Abstract
Objective: To use clustering techniques to characterize maintenance service providers in a health care institution.
Methods. The study analyzes the inventory of equipment belonging to 7 pilot areas (264 medical equipment). Clustering techniques are applied using 26 variables. Among the most significant: response time (RT), duration of interventions (DR), availability and time to change state (TAT).
Results: The average obsolescence of biomedical equipment is 0.78. Four groups of service providers are identified. Groups (1 and 3): Better performance, lower TAT, RT and DR values; whose providers are: O, L, C, B, I, S, H, F, G; they represent 56 % of the total; with TAT values between: 1.4 days provider: J, represents 6 % of the total sample analyzed.
Conclusions: The methodology used allowed characterizing the inventory of medical equipment and maintenance service providers. The clustering technique proved to be effective in identifying the most competitive suppliers.
Methods. The study analyzes the inventory of equipment belonging to 7 pilot areas (264 medical equipment). Clustering techniques are applied using 26 variables. Among the most significant: response time (RT), duration of interventions (DR), availability and time to change state (TAT).
Results: The average obsolescence of biomedical equipment is 0.78. Four groups of service providers are identified. Groups (1 and 3): Better performance, lower TAT, RT and DR values; whose providers are: O, L, C, B, I, S, H, F, G; they represent 56 % of the total; with TAT values between: 1.4 days provider: J, represents 6 % of the total sample analyzed.
Conclusions: The methodology used allowed characterizing the inventory of medical equipment and maintenance service providers. The clustering technique proved to be effective in identifying the most competitive suppliers.
| Translated title of the contribution | Application of clustering techniques to characterize maintenance service providers. |
|---|---|
| Original language | Spanish (Colombia) |
| Pages (from-to) | 464-473 |
| Number of pages | 10 |
| Journal | Revista de Salud Publica |
| Volume | 12 |
| Issue number | 3 |
| DOIs | |
| State | Published - May 1 2010 |
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
- Public Health, Environmental and Occupational Health
- Biomedical Engineering
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