HEALTHTECH
Public data, private insight - pharmaceutical trade analytics for Hungary's National Health Insurance Fund
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Live
In production on Smart DataLake (DLX)
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Month-to-month
Trend analysis on Hungarian medicine trade data
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NEAK
National Health Insurance Fund of Hungary
The challenge
Public health data published but not analysed insight trapped in raw numbers
The National Health Insurance Fund of Hungary (NEAK) publishes pharmaceutical trade data on its official website - monthly figures on drug consumption, pricing, and market movement. This data has significant value for health economic decision-making and pharmaceutical market intelligence, but in its raw form it remains opaque. The challenge was transforming publicly available data into actionable trend analysis that surfaces correlations and provides decision-relevant insights for the health and economic sectors.
The solution
Smart DataLake (DLX) pharmaceutical trend analysis built on public data
E-Group built a trend analysis dashboard on its Smart DataLake (DLX) platform, ingesting NEAK's publicly published medicine trade data and applying the same data engineering, transformation, and business intelligence methodology used in the InnoHealth DataLake. The system generates month-to-month trend analysis - identifying patterns in drug consumption, pricing trends, and market movements - and surfaces correlations that would be invisible in raw tabular data. The platform demonstrates DLX applied to health economic analysis rather than clinical research.
The result
Health economic intelligence from public data - live in production
The NEAK analytics platform is live in production, delivering pharmaceutical market trend analysis to health and economic sector stakeholders. The project demonstrates the versatility of E-Group's Smart DataLake platform across the full health data spectrum - from clinical research (InnoHealth, HeliX) to health economic intelligence - and its ability to extract genuine analytical value from data that is publicly available but underutilised.