Cruz Antonio Miguel, Rincon Adriana Maria Rios, Haugan Gregory L
Biomed Instrum Technol. 2013 Nov-Dec;47(6):524-35. doi: 10.2345/0899-8205-47.6.524.
The aims of this paper are (1) to identify the characteristics of maintenance service providers that directly impact maintenance service quality, using 18 independent covariables; (2) to quantify the change in risk these covariables present to service quality, measured in terms of equipment turnaround time (TAT). A survey was applied to every maintenance service provider (n = 19) for characterization purposes. The equipment inventory was characterized, and the TAT variable recorded and monitored for every work order of each service provider (N = 1,025). Finally, the research team conducted a statistical analysis to accomplish the research objectives. The results of this study offer strong empirical evidence that the most influential variables affecting the quality of maintenance service performance are the following: type of maintenance, availability of spare parts in the country, user training, technological complexity of the equipment, distance between the company and the hospital, and the number of maintenance visits performed by the company. The strength of the results obtained by the Cox model built are supported by the measure of the Rp,e(2) = 0.57 with a value of Rp,e= 0.75. Thus, the model explained 57% of the variation in equipment TAT, with moderate high positive correlation between the dependent variable (TAT) and independent variables.
(1)使用18个独立协变量,确定直接影响维修服务质量的维修服务提供商的特征;(2)量化这些协变量对服务质量造成的风险变化,以设备周转时间(TAT)来衡量。为了进行特征描述,对每个维修服务提供商(n = 19)进行了一项调查。对设备库存进行了特征描述,并记录和监测了每个服务提供商的每个工作订单的TAT变量(N = 1,025)。最后,研究团队进行了统计分析以实现研究目标。本研究结果提供了有力的实证证据,表明影响维修服务绩效质量的最具影响力的变量如下:维修类型、该国备件的可用性、用户培训、设备的技术复杂性、公司与医院之间的距离以及公司进行的维修访问次数。所构建的Cox模型得到的结果强度得到了Rp,e(2) = 0.57且Rp,e = 0.75这一测量值的支持。因此,该模型解释了设备TAT变化的57%,因变量(TAT)与自变量之间存在中度高度正相关。