The Sydney Triage to Admission Risk Tool (START) to predict Emergency Department Disposition: A derivation and internal validation study using retrospective state-wide data from New South Wales, Australia
Open accessAbstract
BACKGROUND: Disposition decisions are critical to the functioning of Emergency Departments. The objectives of the present study were to derive and internally validate a prediction model for inpatient admission from the Emergency Department to assist with triage, patient flow and clinical decision making. METHODS: This was a retrospective analysis of State-wide Emergency Department data in New South Wales, Australia. Adult patients (age ≥ 16 years) were included if they presented to a Level five or six (tertiary level) Emergency Department in New South Wales, Australia between 2013 and 2014. The outcome of interest was in-patient admission from the Emergency Department. This included all admissions to short stay and medical assessment units and being transferred out to another hospital. Analyses were performed using logistic regression. Discrimination was assessed using area under curve and derived risk scores were plotted to assess calibration. RESULTS: 1,721,294 presentations from twenty three Level five or six hospitals were analysed. Of these 49.38% were male and the mean (sd) age was 49.85 years (22.13). Level 6 hospitals accounted for 47.70% of cases and 40.74% of cases were classified as an in-patient admission based on their mode of separation. The final multivariable model including age, arrival by ambulance, triage category, previous admission and presenting problem had an AUC of 0.82 (95% CI 0.81, 0.82). CONCLUSION: By deriving and internally validating a risk score model to predict the need for in-patient admission based on basic demographic and triage characteristics, patient flow in ED, clinical decision making and overall quality of care may be improved. Further studies are now required to establish clinical effectiveness of this risk score model.
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Logistic regression and Naive Bayes are commonly used, with few studies using more complex algorithms like random-forests, artificial neural networks, and support vector machines.
“Logistic regression and Naive Bayes are commonly used [9,11,16,18–22], with few studies using more complex algorithms like random-forests, artificial neural networks, and support vector machines [12,15,17].”
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A Prediction Rule to Identify Low-Risk Patients with Community-Acquired Pneumonia
Fine, M. J., Auble, T. E., Yealy, D. M., Hanusa, B. H., Weissfeld, L. A., Singer, D. E., Coley, C. M., Marrie, T. J., & Kapoor, W. N. (1997) · New England Journal of Medicine · doi:10.1056/nejm199701233360402 · Cited by 4,560 · see citing works
Garg, A. X., Adhikari, N. K. J., McDonald, H., Rosas-Arellano, M. P., Devereaux, P. J., Beyene, J., Sam, J., & Haynes, R. B. (2005) · JAMA · doi:10.1001/jama.293.10.1223 · Cited by 2,936 · see citing works
Systematic Review of Emergency Department Crowding: Causes, Effects, and Solutions
Hoot, N. R., & Aronsky, D. (2008) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2008.03.014 · Cited by 1,689 · see citing works
Sprivulis, P., Silva, J. D., Jacobs, I. G., Jelinek, G. A., & Frazer, A. R. L. (2006) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2006.tb00203.x · Cited by 760 · see citing works
Sprivulis, P., Silva, J. D., Jacobs, I. G., Frazer, A. R. L., & Jelinek, G. A. (2006) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2006.tb00416.x · Cited by 757 · see citing works
Demand at the emergency department front door: 10‐year trends in presentations
Lowthian, J. A., Curtis, A. J., Jolley, D. J., Stoelwinder, J. U., McNeil, J. J., & Cameron, P. A. (2012) · The Medical Journal of Australia · doi:10.5694/mja11.10955 · Cited by 280 · see citing works
Predicting emergency department admissions
Boyle, J., Jessup, M., Crilly, J. L., Green, D., Lind, J., Wallis, M. C., Miller, P. G., & FitzGerald, G. (2011) · Emergency Medicine Journal · doi:10.1136/emj.2010.103531 · Cited by 149 · see citing works
How do emergency physicians make discharge decisions?
Calder, L. A., Arnason, T., Vaillancourt, C., Perry, J. J., Stiell, I. G., & Forster, A. J. (2013) · Emergency Medicine Journal · doi:10.1136/emermed-2013-202421 · Cited by 112 · see citing works
Generalizability of a Simple Approach for Predicting Hospital Admission From an Emergency Department
Peck, J. S., Gaehde, S. A., Nightingale, D. J., Gelman, D. Y., Huckins, D. S., Lemons, M. F., Dickson, E. W., & Benneyan, J. C. (2013) · Academic Emergency Medicine · doi:10.1111/acem.12244 · Cited by 63 · see citing works
Dinh, M. M. Q., Russell, S. B., Bein, K. J., Chalkley, D. R., Muscatello, D. J., Paoloni, R., & Ivers, R. (2016) · Emergency Medicine Australasia · doi:10.1111/1742-6723.12542 · Cited by 62 · see citing works
Self-citationHodge, A. N., Hugman, A., Varndell, W., & Howes, K. (2013) · Australasian Emergency Nursing Journal · doi:10.1016/j.aenj.2012.12.003 · Cited by 54 · see citing works
Casalino, E., Choquet, C., Bernard, J., Debit, A., Doumenc, B., Berthoumieu, A., & Wargon, M. (2012) · Emergency Medicine Journal · doi:10.1136/emermed-2012-201404 · Cited by 49 · see citing works
Dinh, M. M. Q., Bein, K. J., Latt, M. D., Chalkley, D. R., & Muscatello, D. J. (2014) · Emergency Medicine Journal · doi:10.1136/emermed-2014-204174 · Cited by 28 · see citing works
Self-citationThe emergency department prediction of disposition (EPOD) study
Vaghasiya, M. R., Murphy, M., O’Flynn, D., & Shetty, A. (2014) · Australasian Emergency Nursing Journal · doi:10.1016/j.aenj.2014.07.003 · Cited by 25 · see citing works
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Hong, W. S., Haimovich, A. D., & Taylor, R. A. (2018) · PLOS ONE · doi:10.1371/journal.pone.0201016 · Cited by 326 · see citing works
Sterling, N. W., Patzer, R. E., Di, M., & Schrager, J. D. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.06.008 · Cited by 112 · see citing works
Miles, J., Turner, J., Jacques, R., Williams, J., & Mason, S. M. (2020) · Diagnostic and Prognostic Research · doi:10.1186/s41512-020-00084-1 · Cited by 77 · see citing works
Tahayori, B., Chinniforoush, N., & Akhlaghi, H. (2020) · Emergency Medicine Australasia · doi:10.1111/1742-6723.13656 · Cited by 54 · see citing works
Lee, S.-Y., Chinnam, R. B., Dalkiran, E., Krupp, S., & Nauss, M. D. (2019) · Health Care Management Science · doi:10.1007/s10729-019-09496-y · Cited by 52 · see citing works
Rahman, A., Honan, B., Glanville, T., Hough, P., & Walker, K. (2019) · Emergency Medicine Australasia · doi:10.1111/1742-6723.13421 · Cited by 45 · see citing works
Rendell, K., Koprinska, I., Kyme, A. Z., Ebker‐White, A. A., & Dinh, M. M. Q. (2018) · Emergency Medicine Australasia · doi:10.1111/1742-6723.13199 · Cited by 40 · see citing works
Self-citationKlang, E., Kummer, B. R., Dangayach, N. S., Zhong, A., Kia, A., Timsina, P., Cossentino, I., Costa, A. B., Levin, M. A., & Oermann, E. K. (2021) · Scientific Reports · doi:10.1038/s41598-021-80985-3 · Cited by 38 · see citing works
Patel, D. D., Cheetirala, S. N., Raut, G., Tamegue, J., Kia, A., Glicksberg, B. S., Freeman, R., Levin, M. A., Timsina, P., & Klang, E. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11236888 · Cited by 23 · see citing works
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Kishore, K., Braitberg, G., Holmes, N. E., & Bellomo, R. (2023) · Emergency Medicine Australasia · doi:10.1111/1742-6723.14169 · Cited by 19 · see citing works
Berecki‐Gisolf, J., Darzi, E. R., & Natora, A. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1426726 · Cited by 15 · see citing works
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Kim, E., Han, K. S., Cheong, T., Lee, S. W., Eun, J., & Kim, S. J. (2022) · IEEE Access · doi:10.1109/access.2022.3160742 · Cited by 13 · see citing works
Shin, H. A., Kang, H., & Choi, M. (2025) · Healthcare Informatics Research · doi:10.4258/hir.2025.31.1.23 · Cited by 14 · see citing works
Leonard, F., Gilligan, J., & Barrett, M. J. (2022) · Journal of the American College of Emergency Physicians Open · doi:10.1002/emp2.12779 · Cited by 11 · see citing works
Predictive Models for Emergency Department Triage using Machine Learning: A Systematic Review
Gao, F., Boukebous, B., Pozzar, M., Enora, A., Sano, B., & Bayat, S. (2022) · Obstetrics and Gynecology Research · doi:10.26502/ogr085 · Cited by 11 · see citing works
Ebker‐White, A. A., Bein, K. J., & Dinh, M. M. Q. (2018) · Emergency Medicine Journal · doi:10.1136/emermed-2017-207227 · Cited by 11 · see citing works
Self-citationCurtis, K. A., Dinh, M. M. Q., Shetty, A., Kourouche, S., Fry, M., Considine, J., Li, L., Lung, T. W.-C., Shaw, T. J., Lam, M. K., et al. (2023) · Implementation Science Communications · doi:10.1186/s43058-023-00452-0 · Cited by 11 · see citing works
Self-citationEbker‐White, A. A., Bein, K. J., Russell, S. B., & Dinh, M. M. Q. (2019) · BMC Emergency Medicine · doi:10.1186/s12873-019-0290-x · Cited by 10 · see citing works
Self-citationDrinking from the Holy Grail—Does a Perfect Triage System Exist? And Where to Look for It?
Ingielewicz, A., Rychlik, P., & Siemiński, M. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14060590 · Cited by 9 · see citing works
Afnan, M. A. M., Netke, T., Singh, P., Worthington, H., Ali, F., Kajamuhan, C., & Nagra, A. (2020) · Emergency Medicine Journal · doi:10.1136/emermed-2019-208910 · Cited by 9 · see citing works
Lohan, L., Marin, G., Faucanié, M., Laureau, M., Macioce, V., Périer, D., Pinzani, V., Giraud, I., Castet‐Nicolas, A., Jalabert, A., et al. (2021) · International Journal of Clinical Practice · doi:10.1111/ijcp.14224 · Cited by 7 · see citing works
Salvato, M., Solbiati, M., Bosco, P., Casazza, G., Binda, F., Iotti, M., Calegari, J. G., Laquintana, D., & Costantino, G. (2021) · Emergency Medicine Journal · doi:10.1136/emermed-2020-210814 · Cited by 7 · see citing works
Leonard, F., Gilligan, J., & Barrett, M. J. (2021) · Frontiers in Big Data · doi:10.3389/fdata.2021.643558 · Cited by 5 · see citing works
Hutchinson, C. L., Curtis, K. A., McCloughen, A., Qian, S., Yu, P., & Fethney, J. (2021) · Australasian Emergency Care · doi:10.1016/j.auec.2021.04.003 · Cited by 5 · see citing works
Song, L., Aickelin, U., Fazio, T. N., Sharma, A., Kouhounestani, M., Plumb, S., & Putland, M. (2025) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2024-101152 · Cited by 4 · see citing works
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Mueller, O. S., Rentsch, K., Nickel, C. H., & Bingisser, R. M. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10050939 · Cited by 4 · see citing works
Crilly, J. L., Bartlett, D., Sladdin, I., Pellatt, R. A. F., Young, J. T., Ham, W. H. W., & Porter, L. E. (2022) · Collegian Journal of the Royal College of Nursing Australia · doi:10.1016/j.colegn.2022.03.002 · Cited by 4 · see citing works
Alahmary, K. A., Kadasah, S., Alsulami, A., Alshehri, A., Alsalamah, M. A., & Da’ar, O. B. (2023) · Healthcare · doi:10.3390/healthcare11050667 · Cited by 4 · see citing works
Zahid, M., Khan, A. A., Ata, F., Yousaf, Z., Naushad, V. A., Purayil, N. K., Chandra, P., Singh, R., Kartha, A. B., Elzouki, A.-N. Y., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0293140 · Cited by 4 · see citing works
Crilly, J. L., Sweeny, A. L., Athlin, Å. M., Green, D., Malyon, L., Christofis, L., Higgins, M., Källberg, A.-S., Dellner, S., Myrelid, Å., et al. (2024) · BMC Health Services Research · doi:10.1186/s12913-023-09403-w · Cited by 3 · see citing works
Russell, S. B., Seimon, R. V., Dixon, E., Murphy, M., Vukasovic, M., Bohlken, N., Taylor, S., Cooper, Z., Scruton, J., Jain, N. K., et al. (2024) · BMC Emergency Medicine · doi:10.1186/s12873-024-00956-5 · Cited by 2 · see citing works
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Uhl, L., Augusto, V., Lemaire, V., Alexandre, Y., Jardinaud, F., Bercelli, P., & Aloui, S. (2022) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata55660.2022.10020777 · Cited by 2 · see citing works
Raven, W., de Hond, A., Vermeire, J., Schinkelshoek, L., Mulder, L., van Someren, A., Gaakeer, M. I., de Jonge, E., & de Groot, B. (2026) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2026.106446 · Cited by 2 · see citing works
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Service Delivery Innovation in Health Care for Patient Satisfaction at Primary and Secondary Level
Grang, H. K., Bhuiyan, M., Prasad, P. W. C., Haque, F., & Elchouemi, A. (2019) · American Journal of Applied Sciences · doi:10.3844/ajassp.2019.33.42
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Girija, N. H., Aravind, R., & Rani, K. S. (2020) · Journal of Emerging Technologies and Innovative Research
Dinh, M. M. Q., Bein, K. J., Alkhouri, H., Bhraonáin, S. N., & Seimon, R. V. (2023) · Emergency Medicine Australasia · doi:10.1111/1742-6723.14183
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Ramadarsan, M. (2020) · International Journal of Circuit Computing and Networking · doi:10.33545/27075923.2020.v1.i1a.7
Curtis, K., Dinh, M. M. Q., Shetty, A., Kourouche, S., Fry, M., Considine, J., Li, L., Lung, T. W.-C., Shaw, T. J., Lam, M. K., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23550242
Self-citationCurtis, K., Dinh, M. M. Q., Shetty, A., Kourouche, S., Fry, M., Considine, J., Li, L., Lung, T. W.-C., Shaw, T. J., Lam, M. K., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23550236
Self-citationCurtis, K., Dinh, M. M. Q., Shetty, A., Kourouche, S., Fry, M., Considine, J., Li, L., Lung, T. W.-C., Shaw, T. J., Lam, M. K., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23550239
Self-citationCrilly, J. L., Sweeny, A. L., Athlin, Å. M., Green, D., Malyon, L., Christofis, L., Higgins, M., Källberg, A.-S., Dellner, S., Myrelid, Å., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26684682
Russell, S. B., Seimon, R. V., Dixon, E., Murphy, M., Vukasovic, M., Bohlken, N., Taylor, S., Cooper, Z., Scruton, J., Jain, N. K., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26690536
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Self-citationIbrahim, A. A., Darwish, S. S., Abualruz, H., Alzoubi, M. M., Al‐Mugheed, K., Alabdullah, A. A. S., Abdelaliem, S. M. F., & Lasheen, A. F. (2026) · African Journal of Emergency Medicine · doi:10.1016/j.afjem.2026.100972
Franklin, C., Carter, B., Taylor-Robinson, D. C., & Carrol, E. D. (2026) · BMJ Public Health · doi:10.1136/bmjph-2025-002916
- Authors
- Dinh, M. M., Russell, S. B., Bein, K. J., Rogers, K., Muscatello, D., Paoloni, R., Hayman, J., Chalkley, D. R., & Ivers, R.
- Affiliations
- The University of Sydney (AU)
- Royal Prince Alfred Hospital (AU)
- UNSW Sydney (AU)
- Corresponding author
- Dinh, Michael M.
- Venue
- BMC Emergency Medicine
- Published
- 2016-12
- Volume
- 16
- Issue
- 1
- Pages
- 46-46
- ISSN
- 1471-227X (ISSN-L)
- PMC
- PMC5135778
- OpenAlex
- W2559485670
- Cited by
- 47
- References
- 14
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 6 · 2023: 9 · 2022: 6 · 2021: 6 · 2020: 5 · 2019: 5 · 2018: 5
- FWCI
- 4.41
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Emergency Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OPUS - Open Publications of UTS Scholars (University of Technology Sydney) (submittedVersion, other-oa)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Funders
- NSW Ministry of Health
- Topics
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Health Sciences › Medicine › Emergency Medicine › Trauma and Emergency Care Studies
- Health Sciences › Medicine › Emergency Medicine › Hospital Admissions and Outcomes
- Keywords
- emergency department disposition, risk scoring, emergency department triage, patient flow, ambulance arrival, triage categories, previous hospital admissions
- MeSH terms
- Clinical Decision-Making, Adolescent, Adult, Aged, Aged, 80 and over, Emergency Service, Hospital, Female, Humans, Male, Middle Aged, Models, Theoretical, New South Wales, Patient Admission, Retrospective Studies, Triage, Reproducibility of Results, Logistic Models, Risk Assessment, Young Adult
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