BG Medicine - Clinical Data Appliance

BG Medicine - Clinical Data Appliance

To support a cardiovascular test developed by BG Medicine, Quoin implemented a network-based application using Java and a rules framework to retrieve, score specific clinical patient data, and generate a result to predict adverse patient outcomes. The project objective was to build an easily-deployed software and hardware solution that can access patient data, apply rules-based calculations, and provide the resulting index value as a new result for a patient's medical records.

BG Medicine - Clinical Data Appliance

To support a cardiovascular test developed by BG Medicine, Quoin implemented a network-based application using Java and a rules framework to retrieve, score specific clinical patient data, and generate a result to predict adverse patient outcomes. The project objective was to build an easily-deployed software and hardware solution that can access patient data, apply rules-based calculations, and provide the resulting index value as a new result for a patient's medical records.
BG Medicine is a life sciences and diagnostics company focused on the development of cardiovascular diagnostic tests. The Galectin-3 Test was its first commercial product. Our overall technical approach was to construct a standalone software and hardware appliance – a Java-based application and open source rules framework (JESS) deployed to a dedicated Linux server. The BG Medicine AMIPredict application integrates with a specific LIMS middleware system, Data Innovations Instrument Manager, to enable access to clinical data. The appliance essentially emulates a laboratory system, using the appropriate Instrument Manager API to read clinical data and write the results after applying the rules-based scoring. As the architecture was designed for versatility, the appliance can be deployed to any number of clinical or laboratory environments. The application was designed to be light-weight, and require limited processing capabilities. Thus, the 'server' could be any small-footprint Linux device. Another key objective was to support easy updates to the rules, as the scoring algorithm for the Galactin-3 Test evolves.

We assembled a project team with a technical lead and 2 software engineers. Our technical lead worked closely with senior management at BG Medicine to ensure that our technical approach supported life science and compliance requirements. Quoin was responsible for technology selection, architecture, design, implementation, and testing. We collaborated with client stakeholders to ensure that AMIPredict could be used as part of the clinical trials, which required a series of internal reviews, and modifications to the original application design. Our work on this application demonstrates how Quoin can tackle a complex problem and rapidly define an effective technical solution.