Selecting medical equipment is a complex multidisciplinary task requiring mathematical tools, considering associated uncertainties. This paper offers an in-depth study of multiple-criteria decision analysis (MCDA) methods to identify the most appropriate ones for performing management tasks in resource-limited settings. The chosen articles were divided into three topics: evaluation of projects and equipment, selection of projects and equipment, and development of medical devices. Three methods (analytic hierarchy process [AHP], multi-attribute utility theory and elimination and choice expressing reality) were selected for detailed analyses of their application for medical equipment management. Twenty-one work using MCDA, artificial neural networks, human factors engineering, and value analysis were analysed in the framework of medical equipment management. The important aspects of the procedure were described, highlighting their advantages and disadvantages. It was determined that the AHP approach corresponds to all defined criteria for selecting large medical equipment. Managing large medical equipment using MCDA will reduce uncertainties, and provide a rational selection and purchase of the most efficient equipment in resource-limited settings. The direction for improving the AHP method was determined.
Development and Evaluation of a WiFi-based Location Detection System for Medical Equipment Management
