far more targeted.

Opening the door to actionable patient data

There have been several developments in recent years that have eased access to relevant patient data. First, regulatory authorities are changing attitudes. The U.S. Food and Drug Administration (FDA) released the framework for its RWE program in December 2018, backing the use of real-world data sources, such as registries and data from electronic health records, to support study designs including randomized trials and observational studies.

Support for using patient data has been gaining among other government bodies as well. For example, the U.S. Social Security Administration has been working with large integrated delivery networks to gather patient information to determine whether to approve or reject a Social Security claim.

Advances in standardization practices have played an even more important role in terms of putting actionable RWE into the hands of not only life sciences companies, but also healthcare providers and payers. One of the biggest barriers to advancing RWE has been a lack of data consistency. Different stakeholders don’t speak the same language. Consider the varying terms used to describe the end customer: for providers, it’s a patient; for payers, it’s a member; and for life sciences companies, it’s a subject.

Standardization — bringing together Fast Healthcare Interoperability Resources (FHIR) as used by providers and payers and the Observational Medical Outcomes Partnership (OMOP) Common Data Model as used by life sciences — makes it possible to break down such language barriers. The objective is to enable the three different parties to exchange and extract data using their language within a single, cohesive, coordinated and structured environment.

Ultimately, standardization translates all the data into a standard format that is usable by any party to support the convergence across the wider healthcare industry. This is done to achieve the overarching objective: to provide value-based care to patients.

With access to RWE from multiple different sources, life sciences companies as well as payers and providers will have an opportunity to shift the dial on healthcare, while also advancing their own business objectives.


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