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PurposeThe paper aims to investigate cost reduction in logistics and supply chain management of medical supplies.Design/methodology/approachThe paper takes the form of a case study.FindingsIn many healthcare systems, executives focus on cost containment efforts to lower acquisition price of supplies instead of lowering the total delivered cost. However, the case in this research presents a novel contemporary approach to reduce costs by process reengineering in supply chain management.Originality/valueHealthcare managers are continually searching for innovative ways to contain costs without sacrificing quality. To achieve a reduction in costs, hospitals need to review their activities and associated costs, and eliminate nonvalue‐added activities. The novel process reengineering presented in this paper is concerned with the centralization of warehousing and the control of non‐production goods.

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The measurement model developed could be used for any hospital procurement system.

Purpose -Using computer simulation, this paper seeks to model the emergency care process in a hospital and evaluate the effects of some proposed changes to improve patient wait times in the process. Design/methodology/approach -The paper is based upon a case study conducted at the hospital and uses historical data provided by the hospital to simulate the emergency care process. Findings -The simulation results demonstrate that the changes proposed can shorten patient wait times in the emergency care process. The proposed changes involve adding another payment station and a new short-stay ward in the process. Based upon the results, the paper supports the implementation of the changes proposed. Research limitations/implications -A couple of limitations are recognized in this paper. First, the simulation does not consider varying the capacity of resources and locations involved in the emergency care process. Second, the simulation does not consider patients by clinical disciplines in which they are treated. Practical implications -The simulation results show that computer simulation can be an effective decision support tool in modelling the emergency care process and evaluating the effects of changes in the process. The results would be helpful to those who are considering reengineering and improving emergency care or other similar processes in hospitals. Originality/value -Based upon a case study using real-world data, this paper extends the line of studies on computer simulation in healthcare by considering not only patient wait times in the emergency care process but also some ways to improve patient wait times and their effects on the process.

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Highlights Utilized ECDC data Google trend term frequency to forecast the spread of COVID-19 in different regions. Used Spearmann correlation to select the effective COVID related search terms. Proposed a novel technique based on meta-heuristic GWO algorithm to optimize hyperparameters for LSTM network.