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An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments

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  • Muhammet Gul
  • Erkan Celik

Abstract

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.

Suggested Citation

  • Muhammet Gul & Erkan Celik, 2020. "An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments," Health Systems, Taylor & Francis Journals, vol. 9(4), pages 263-284, October.
    • Handle: RePEc:taf:thssxx:v:9:y:2020:i:4:p:263-284
    DOI: 10.1080/20476965.2018.1547348
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    Cited by:

    1. Jing Chen & Germán G. Creamer & Yue Ning & Tal Ben-Zvi, 2023. "Healthcare Sustainability: Hospitalization Rate Forecasting with Transfer Learning and Location-Aware News Analysis," Sustainability, MDPI, vol. 15(22), pages 1-24, November.

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