Specialty data enables the creation of sub-cohorts to increase your understanding of therapy adoption and patient adherence, persistence, and outcomes.
Improving health outcomes for a patient population defined by a single ICD-10-CM code has never been an easy, one-size-fits-all proposition. Rather, Commercial teams must understand a multitude of variables that can impact both a patient’s access and response to a therapy.
Obtaining these insights isn’t easy.
While administrative claims data connects the dots for understanding the various pathways to a diagnosis and treatment decision, it lacks the context that could explain, for example, why a diagnosis is often delayed, what led to a therapy choice, and why one patient responded to a therapy when another didn’t.
To answer these questions, specialty data such as lab results, genomics, clinical variables, health insurance, social determinants of health, and race and ethnicity (to name a few) must be integrated with claims data. This enables a multidimensional view that surfaces sub-cohorts within a patient population. Commercial teams can then take a more targeted, better-informed approach to HCP engagement.
A recent Komodo webinar featured the power of integrating data sources. Here are some key takeaways:
.png)
New data sources — including those outside of the healthcare system — have the potential to predict and prevent health events, impacting 80% of health outcomes.
Clinical data from EHRs, genomics, and wearables is already being integrated with administrative claims data to generate a deeper understanding of population health, identify patients with rare disease, and assess how a therapy impacts various sub-cohorts. As the use of digital devices continues to grow, so does the potential for richer insights.
.png)
Life Sciences companies can streamline access to multiple types of specialty data by working with a data partner that has pre-integrated data sources, accelerating speed to insights. Accessing and integrating specialty data is no small feat. A recent industry survey revealed the process of linking, deduplicating, cleaning, and standardizing data takes seven months, on average. Organizations can shave four to nine months off their data-management timeline by accessing pre-integrated data from one source.
Data layering enables deeper, richer insight into the market landscape and patient journey. Commercial teams can access specialty data to support a variety of use cases. For example, teams can track brand performance in highly specific patient populations by including genomic/biomarker data, or leverage predictive modeling to identify HCPs who are most likely to see patients in a highly defined cohort:
If you’d like more information on how Komodo’s MapEnhance™ gives you both a more holistic and granular view of a patient population, just let us know.
To see more articles like this, follow Komodo Health on X, LinkedIn, or YouTube, and visit Insights on our website.
