Announcing NeuroBlu v3.8, the first release of 2024! This version of NeuroBlu integrates a suite of comprehensive data features and our new NeuroBlu NLP psychotic disorders model for in-depth research across our extensive patient database. NeuroBlu v3.8 is at the forefront of mental health data analysis with enhanced processing speeds and a strategic dataset management update.
A New Dataset Management Strategy
We have introduced a new Dataset Management Strategy Update, where with one Active Dataset (updated approximately every 6 weeks) and four Static Datasets (snapshots of the Active Dataset taken every 6 months) promises flexibility for both current and longitudinal research needs. The retirement of legacy datasets (NeuroDB 22R1 through 23R7 with exclusions to bi-annual snapshots) paves the way for this new data structure. We are updating the NeuroBluDB Active on February 15 with the 24R1 release and future enhancements, updates, and new data will be added regularly to the Active Dataset. This strategy is designed to optimize your experience with our datasets, ensuring you can access the most relevant and stable data for your research needs. For current partners and those undergoing a NeuroBlu trial, additional information on these changes and how to adapt to them is available in our updated documentation in the User Manual upon logging in NeuroBlu.
Upgraded Data Features and Refinements
In addition to our NeuroBlu NLP depressive disorders model, we have now developed a psychotic disorders model that transforms information from unstructured clinical notes into structured, analyzable, and actionable data. New measurement functions (get_NLP and get_Descriptives) as well as NLP-enhanced data enable deeper data exploration, profiling over 14,000 patients. We have also leveraged NeuroBlu NLP to resolve conflicting demographic data to enhance the accuracy of patient identification.
New outcomes measures in NeuroBlu include the PCL-5 and the PC-PTSD-5. The PTSD Checklist for DSM-5 (PCL-5) is a 20-item self-report measure that assesses the 20 DSM-5 symptoms of PTSD, and the Primary Care PTSD Screen for DSM-5 (PC-PTSD-5) is a 5-item screen that was designed to identify individuals with probable PTSD in primary care settings. A new addition of Census (ACS 5 Year) data enriches geographic, SDOH, and epidemiological analysis for multifaceted research.
This expansion also introduces two additional versions of the Columbia Suicide Severity Rating Scale (C-SSRS). Previously, NeuroBlu included the 6-question screener (C-SSRS Screener - Recent), which contains Y/N responses. Now, The C-SSRS Lifetime/Recent Full Scale (containing Y/N, frequency, and likert-type responses) and the C-SSRS Frequent Screener (containing Y/N but omits question 1 from the 6 item screener) are also available. Across two data partners, adding these versions of the C-SSRS resulted in a 97k increase in patients with C-SSRS.
We have also revamped measurement templates and removed outdated measurements (smoothened CGI-S and derived MSE) to align with cutting-edge research standards. The ability to identify symptom patterns and provider insights is now enhanced by adding new data tables and millions of provider_ids.
User Experience Enhancements
A tenet of NeuroBlu v3.8 is versatility - the ability to address a broad spectrum of research needs, from quick, preliminary analyses to detailed, longitudinal studies. We have implemented enhancements to Cohort Explorer and Treatment Journey - accelerated processing and intuitive visualization features ensure streamlined research workflows. Treatment Journey, a new feature launched in December of 2023, captures a timeline view of a cohort's pharmacotreatment journey using EHR data. Leverage Treatment Journey to map patient progress over time to generate new perspectives on treatment efficacy.
NeuroBlu v3.8 embodies our relentless pursuit to provide depth, flexibility, innovation, and precision in behavioral health analytics. Join us as we continue to drive mental health research forward with real-world data that leads to better evidence generation and in turn, better patient outcomes.
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