Assessing the queuing process using data envelopment analysis:an application in health centres

Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages

A review on simulation models applied to emergency medical service operations

International audienceEmergency medical services (EMS) are public safety systems responsible for the pre-hospital stabilization and transport of seriously injured patients. The goal of such systems is to respond adequately to population calls by providing first aid services and transferring patients, when needed, to the emergency department of the appropriate hospital. In order to achieve this goal, a variety of tools (e.g. simulation, mathematical programming and queuing theory models) have been used to improve the performance of EMS. This paper focuses specifically on computer simulation models used for the analysis and improvement of EMS. In particular, we give a critical overview of the existing international literature on simulation models for EMS by pinpointing the issues considered, the associated modeling assumptions as well as the results obtained. Such a contribution is lacking in the current literature