Streaming by case complexity: evaluation of a model for emergency department fast track
Abstract
Objectives: To evaluate a patient flow streaming system within a teaching hospital's ED, using functional principles to separate patients into two streams on the basis of complexity rather than acuity, severity or disposition. Methods: The project used conceptual principles, such as patient complexity and ‘lean thinking’ theory, to create a new Fast Track patient stream, which was separately resourced. Data collected before and after implementation of the Fast Track system were analysed to evaluate the system. Results: Following implementation of the system, significant improvements were observed in several key ED performance indicators. Mean waiting time was reduced from 55 to 32 min, mean treatment time was reduced from 209 to 191 min, compliance with New South Wales Department of Health waiting‐time benchmarks increased from 59% to 77% and the percentage of patients who did not wait to complete their treatment halved from 6.2% to 3.1%. Conclusions: Key features in the success of the system included use of dedicated senior staff for Fast Track patients, and quarantining of clinical resources. The ED aiming to improve their waiting times and throughput should consider using complexity as a key criterion for triaging patients into separate streams. A low‐complexity patient stream in the ED provides an ideal focus for advanced nursing practice.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Lean implementation in reviewed emergency departments was associated with decreased waiting time to be seen.
“Decreased waiting time to be seen [ 72 ] [ 77 ] [ 79 ] [ 80 ] [ 81 ]”
From Lean Thinking in Emergency Departments: A Critical Review (2011) · cites this paper as [77]
Cites
Redesigning emergency department patient flows: application of Lean thinking to health care
King, D. L., Ben‐Tovim, D. I., & Bassham, J. (2006) · Emergency Medicine Australasia · doi:10.1111/j.1742-6723.2006.00872.x · Cited by 279 · see citing works
Improving emergency department efficiency by patient streaming to outcomes-based teams
Kelly, A.-M., Bryant, M., Cox, L., & Jolley, D. (2007) · Australian Health Review · doi:10.1071/ah070016 · Cited by 124 · see citing works
Terris, J., Leman, P., O’Connor, N., & Wood, R. (2004) · Emergency Medicine Journal · doi:10.1136/emj.2002.003913 · Cited by 100 · see citing works
Impact of streaming “fast track” emergency department patients
O'Brien, D., Williams, A., Blondell, K., & Jelinek, G. A. (2006) · Australian Health Review · doi:10.1071/ah060525 · Cited by 82 · see citing works
(2002) · Emergency Medicine Australasia · doi:10.1046/j.1442-2026.2002.00371.x · Cited by 75 · see citing works
Triage nurses validly and reliably estimate emergency department patient complexity
Vance, J., & Sprivulis, P. (2005) · Emergency Medicine Australasia · doi:10.1111/j.1742-6723.2005.00761.x · Cited by 37 · see citing works
The identification of costs associated with emergency department attendances
Erwich‐Nijhout, M. A., Bond, M. J., Phillips, D. G., et al. (1997) · Emergency Medicine Australasia · doi:10.1111/j.1442-2026.1997.tb00386.x · Cited by 22 · see citing works
Pilot study of metropolitan emergency department workload complexity
Sprivulis, P. (2004) · Emergency Medicine Australasia · doi:10.1111/j.1742-6723.2004.00558.x · Cited by 13 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Lean Thinking in Emergency Departments: A Critical Review
Holden, R. J. (2011) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2010.08.001 · Cited by 516 · see citing works
Optimizing Emergency Department Front-End Operations
Wiler, J. L., Gentle, C., Halfpenny, J. M., Heins, A., Mehrotra, A., Mikhail, M. G., & Fite, D. (2010) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2009.05.021 · Cited by 339 · see citing works
Kaushal, A., Zhao, Y., Peng, Q., Strome, T., Weldon, E., Zhang, M., & Chochinov, A. (2015) · Socio-Economic Planning Sciences · doi:10.1016/j.seps.2015.02.002 · Cited by 74 · see citing works
- Authors
- Ieraci, S., Digiusto, E., Sonntag, P., Dann, L., & Fox, D.
- Affiliations
- UNSW Sydney (AU)
- Corresponding author
- Ieraci, Susan
- Venue
- Emergency Medicine Australasia
- Publisher
- Wiley
- Published
- 2008-05-06
- Volume
- 20
- Issue
- 3
- Pages
- 241-249
- ISSN
- 1035-6851 (ISSN-L)
- 1742-6731
- 1742-6723
- OpenAlex
- W2123587276
- Cited by
- 106
- References
- 8
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 7 · 2020: 8 · 2019: 8 · 2018: 5 · 2017: 3 · 2016: 4 · 2015: 17 · 2014: 11 · 2013: 6 · 2012: 12
- FWCI
- 5.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Emergency Medicine Australasia (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
- Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
- Keywords
- emergency department, patient flow, fast tracking, patient complexity, triage, lean thinking, waiting time, treatment duration, ED throughput, advanced practice nursing
- MeSH terms
- Adult, Emergency Service, Hospital, Female, Health Services Accessibility, Health Services Needs and Demand, Humans, Male, Middle Aged, Models, Theoretical, New South Wales, Quality of Health Care, Waiting Lists, Models, Organizational
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
