There was a time not so long ago when any attempt to extract meaningful insights from a real-world evidence (RWE) database required an army of specialists with job titles like “healthcare informaticist,” “medical coder,” and “data scientist.” Today, thanks to advances in no-code analytics and powerful, cloud-based software, those insights are available to multiple stakeholders — regardless of whether or not they have deep expertise in arcane aspects of healthcare data science. And that has the power to really transform Life Sciences by delivering faster insights to support better decisions.

The phenomenon is being driven by new software that makes it possible for users to query RWE databases using natural language, aided by co-piloting tools that can walk non-data scientists through the process of analyzing patterns of real-world patient behavior. We’ve developed this capability as part of our MapLab™ platform — the first all-in-one offering for healthcare and Life Sciences companies to generate insights into disease trends, treatment pathways, patient populations, and a host of other complex research questions. 

Giving Everyone a Complete View of the Patient Journey 
In practice, what we’re seeing when Life Sciences teams give greater access to RWE to those outside the traditional analyst and data science roles within Clinical Development, Medical Affairs, Commercial and Health Economics and Outcomes Research (HEOR) teams is a broadening of the types of analyses being conducted and much faster production of insights. 

For example, MapView™, an application on our MapLab platform, offers a range of pre-built templates that make it possible for users to quickly produce real-time insights into disease trends, treatment pathways, patient population, brand performance, and more. This solution enables users to capture a complete patient cohort overview — including details such as patient age, gender, demographic distribution, payer and provider types, diagnosis codes, and prescription trends — in minutes. Detailed, real-time patient data can now be incorporated into the baseline strategy-planning process.

And because the RWE dataset is being updated continuously as new encounters are added to our Healthcare Map™, we’re seeing teams keep these analyses running in the background to track changes over time as data refreshes and new evidence is gathered from clinical research and other sources. Ultimately, we see this as a tremendous opportunity to unlock new patterns that no one ever thought to track before because they never had the time, the bandwidth, or the coding expertise to do so. 

At each step, easy, universal access to RWE insights makes it possible for Life Sciences teams to keep digging deeper into the links between specific therapeutic interventions and real-world patient outcomes, tracking metrics like target population growth, new patient starts, and even regional trends in utilization. 

A Common Language Built on Patient-Centric Insights
Perhaps more importantly, we’re starting to see the emergence of a common language of data-driven real-world insights that is being shared across the Life Sciences enterprise. Over time, this communication will create a truly patient-centric approach to Life Sciences research. By using Komodo’s platform to track real-world patient journeys and designing clinical, commercial, and medical affairs strategies based on that data, our clients are able to find new ways to innovate, collaborate, and create efficiencies of scale.

Read more about how Komodo’s real-world data is powering new insights for Life Sciences teams.

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