NorstellaLinQ: Creating real-world data products for what’s next

Run time

1 minute, 3 seconds

This abstract explores how a client-focused approach aims to bring organizations closer to patients by deeply understanding the context surrounding targeted patient populations, including social determinants of health, prior therapies, and ongoing clinical trials. Rather than relying on high-level descriptions, the emphasis is on interpreting what these contextual factors mean in practice, identifying barriers that prevent patients from accessing or staying on therapy, and determining the highest-impact decisions needed to remove those barriers and support optimal treatment initiation.

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I think everything that we do is really about how do we help our clients get closer to a patient? How am I better informing context? What is happening around that patient from the point of social determinants of health to the therapies that they may have stepped through to the clinical trials that are ongoing around them. I’ve got to be able to get deeper and deeper and understand contextually what’s happening around a targeted patient population. Don’t just paint me a picture, but help me think about what that means. What are the implications around the barriers that maybe this patient has to getting on therapy and what are the highest impact decisions that stand in front of me to helping clear those barriers and get that patient on therapy?

Frequently asked questions

What is the primary goal of real-world data insights?

The primary goal is to help life sciences organizations better understand patients, their treatment journeys, and the barriers impacting access to therapy so they can make more informed decisions.

How does real-world data help pharma companies get closer to patients?

RWD provides deeper insight into patient experiences, including treatment history, social determinants of health, and access challenges, helping organizations better understand the full patient journey.

Social determinants of health are non-medical factors—such as income, education, transportation, and access to care—that can influence a patient’s health outcomes and ability to receive treatment.

How can RWD identify barriers to therapy access?

Integrated datasets can reveal factors such as prior treatment requirements, payer restrictions, socioeconomic challenges, and clinical complexities that may prevent patients from accessing therapy.