Through coursework in bioinformatics, human genetics, molecular biology, computer science, and statistics, learning comes through practical training in the methods and software used in analysis of genetic data and through training in a specific area of the student’s choice.
Clinical Research Decision Support
Research supported by the ARDS Network and NIH RoadMap grants have developed computerized bedside clinical decision support applications which have been used indirectly in multicenter clinical trials. These software tools have been developed for glucose control, fluid and hemodynamic support and ventilator support. The glucose application has been shown to be effective in obtaining strictly comparable results for adult and pediatric ICU patients in maintaining optimal blood glucose. These tools are being used in this and other countries. This research has expanded to develop a protocol application for heart failure management since there is a lack of tools that enable clinicians to consistently link practice decisions to evidence-based guidelines and ensure reproducible methods. The new application will monitor and assure clinician behavioral change, and reinforce process improvement, while preserving patient-specific treatment and ultimate clinician decision making authority over a spectrum of care extending from the intensive care unit, through the hospital ward, outpatient clinic and into the home.
Several faculty in the Department of Biomedical Informatics are involved in the Health Sciences Center-wide Clinical and Translational Science Award (CTSA). This effort concentrates on systems development, standards, vocabularies and metadata for interoperability, assisting clinical researchers to translate their research findings in the practice of medicine. The entire chain of faculty expertise spreads across the domain from basic research into patient care and public health—translation and effective adoption of research results requires each link in the chain.
New Research Infrastructure
As part of a CTSA initiative and in conjunction with the University’s Center for Clinical and Translational Science, new and cutting edge research is being built using federated query technology, grid computing applications and natural language processing. Many faculty from the department are lead architects of these next generation systems.