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- MakaleAçık Erişim2020Scopus SJRQ3An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments
Gul, Muhammet; Celik, Erkan
Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of health care in EDs are associated with a number of factors, such as patient overall length of stay (LOS) and admission, prompt ambulance diversion, quick and accurate triage, nurse and physician assessment, diagnostic and laboratory services, consultations and treatment. One of the most important ways to plan the healthcare delivery efficiently is to make forecasts of ED processes. The aim this study is thus to provide an exhaustive review for ED stakeholders interested in applying forecasting methods to their ED processes. A categorisation, analysis and interpretation of 102 papers is performed for review. This exhaustive review provides an insight for researchers and practitioners about forecasting in EDs in terms of showing current state and potential areas for future attempts.
AtıfScopus63WoS54OpenAlex80
İncele - MakaleYalnız künye2020Scopus SJRQ2A multi-method patient arrival forecasting outline for hospital emergency departments
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Patient arrivals at the emergency department (ED) of hospitals has an unpredictable behavior. So that, adequate forecasting of this process can serve a management baseline to better allocate ED human resources and medical equipment. In this paper, a multi-method patient arrival forecasting outline for EDs is developed. The methods followed within this study include single methods as linear regression (LR), autoregressive integrated moving average (ARIMA), artificial neural network (ANN), exponential smoothing and hybrid methods as ARIMA–ANN and ARIMA-LR. As the subject of the study, a private hospital ED case in Turkey is carried out. Data of ED patient arrivals for the year of 2016 was used to set up models. Forecasting performance of the multi-method outline was measured using mean absolute percentage error. The ARIMA–ANN hybrid model is shown to outperform in terms of forecasting accuracy. In order to contribute to the current knowledge, this paper is a novel attempt of applying these methods to model ED patient arrivals and making an overall assessment among them. The results can be used to aid in strategic decision-making on ED staffing and scheduling policy planning in response to predictable arrival variations.
AtıfScopus29WoS26OpenAlex37İncele - MakaleYalnız künye2012Scopus SJRQ2A COMPUTER SIMULATION MODEL TO REDUCE PATIENT LENGTH OF STAY AND TO IMPROVE RESOURCE UTILIZATION RATE IN AN EMERGENCY DEPARTMENT SERVICE SYSTEM
Gul, Muhammet; Guneri, Ali Fuat
This paper presents a case study of a discrete-event simulation (DES) model of an emergency department (ED) unit in a regional university hospital in Turkey. In this paper emergency department operations of the hospital were modeled, analyzed and improved. The goal of the study is to reduce patient average length of stay (LOS) and to improve patient throughput and utilization of locations and human resources (doctors, nurses, receptionists). Some alternative scenarios in an attempt to determine optimal staff level were evaluated. These alternative approaches illustrate that vital improvement in LOS and throughput can be obtained by minor changes in shift hours and number of resources. Considering future changes in patient demand a scenario which reduces LOS and improves throughput is available in the paper. Significance: The Key Performance Indicators (KPIs) to determine and improve system performance in healthcare emergency departments consist of to reduce patient average length of stay (LOS), to improve patient throughput and resource utilization rates. Alternative scenarios and optimal staff levels are enhanced within the scope of this study.
AtıfWoS53İncele