Abstract

CRUZ, Antonio M; BARR, Cameron  and  PUNALES-POZO, Elsa. Building a New Predictor for Multiple Linear Regression Technique-based Corrective Maintenance Turnaround Time. Rev. salud pública [online]. 2008, vol.10, n.5, pp.808-817. ISSN 0124-0064.

Objectives This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. Materials and methods The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Results Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE_rt, 0.415 positive coefficient), stock service response time (Stock_rt, 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock_rt, CE_rt and priority, in that order. Clustering techniques revealed the main causes of high TAT values. Conclusions This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Keywords : Maintenance; regression analysis; biomedical technology; decision support system; management.

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