The Brigham and Women’s Hospital and Harvard Medical School research team will be creating an IT framework that aids in extracting, managing and analyzing relevant data from electronic medical records and medical claims to enable causal inference and improve comparison of the effectiveness of various treatments. The team will also be developing a repeatable approach that allows organizations to use the framework to better understand the relationships between prescription drug use and health outcomes.
The Coalition Against Major Diseases (CAMD) at Critical Path Institute (C-Path) will be exploring the use of Oracle Health Sciences Empirica Study On Demand to perform data mining and analysis on C-Path’s Online Data Repository. This database contains clinical data for over 5,700 patients with Alzheimer’s disease, pooled from the control arms of 20 pharmaceutical and other clinical trials. Working with the FDA and EMA, researchers hope to learn how to effectively apply advanced data mining methods and tools to gain insight helpful in the evaluation of efficacy and safety of new treatments for neurodegenerative diseases.
The Human-Computer Interaction Lab at the University of Maryland will be expanding development of a tool to facilitate the visualization of patient clinical data patterns over time, as they apply to drug safety signals in large repositories of longitudinal healthcare and claims data. Visual data has been proven to significantly improve the thought processes of researchers. As such, the newly-designed tool is expected to help accelerate and broaden adverse events analysis, leading to new insights, as well as expanded research opportunities.
