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Updated: Jun 4, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
Published on: December 9, 2022
[Applying the clustering technique for characterising maintenance outsourcing]
Antonio M Cruz1, Sandra P Usaquén-Perilla, Nidia N Vanegas-Pabón
1Departamento de Ciencias Básicas, Facultad de Medicina, Universidad del Rosario, Bogotá, Colombia. antonio.cruz43@urosario.edu.co
Objective:
Using clustering techniques for characterising companies providing health institutions with maintenance services.
Methods:
The study analysed seven pilot areas' equipment inventory (264 medical devices). Clustering techniques were applied using 26 variables. Response time (RT), operation duration (OD), availability and turnaround time (TAT) were amongst the most significant ones.
Results:
Average biomedical equipment obsolescence value was 0.78. Four service provider clusters were identified: clusters 1 and 3 had better performance, lower TAT, RT and DR values (56 % of the providers coded O, L, C, B, I, S, H, F and G, had 1 to 4 day TAT values:
Conclusions:
The methodology allowed medical equipment inventory and maintenance service suppliers to be characterised. The cluster technique was effective in identifying the most competitive suppliers.
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