EHDEN - D3.4 - Second Report on the Implementation of the Analytical Pipeline for Personalized Medicine

There are large opportunities to use the massive amount of observational data in Europe for personalized decision-making. However, the lack of inter-operability of the data sources makes this a challenging task. The differences in structure (syntactic inter-operability) and terminology systems (semantic inter-operability) make the development of standardized analytical pipelines cumbersome. The European Health Data and Evidence Network (EHDEN) project is addressing this by standardizing a large amount of European data sources to the OMOP Common Data Model (CDM). The goal of WP3 “Personalized Medicine” is to establish a standardized process to enable personalized decision-making that can be utilized for multiple outcomes of interest and can be applied to observational healthcare data from any patient subpopulation.

In the first report on WP3 activities, we introduced the analytical pipelines for Patient-Level Prediction and Population-Level Effect Estimation. Furthermore, we discussed our initial work for the development of a pipeline for Risk Stratified Effect Estimation to assess heterogeneity of treatment effect.

The current second report provides an update on the work done in the second year. This includes an overview of use cases in which the analytical pipelines have been applied and describes the advances made in methodological research, the start of a natural language processing pipeline, and work done to develop a pipeline for disease trajectories.

This work falls under Task 3.2. “Development of an integrated patient-level prediction pipeline” (M6-M60), Task 3.3 “Development of an integrated risk-effect estimation pipeline” (M6-M60), and Task 3.4 “Development of a pipeline for disease trajectory analysis” (M12-M36).