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

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. © 2013 Elsevier Ltd. All rights reserved.

• Fecha de publicación: 2013
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: eng
• OAI Identifier: oai:repository.urosario.edu.co:10336/24051
• Acceso en línea: https://doi.org/10.1016/j.eswa.2013.03.034; https://repository.urosario.edu.co/handle/10336/24051
• Palabra clave: Biomedical engineering; Cluster analysis; Data mining; Hospitals; Maintenance; Medical problems; Operations research; Quality of service; Association discoveries; Clinical engineering; Clustering analysis; Clustering techniques; Corrective actions; Intrinsic failure; Outsourced services; Scheduled maintenance; Biomedical equipment; Biomedical engineering; Clinical engineering; Clustering analysis; Data mining; Hospital; Maintenance and engineering; Operations research; Outsourced services
• License: Abierto (Texto Completo)