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New feature - Cohort Explorer: Explore insights and build cohorts in one place

July 12, 2023

Announcing the latest NeuroBlu feature: Cohort Explorer - visualize and refine cohorts in one step to accelerate study feasibility and direction.

We need more research on behavioral health

The mental health crisis is a defining problem of our generation, but there is a debilitating lack of evidence and progress. To address this challenge, we have created NeuroBlu, a best-in-class analytics tool for behavioral health insights powered by the most robust real-world database in the field. We are continually working with partners, advisors, subject matter experts, and thought leaders to improve our software and database. Our goal is to ensure we are enabling the most robust real-world evidence and driving better outcomes in behavioral health. Here is the latest update to NeuroBlu:

Refine, analyze, and visualize cohorts, without coding, all in one place

When formulating a behavioral health research question, the first step is to examine a population of interest. It is critical to understand the size and demographic characteristics of this population, engagement, events within healthcare systems, treatments, and outcomes. This information helps refine the criteria used to build a cohort and informs what variables could be analyzed in a study.

We built Cohort Explorer so researchers can quickly and easily refine, analyze, and visualize cohorts, without coding, all in one place. Instead of going directly to the data based on a set of assumptions and experiencing trial and error, researchers can answer questions like:

  • Is this cohort large enough to merit further analysis?
  • Do demographic characteristics align with expectations/previous research?
  • Which outcome measures are most frequently captured?
  • What are the most common diagnoses and commonly prescribed drugs?
  • What is the frequency and duration of visits and hospitalizations?

Researchers can use Cohort Explorer to confirm or correct assumptions, identify new patterns, and flag outliers within patient populations, accelerating decision-making around study feasibility and direction.

Step 1: Select cohort criteria, Step 2: Visualize and explore cohort

Cohort Explorer also enables researchers to compare drugs and drug cost-effectiveness within a given cohort. Previously, the ability to view disorder trends and compare drugs and economic burden was separate from the ability to build cohorts. At Holmusk, we are continually updating the platform to incorporate feedback from our partners, so now, Insights Explorer and Cohort Builder are one higher-powered feature - Cohort Explorer.

“Cohort Explorer helps me quickly and easily identify characteristics within a real-world data cohort, as if I was a clinician observing thousands of patients in a clinic over a number of years.” - NeuroBlu user

Generate cohorts with data representative of how patients actually receive care in clinical settings

EHR data provides the most granular, complete picture of what is happening when a patient receives care during routine clinical practice. EHR data can provide answers, through a real-world lens, to the same questions that have been traditionally addressed with clinical trials. At Holmusk, we urge the behavioral health industry to view different types of data as complementary and to recognize the strengths and limitations of each. Clinical trial data, although highly structured and characterized by frequently captured outcome measures, does not necessarily represent how a treatment will work outside of a trial, in non-controlled environments, and in different populations.

The NeuroBlu Database is the world’s leading source of real-world data for behavioral health, with over 1.5M+ patients, 30+ geographically diverse health systems, and 20+ years of longitudinal data. The database contains behavioral health conditions, assessments, and pharmacological treatments as well as symptoms, external stressors, and social determinants of health extracted from unstructured notes via novel natural language processing approaches.

Cohort Explorer combines the power of real-world data with the ability to quickly refine and analyze cohorts. Researchers can make more informed decisions about how the characteristics and patterns within a cohort will inform study feasibility and direction, without coding.

Interested in learning more? Contact us to schedule a demo.

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