An approach for predicting and describing patient outcome using multicriteria decision analysis and decision rules

Patient outcome in brain trauma patients is affected by a multiplicity of factors, beginning with ambulatory transportation and routing, to the grade of the receiving facility and treatment therein, and finally the treatment and monitoring in definitive care (the brain trauma intensive care unit). Factors and events in each of these phases can be modeled as a multicriteria problem, where the objective is to optimize patient outcome; moreover, a more comprehensive model can embody the interactions of all three phases. This study focuses on modeling the factors that affect patient outcome in definitive care and on expressing these in machine readable format so that we can better describe or predict patient outcome using data mining tools. We use multicriteria decision analysis and decision rules for knowledge representation. Preliminary results suggest that the incorporation of a priori knowledge does help better predict or describe patient outcome when using decision tree induction.