Clinical Data Retrieval System

Abstract

 Clinical data analysis requires well-designed clinical data retrieval systems that help users to efficiently obtain desired data without considering the details of complex database structures. In this paper, specialized data-retrieval methods for clinical data analysis are proposed: a condition-setting method suited for dividing retrieved data into two groups, and a method of selecting data items for user data analysis based on data mining. The condition-setting method provides three types of search conditions: precondition, classifier condition, and search items. For both types of condition, complex data-retrieval statements can be expressed by using logical operators to join multiple conditions. The method of selecting data items shows association rules which have high odds ratio as candidate at ributes by using association rule mining.
 Both methods have been implemented in an inpatient case database for cardiac disease. The good usability of the methods has been demonstrated.