Built on the powerful Mosaic™ Platform, Remedy Informatics’s registry products enable researchers to integrate data from disparate sources into one registry and use cutting-edge pattern recognition tools to gain a 360° degree view of each patient.
Clinical research demands an integrated, dynamic approach to data collection and analysis since the needs are constantly in flux. For too long, researchers at Academic Medical Centers, Clinical Translational Science Institutes (CTSIs), and national disease or specialty associations have been limited to “toy” patient registries or custom built clinical registries that are extremely expensive to build, customize and maintain and still fail to meet researchers’ fundamental needs.
EHR applications, data warehouses, and other medical research software have simply been unable to deliver research registries that allow integration and harmonization of data from disparate sources, the flexibility to adapt their data collection tools and data model over time, and powerful data visualization and pattern recognition tools. Today’s principal investigators need research management software that gives them the ability to collaborate with researchers at other sites and to connect with patients to capture valuable longitudinal data.
With the Mosaic™ Platform and a suite of powerful clinical informatics products, Remedy provides clinical researchers with the tools they need. Remedy products are configurable, off-the-shelf systems (COTS) that AMCs, CTSIs, clinical care providers, and associations can quickly deploy and configure to their specific needs. These highly flexible systems enable clinical researchers to adapt as their research needs change over time, yet provide structure through the Mosaic Ontology™. The Ontology is coupled with a set of tools and applications that enables intelligent queries and ensures quality, semantically consistent data. Remedy products also include cutting-edge data visualization and pattern recognition tools that enable clinical researchers to discover unseen patterns in their data.
Solutions for Clinical Research