Skip to main navigation menu Skip to main content Skip to site footer

Original article

Vol. 153 No. 5 (2023)

Throughput delays: causes, predictors, and outcomes – observational cohort in a Swiss emergency department

  • Isabelle Arnold
  • Jeannette-Marie Busch
  • Lukas Terhalle
  • Christian H. Nickel
  • Roland Bingisser
Cite this as:
Swiss Med Wkly. 2023;153:40084


BACKGROUND: Optimal throughput times in emergency departments can be adjudicated by emergency physicians. Emergency physicians can also define causes of delays during work-up, such as waiting for imaging, clinical chemistry, consultations, or exit blocks. For adequate streaming, the identification of predictors of delays is important, as the attribution of resources depends on acuity, resources, and expected throughput times.

OBJECTIVE: This observational study aimed to identify the causes, predictors, and outcomes of emergency physician-adjudicated throughput delays.

METHODS: Two prospective emergency department cohorts from January to February 2017 and from March to May 2019 around the clock in a tertiary care centre in Switzerland were investigated. All consenting patients were included. Delay was defined as the subjective adjudication of the responsible emergency physician regarding delay during emergency department work-up. Emergency physicians were interviewed for the occurrence and cause of delays. Baseline demographics, predictor values, and outcomes were recorded. The primary outcome – delay – was presented using descriptive statistics. Univariable and multivariable logistic regression analyses were performed to assess the associations between possible predictors and delays and hospitalization, intensive care, and death with delay.

RESULTS: In 3656 (37.3%) of 9818 patients, delays were adjudicated. The patients with delays were older (59 years, interquartile range [IQR]: 39–76 years vs 49 years, IQR: 33–68 years) and more likely had impaired mobility, nonspecific complaints (weakness or fatigue), and frailty than the patients without delays. The main causes of delays were resident work-up (20.4%), consultations (20.2%), and imaging (19.4%). The predictors of delays were an Emergency Severity Index of 2 or 3 at triage (odds ratio [OR]: 3.00; confidence interval [CI]: 2.21–4.16; OR: 3.25; CI: 2.40–4.48), nonspecific complaints (OR: 1.70; CI: 1.41–2.04), and consultation and imaging (OR: 2.89; CI: 2.62–3.19). The patients with delays had an increased risk for admission (OR: 1.56; CI: 1.41–1.73) but not for mortality than those without delays.

CONCLUSION: At triage, simple predictors such as age, immobility, nonspecific complaints, and frailty may help to identify patients at risk of delay, with the main reasons being resident work-up, imaging, and consultations. This hypothesis-generating observation will allow the design of studies aimed at the identification and elimination of possible throughput obstacles.


  1. Guttmann A, Schull MJ, Vermeulen MJ, Stukel TA. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011 Jun; jun01 1:d2983. 10.1136/bmj.d2983
  2. Di Somma S, Paladino L, Vaughan L, Lalle I, Magrini L, Magnanti M. Overcrowding in emergency department: an international issue. Intern Emerg Med. 2015 Mar;10(2):171–5. 10.1007/s11739-014-1154-8
  3. Camille Stromboni GR. A growing crisis in French emergency rooms. Le Monde. 2022.
  4. Shetty A, Gunja N, Byth K, Vukasovic M. Senior Streaming Assessment Further Evaluation after Triage zone: a novel model of care encompassing various emergency department throughput measures. Emerg Med Australas. 2012 Aug;24(4):374–82. 10.1111/j.1742-6723.2012.01550.x
  5. Forero R, McCarthy S, Hillman K. Access Block and Emergency Department Overcrowding. In: Vincent JL, editor. Annual Update in Intensive Care and Emergency Medicine 2011. Berlin, Heidelberg: Springer Berlin Heidelberg; 2011. pp. 720–8. 10.1007/978-3-642-18081-1_63
  6. Carter EJ, Pouch SM, Larson EL. The relationship between emergency department crowding and patient outcomes: a systematic review. J Nurs Scholarsh. 2014 Mar;46(2):106–15. 10.1111/jnu.12055
  7. Chaou CH, Chen HH, Chang SH, Tang P, Pan SL, Yen AM, et al. Predicting Length of Stay among Patients Discharged from the Emergency Department-Using an Accelerated Failure Time Model. PLoS One. 2017 Jan;12(1)e0165756. 10.1371/journal.pone.0165756
  8. Grossmann FF, Nickel CH, Christ M, Schneider K, Spirig R, Bingisser R. Transporting clinical tools to new settings: cultural adaptation and validation of the Emergency Severity Index in German. Ann Emerg Med. 2011 Mar;57(3)257–64. 10.1016/j.annemergmed.2010.07.021
  9. Sundarapandian V. Probability, Statistics and Queing Theory: PHI Learning; 2009.
  10. Hall R. Patient Flow. Second Edition ed2013. 547 p. 10.1007/978-1-4614-9512-3
  11. Steward D, Glass TF, Ferrand YB. Simulation-Based Design of ED Operations with Care Streams to Optimize Care Delivery and Reduce Length of Stay in the Emergency Department. J Med Syst. 2017 Sep;41(10):162. 10.1007/s10916-017-0804-6
  12. Bingisser R, Nickel CH. The last decade of symptom-oriented research in emergency medicine: triage, work-up, and disposition. Swiss Med Wkly. 2019 Oct;:w20141. 10.4414/smw.2019.20141
  13. Medicine TRCoE. Improving Quality Indicators and System Metrics for Emergency Departments in England. 2019.
  14. Calf AH, Lubbers S, van den Berg AA, van den Berg E, Jansen CJ, van Munster BC, et al. Clinical impression for identification of vulnerable older patients in the emergency department. Eur J Emerg Med. 2020 Apr;27(2):137–41. 10.1097/MEJ.0000000000000632
  15. Grossmann FF, Zumbrunn T, Ciprian S, Stephan FP, Woy N, Bingisser R, et al. Undertriage in older emergency department patients—tilting against windmills? PLoS One. 2014 Aug;9(8)e106203. 10.1371/journal.pone.0106203
  16. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al.; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007 Nov:805–35. 10.1097/EDE.0b013e3181577511
  17. Mason S, Knowles E, Boyle A. Exit block in emergency departments: a rapid evidence review. Emerg Med J. 2017 Jan;34(1):46–51. 10.1136/emermed-2015-205201
  18. Fernandes CM, Tanabe P, Gilboy N, Johnson LA, McNair RS, Rosenau AM, et al. Five-level triage: a report from the ACEP/ENA Five-level Triage Task Force. J Emerg Nurs. 2005 :39–50. 10.1016/j.jen.2004.11.002
  19. Kellett J, Clifford M, Ridley A, Murray A, Gleeson M. A four item scale based on gait for the immediate global assessment of acutely ill medical patients– one look is more than 1000 words. Eur Geriatr Med. 2014;5(2):92–6. 10.1016/j.eurger.2013.11.011
  20. Weigel K, Nickel CH, Malinovska A, Bingisser R. Symptoms at presentation to the emergency department: predicting outcomes and changing clinical practice? Int J Clin Pract. 2018 72(1):e13033. 10.1111/ijcp.13033
  21. Nemec M, Koller MT, Nickel CH, Maile S, Winterhalder C, Karrer C, et al. Patients presenting to the emergency department with non-specific complaints: the Basel Non-specific Complaints (BANC) study. Acad Emerg Med. 2010 Mar;17(3):284–92. 10.1111/j.1553-2712.2009.00658.x
  22. Rueegg M, Nickel CH, Bingisser R. Disagreements between emergency patients and physicians regarding chief complaint - Patient factors and prognostic implications. Int J Clin Pract. 2021 May;75(5):e14070. 10.1111/ijcp.14070
  23. Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005 Aug;173(5):489–95. 10.1503/cmaj.050051
  24. Kuster T, Nickel CH, Jenny MA, Blaschke LL, Bingisser R. Combinations of Symptoms in Emergency Presentations: prevalence and Outcome. J Clin Med. 2019 Mar;8(3):345. 10.3390/jcm8030345
  25. Jenny MA, Hertwig R, Ackermann S, Messmer AS, Karakoumis J, Nickel CH, et al. Are Mortality and Acute Morbidity in Patients Presenting With Nonspecific Complaints Predictable Using Routine Variables? Acad Emerg Med. 2015 Oct;22(10):1155–63. 10.1111/acem.12755
  26. Herzog SM, Jenny MA, Nickel CH, Nieves Ortega R, Bingisser R. Emergency department patients with weakness or fatigue: can physicians predict their outcomes at the front door? A prospective observational study. PLoS One. 2020 Nov;15(11):e0239902. 10.1371/journal.pone.0239902
  27. Kemp K, Mertanen R, Lääperi M, Niemi-Murola L, Lehtonen L, Castren M. Nonspecific complaints in the emergency department - a systematic review. Scand J Trauma Resusc Emerg Med. 2020 Jan;28(1):6. 10.1186/s13049-020-0699-y
  28. Oliver D. ‘Acopia’ and ‘social admission’ are not diagnoses: why older people deserve better. J R Soc Med. 2008 Apr;101(4):168–74. 10.1258/jrsm.2008.080017
  29. Rohacek M, Nickel CH, Dietrich M, Bingisser R. Clinical intuition ratings are associated with morbidity and hospitalisation. Int J Clin Pract. 2015 Jun;69(6):710–7. 10.1111/ijcp.12606
  30. Misch F, Messmer AS, Nickel CH, Gujan M, Graber A, Blume K, et al. Impact of observation on disposition of elderly patients presenting to emergency departments with non-specific complaints. PLoS One. 2014 May;9(5):e98097. 10.1371/journal.pone.0098097
  31. Jones S, Moulton C, Swift S, Molyneux P, Black S, Mason N, et al. Association between delays to patient admission from the emergency department and all-cause 30-day mortality. Emerg Med J. 2022 Mar;39(3):168–73. 10.1136/emermed-2021-211572
  32. Nieves-Ortega R, Brabrand M, Dutilh G, Kellett J, Bingisser R, Nickel CH. Assessment of patient mobility improves the risk stratification of triage with the Emergency Severity Index: a prospective cohort study. Eur J Emerg Med. 2021 Dec;28(6):456–62. 10.1097/MEJ.0000000000000845
  33. Fatovich DM, Hirsch RL. Entry overload, emergency department overcrowding, and ambulance bypass. Emerg Med J. 2003 Sep;20(5):406–9. 10.1136/emj.20.5.406

Most read articles by the same author(s)

1 2 3 > >>