Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 5292-5305 |
| Number of pages | 14 |
| Journal | Expert Systems with Applications |
| Volume | 40 |
| Issue number | 13 |
| DOIs | |
| State | Published - Apr 9 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General
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