The implementation of information systems in the medical field has created an abundance of valuable data. We use decision tress and association rules on real world hospital data to uncover interesting patterns. We build two different models linking diagnoses and procedures. We also use associative rules to explain the relationship between the principal payment source and the charges reported in our sample data. Our models could serve as a valuable tool for practitioners to increase decision confidence, as well as insurance companies to review their patients' cases at a considerably lower cost.
