[Applying the clustering technique for characterising maintenance outsourcing].

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: <TAT < 2.56 days on average). Cluster 0 had medium performance (38 % of providers coded V, M, K, Z, T and Y, having an average 9.79 TAT value). Cluster 2 (6 % - provider J) had low performance, having very a high TAT level (101 days on average). 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.