Katia Druzhynina, Pippa Hodgkins, Lucy Mosquera

Driven by our mission to redefine real-world evidence generation, Aetion is committed to ongoing platform and application improvements that enable teams to advance their work with greater speed and precision. In this blog, we highlight the product enhancements over the first half of the year—from improved text reporting options in Aetion® Substantiate to multi-table transformation in Aetion® Generate—which demonstrate our ongoing effort to boost usability and expand scientific utility across Aetion Evidence Platform® (AEP).

Recent enhancements to Discover expand outcome tracking and improve study management, helping users scale analyses and streamline workflows.

• New Prevalence Outcome: Run Prevalence as an outcome in analyses to capture the proportion of the population with an existing condition alongside incidence metrics. 

Image 1: Capture point and period prevalence with visual options including bar plot, number card, line graph, or table.

• Additional outcome support: Support research by adding as many outcomes as needed to Discover analyses. 
• Archiving Analyses: Archive completed Discover analyses to stay organized without losing access for future reference or review.
• Measure Import Tool: Import custom-created, validated Substantiate measures to streamline study setup, improve consistency, and support methodological transparency across research efforts.
  
  

Three new feature updates target expanded results capabilities and an improved user experience within Substantiate.

• Improved Text Reporting for Patient Characteristics: Use text-based Event Value measures as patient characteristics or covariates in descriptive and comparative analysis plans, with options to aggregate by first, last, or most frequent value.
• Baseline Period Attributes in Population Exploration: Define custom time periods for attributes in Population Exploration, including intervals before cohort entry, to extract insights like top medications or ICD-10 codes across any relevant timeframe.

Image 2: Specify key attributes of interest in a defined population in Population Exploration.

• Comparative Cohort from External Source: Create comparative cohorts from CSV files using patient ID, entry date, and exposure index columns for use in Comparative Effectiveness and Event Exploration analyses.
  
  

The latest updates to Generate strengthen privacy safeguards, streamline large-scale data processing, and support flexible transformations across complex, multi-table datasets.

• Identifier Transformation Across Multi-Tables: Ensure consistency in longitudinal analyses by applying transformations uniformly across linked datasets. 
• Advanced Identifier Transformation Methods: Use advanced techniques like conditional suppression, quantile transformation, and binning to protect sensitive data while preserving utility. 
  

Image 3: Example identifier transformations applied to raw tables before consolidation. 

• Partial Longitudinal Synthesis (PLS): Create synthetic versions of multi-table datasets with linked identifiers to enable integration across sources.
• Accelerate re-identification risk assessments: Run large-scale assessments faster using optimized, parallelized processing—now with uniqueness calculation to estimate the probability that a record is unique at both the sample and population levels.
• New Date Transformations: 
  • Generalize date values by specifying a new format for the date (e.g., transform YYYY-MM-DD to YYYY-MM).
  • Use date shift transformation to apply “noise” that shifts dates randomly within a defined minimum and maximum magnitude. 
    

What to Expect in H2 2025

In the next half of 2025, Aetion will introduce new capabilities that will increase time to insights, foster greater collaboration across diverse teams, and strengthen data privacy.

• Introducing Aetion® Activate for End-to-end Data Management and Analytics: Accelerate the transformation of real-world data into analysis-ready datasets with our newest product, which brings low-code and technical users together on a single platform. This allows teams to efficiently define measures, transform complex datasets, and execute advanced analytics in a reproducible, audit-ready workflow. 
  
• Expanded EHR and Linked Integration in Discover: Unlock deeper insights with enhanced integration of EHR and linked claims data in Discover for more robust insights across complex patient populations.
• Enhanced Privacy Features in Generate: Scale support for larger datasets and reduce run time. 

Explore What’s Next in RWE

Ready to streamline workflows, strengthen data integrity, and scale analytic capabilities across your organization? Connect with us to see how Aetion can support your next study with our end-to-end evidence generation solutions.