Architecture and application of an innovative decision-support module for use in primary care with electronic patient records

This project is designed to develop a decision-support module to be used with electronic patient records. By using innovative methodologies to analyze patient data as well as the sharing of such data with clinicians and the patients themselves, the project seeks to resolve current problems faced by clinical decision-support information systems (including problems that have limited the impact that these systems have had to date on medical practice). The central hypothesis of this research initiative is that the use of a matrix of patterns can accommodate the complexity of diagnostic information. As a main innovation, we will build and evaluate an intelligent engine to connect specific patterns with a visual representation of contextual knowledge modelled on physician and patient mindsets. This dynamic engine will be able to prescribe diagnostic tests and therapies directly or query and obtain complementary information immediately. Myca, a company that is developing an electronic patient record platform, is counting on its research partners with expertise in medical information systems to design a high-quality, valued-added module for their information platform.

Faculty Supervisor:

Dr. Andrew Grant

Student:

Almehdi Aitnouri, Paul Fabry and Albert Tsanaclis

Partner:

Myca

Discipline:

Biochemistry / Molecular biology

Sector:

Information and communications technologies

University:

Université de Sherbrooke