Evaluating record history of medical devices using association discovery and clustering techniques

• The association discovery revealed problems in users’ training.
• Clustering technique uncovered the main causes of equipment’s failures.
• The service requests ratio average dropped dramatically from 6.4 to 0.4 under the analyzed period.

In this research, association discovery and clustering techniques were utilized for improving the efficiency of a hospital’s service and of the maintenance tasks in a clinical engineering department. The indicator in this study is service requests. The association discovery techniques revealed problems in users’ training (errors in operating procedures), intrinsic failures in medical devices, and badly scheduled maintenance policies. Clustering techniques uncovered the main causes of failures. With the evidence obtained corrective actions were taken. The service request average dropped dramatically from 6.4 to 0.4 during the analyzed period.