This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,Egypt.We construct a patient flow division model by divid...This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,Egypt.We construct a patient flow division model by dividing patients according to their severity level.Although patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay(LoS),there is a lack in a detailed system evaluation and implementation under this configuration.Based on system observation and health care provider’s interviews,a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system.A discrete event simulation model of the Emergency Department is built using collected data.Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division,including different staff capacities and different patient magnitudes.Results indicate that waiting times and length of patient stay can be significantly improved under the proposed7 system configuration.展开更多
The Kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited capacity.Arrival patients who find all beds occupied are simply turned away,i.e.,no waiting is allowed...The Kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited capacity.Arrival patients who find all beds occupied are simply turned away,i.e.,no waiting is allowed.This paper investigates the impact of an early discharge approach that can be applied to patients that have been scheduled to discharge within 5 h.A discrete event simulation(DES)model is built using empirical distributions based on real data.The model has been validated against real data and the results have shown that the proposed early discharge approach can reduce the number of turned away patients by 10%in the Kidney Department,equivalent to 182 patients annually and by 11%in the Oncology Department,equivalent to 150 patients annually.展开更多
文摘This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,Egypt.We construct a patient flow division model by dividing patients according to their severity level.Although patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay(LoS),there is a lack in a detailed system evaluation and implementation under this configuration.Based on system observation and health care provider’s interviews,a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system.A discrete event simulation model of the Emergency Department is built using collected data.Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division,including different staff capacities and different patient magnitudes.Results indicate that waiting times and length of patient stay can be significantly improved under the proposed7 system configuration.
文摘The Kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited capacity.Arrival patients who find all beds occupied are simply turned away,i.e.,no waiting is allowed.This paper investigates the impact of an early discharge approach that can be applied to patients that have been scheduled to discharge within 5 h.A discrete event simulation(DES)model is built using empirical distributions based on real data.The model has been validated against real data and the results have shown that the proposed early discharge approach can reduce the number of turned away patients by 10%in the Kidney Department,equivalent to 182 patients annually and by 11%in the Oncology Department,equivalent to 150 patients annually.
