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Using demand analysis and system status management for predicting ED attendances and rostering.
Am J Emerg Med. 2009 Jan; 27(1):16-22.AJ

Abstract

INTRODUCTION

It has been observed that emergency department (ED) attendances are not random events but rather have definite time patterns and trends that can be observed historically.

OBJECTIVES

To describe the time demand patterns at the ED and apply systems status management to tailor ED manpower demand.

METHODS

Observational study of all patients presenting to the ED at the Singapore General Hospital during a 3-year period was conducted. We also conducted a time series analysis to determine time norms regarding physician activity for various severities of patients.

RESULTS

The yearly ED attendances increased from 113387 (2004) to 120764 (2005) and to 125773 (2006). There was a progressive increase in severity of cases, with priority 1 (most severe) increasing from 6.7% (2004) to 9.1% (2006) and priority 2 from 33.7% (2004) to 35.1% (2006). We noticed a definite time demand pattern, with seasonal peaks in June, weekly peaks on Mondays, and daily peaks at 11 to 12 am. These patterns were consistent during the period of the study. We designed a demand-based rostering tool that matched doctor-unit-hours to patient arrivals and severity. We also noted seasonal peaks corresponding to public holidays.

CONCLUSION

We found definite and consistent patterns of patient demand and designed a rostering tool to match ED manpower demand.

Authors+Show Affiliations

Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore. Electronic address: marcus.ong.e.h@sgh.com.sg.Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.Service Operations Department, Singapore General Hospital, Singapore.Richmond Ambulance Authority, Virginia, USA.Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

19041529

Citation

Ong, Marcus Eng Hock, et al. "Using Demand Analysis and System Status Management for Predicting ED Attendances and Rostering." The American Journal of Emergency Medicine, vol. 27, no. 1, 2009, pp. 16-22.
Ong MEH, Ho KK, Tan TP, et al. Using demand analysis and system status management for predicting ED attendances and rostering. Am J Emerg Med. 2009;27(1):16-22.
Ong, M. E. H., Ho, K. K., Tan, T. P., Koh, S. K., Almuthar, Z., Overton, J., & Lim, S. H. (2009). Using demand analysis and system status management for predicting ED attendances and rostering. The American Journal of Emergency Medicine, 27(1), 16-22. https://doi.org/10.1016/j.ajem.2008.01.032
Ong MEH, et al. Using Demand Analysis and System Status Management for Predicting ED Attendances and Rostering. Am J Emerg Med. 2009;27(1):16-22. PubMed PMID: 19041529.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Using demand analysis and system status management for predicting ED attendances and rostering. AU - Ong,Marcus Eng Hock, AU - Ho,Khoy Kheng, AU - Tan,Tiong Peng, AU - Koh,Seoh Kwee, AU - Almuthar,Zain, AU - Overton,Jerry, AU - Lim,Swee Han, PY - 2007/12/12/received PY - 2008/01/07/revised PY - 2008/01/07/accepted PY - 2008/12/2/pubmed PY - 2009/1/3/medline PY - 2008/12/2/entrez SP - 16 EP - 22 JF - The American journal of emergency medicine JO - Am J Emerg Med VL - 27 IS - 1 N2 - INTRODUCTION: It has been observed that emergency department (ED) attendances are not random events but rather have definite time patterns and trends that can be observed historically. OBJECTIVES: To describe the time demand patterns at the ED and apply systems status management to tailor ED manpower demand. METHODS: Observational study of all patients presenting to the ED at the Singapore General Hospital during a 3-year period was conducted. We also conducted a time series analysis to determine time norms regarding physician activity for various severities of patients. RESULTS: The yearly ED attendances increased from 113387 (2004) to 120764 (2005) and to 125773 (2006). There was a progressive increase in severity of cases, with priority 1 (most severe) increasing from 6.7% (2004) to 9.1% (2006) and priority 2 from 33.7% (2004) to 35.1% (2006). We noticed a definite time demand pattern, with seasonal peaks in June, weekly peaks on Mondays, and daily peaks at 11 to 12 am. These patterns were consistent during the period of the study. We designed a demand-based rostering tool that matched doctor-unit-hours to patient arrivals and severity. We also noted seasonal peaks corresponding to public holidays. CONCLUSION: We found definite and consistent patterns of patient demand and designed a rostering tool to match ED manpower demand. SN - 1532-8171 UR - https://www.unboundmedicine.com/medline/citation/19041529/Using_demand_analysis_and_system_status_management_for_predicting_ED_attendances_and_rostering_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0735-6757(08)00111-3 DB - PRIME DP - Unbound Medicine ER -