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Analysis of factors influencing length of stay in the emergency department

Published online by Cambridge University Press:  21 May 2015

Philip Yoon ,
Ivan Steiner  and
Gilles Reinhardt
Philip Yoon*
Affiliation:
Division of Emergency Medicine and Department of Family Medicine, University of Alberta, Edmonton, Alta
Ivan Steiner
Affiliation:
Division of Emergency Medicine and Department of Family Medicine, University of Alberta, Edmonton, Alta
Gilles Reinhardt
Affiliation:
Department of Management, College of Commerce, DePaul University, Chicago, Ill.
*
Division of Emergency Medicine, University of Alberta Hospital, 8440 — 112 St., Edmonton AB T6G 2B7; 780 407-7047, fax 780 407-3314;[email protected]

Abstract

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Objectives:

Length of stay (LOS) is a key measure of emergency department (ED) throughput and a marker of overcrowding. Time studies that assess key ED processes will help clarify the causes of patient care delays and prolonged LOS. The objectives of this study were to identify and quantify the principal ED patient care time intervals, and to measure the impact of important service processes (laboratory testing, imaging and consultation) on LOS for patients in different triage levels.

Methods:

In this retrospective review, conducted at a large urban tertiary care teaching hospital and trauma centre, investigators reviewed the records of 1047 consecutive patients treated during a continuous 7-day period in January 1999. Key data were recorded, including patient characteristics, ED process times, tests performed, consultations and overall ED LOS. Of the 1047 patient records, 153 (14.6%) were excluded from detailed analysis because of incomplete documentation. Process times were determined and stratified by triage level, using the Canadian Emergency Department Triage and Acuity Scale (CTAS). Multiple linear regression analysis was performed to determine which factors were most strongly associated with prolonged LOS.

Results:

Patients in intermediate triage Levels III and IV generally had the longest waiting times to nurse and physician assessment, and the longest ED lengths of stay. CTAS triage levels predicted laboratory and imaging utilization as well as consultation rate. The use of diagnostic imaging and laboratory tests was associated with longer LOS, varying with the specific tests ordered. Specialty consultation was also associated with prolonged LOS, and this effect was highly variable depending on the service consulted.

Conclusions:

Triage level, investigations and consultations are important independent variables that influence ED LOS. Future research is necessary to determine how these and other factors can be incorporated into a model for predicting LOS. Improved information systems will facilitate similar ED time studies to assess key processes, lengths of stay and clinical efficiency.

Keywords

emergency departmentlength of stayCanadian Emergency Department Triage and Acuity ScaleCTAS
Type
ED Administration • L’administration de la MU
Information
Canadian Journal of Emergency Medicine , Volume 5 , Issue 3 , May 2003 , pp. 155 - 161
Copyright
Copyright © Canadian Association of Emergency Physicians 2003

References

1.Schull, MJ, Slaughter, PM, Redelmeier, DA.Urban emergency department overcrowding: defining the problem and eliminating misconceptions. CJEM 2002;4(2):76–83.CrossRefGoogle ScholarPubMed
2.Canadian Association of Emergency Physicians and National Emergency Nurses Affiliation. Joint position statement on emergency department overcrowding. CJEM 2001;3(2):82–4.CrossRefGoogle Scholar
3.Stock, LM, Bradley, GE, Lewis, RJ, Baker, DW, Sipsey, J, Stevens, CD.Patients who leave emergency departments without being seen by a physician: magnitude of the problem in Los Angeles County. Ann Emerg Med 1994;23:294–8.CrossRefGoogle ScholarPubMed
4.Fernandes, CM, Price, A, Christenson, JM.Does reduced length of stay decrease the number of emergency department patients who leave without seeing a physician? J Emerg Med 1997;15: 397–9.CrossRefGoogle ScholarPubMed
5.Davis, B, Sullivan, S, Levine, A, Dallara, J.Factors affecting ED length-of-stay in surgical critical care patients. Am J Emerg Med 1995;13(5):495–500.CrossRefGoogle ScholarPubMed
6.Lau, FL, Leung, KP.Waiting time in an urban accident and emergency department — a way to improve it. J Accid Emerg Med 1997;14(5):299–301;302–3.CrossRefGoogle Scholar
7.Fromm, RE, Gibbs, LR, McCallum, WG, Niziol, C, Babcock, JC, Gueler, AC, et al. Critical care in the emergency department: a time-based study. Crit Care Med 1993;21:970–6.Google Scholar
8.Saunders, CE.Time study of patient movement through the emergency department: sources of delay in relation to patient acuity. Ann Emerg Med 1987;16:1244–8.CrossRefGoogle ScholarPubMed
9.Bankhead, C.Re-engineering the ED reduces waits and increases patient satisfaction. Emerg Med News 1997;19:74–5.Google Scholar
10.Shea, SS, Senteno, J.Emergency department patient throughput: a continuous quality improvement approach to length of stay. J Emerg Nurs 1994;20:355–60.Google ScholarPubMed
11.Fernandes, CMB, Christenson, JM, Price, A.Continuous quality improvement reduce length of stay for fast-track patients in an emergency department. Acad Emerg Med 1996;3:258–63.CrossRefGoogle ScholarPubMed
12.Fernandes, CMB, Christenson, JM.Use of continuous quality improvement to facilitate patient flow through the triage and fast-track areas of an emergency department. J Emerg Med 1995;13:847–55.CrossRefGoogle ScholarPubMed
13.Ramsey, FE. Enhancing patient flow. In: Hellstern, RA, editor. Managing the emergency department: a team approach. Dallas: American College of Emergency Physicians; 1992. p. 95–104.Google Scholar
14.Kyriacou, DN, Ricketts, V, Dyne, PL, McCollough, MD, Talan, DA.A 5-year time study analysis of emergency department patient care efficiency. Ann Emerg Med 1999;34:326–35.Google Scholar
15.Rayner, H.Length of stay. Taking a day off. Health Serv J 1998;108:32–3.Google Scholar
16.Beveridge, R, Clarke, B, Janes, L, Savage, N, Thompson, J, Dodd, G, et al. Canadian emergency department triage and acuity scale: implementation guidelines. CJEM 1999;1(3 suppl).Google Scholar
17.Simon, HK, McLario, D, Daily, R, Lanese, C, Castillo, J, Wright, J. “Fast tracking” patients in an urban pediatric emergency department. Am J Emerg Med 1996;14:242–4.CrossRefGoogle Scholar
18.Pinedo, M.Scheduling: theory, algorithms, and systems. Englewood Cliffs: Prentice-Hall; 1995.Google Scholar
19.Purnell, L.Reducing waiting time in emergency department triage. Nurs Manag 1995;26:64Q.Google ScholarPubMed
20.Cardello, D.Monitoring staffing variances and length of stay. Nurs Manag 1995;26:38.CrossRefGoogle ScholarPubMed
21.Bazarian, JJ, Schneider, SM, Newman, VJ, Chodosh, J.Do admitted patients held in the emergency department impact the throughput of treat-and-release patients? Acad Emerg Med 1996;3:1113–8.CrossRefGoogle ScholarPubMed
22.Braly, D.Seek alternatives via simulation software. Health Manag Technol 1995;16:13–6.Google ScholarPubMed
23.Saunders, CE, Makens, PK, Leblanc, LJ.Modeling emergency department operations using advanced computer simulation systems. Ann Emerg Med 1989;18:134–40.Google Scholar