OBJECTIVE: Increasing demand to reduce patient waiting times and improve patient flow has led to the introduction of a number of strategies such as fast track and patient streaming. The triage nurse is primarily responsible for identifying suitable patients, based on prediction of likely admission or discharge. The aim of the present study was to explore the accuracy with which triage nurses predict patient disposition. METHODS: Over two separate 1-week periods, triage nurses at two urban tertiary hospitals electronically recorded in real time whether they thought each patient would be admitted or discharged. The patient's ultimate disposition (admission or discharge), age, sex, diagnostic group, triage category and time of arrival were also recorded. RESULTS: In total, 1342 patients were included in the study, of which 36.0% were subsequently admitted. Overall, the triage nurse correctly predicted the disposition in 75.7% of patients (95% CI: 73.2-78.0). Nurses were more accurate at predicting discharge than admission (83.3% vs 65.1%, P = 0.04). Triage nurses were most accurate at predicting admission in patients with higher triage categories and most accurate at predicting discharge in patients with injuries and febrile illnesses (89.6%, 95% CI: 85.6-92.6). Predicted discharge was least accurate for patients with cardiovascular disease, with 41.1% (95% CI: 26.4-57.8) of predicted discharges in this category subsequently requiring admission. CONCLUSION: Triage nurses can accurately predict likely discharge in specific subgroups of ED patients. This supports the role of triage nurses in appropriately identifying patients suitable for 'fast track' or streaming.
OBJECTIVE: Increasing demand to reduce patient waiting times and improve patient flow has led to the introduction of a number of strategies such as fast track and patient streaming. The triage nurse is primarily responsible for identifying suitable patients, based on prediction of likely admission or discharge. The aim of the present study was to explore the accuracy with which triage nurses predict patient disposition. METHODS: Over two separate 1-week periods, triage nurses at two urban tertiary hospitals electronically recorded in real time whether they thought each patient would be admitted or discharged. The patient's ultimate disposition (admission or discharge), age, sex, diagnostic group, triage category and time of arrival were also recorded. RESULTS: In total, 1342 patients were included in the study, of which 36.0% were subsequently admitted. Overall, the triage nurse correctly predicted the disposition in 75.7% of patients (95% CI: 73.2-78.0). Nurses were more accurate at predicting discharge than admission (83.3% vs 65.1%, P = 0.04). Triage nurses were most accurate at predicting admission in patients with higher triage categories and most accurate at predicting discharge in patients with injuries and febrile illnesses (89.6%, 95% CI: 85.6-92.6). Predicted discharge was least accurate for patients with cardiovascular disease, with 41.1% (95% CI: 26.4-57.8) of predicted discharges in this category subsequently requiring admission. CONCLUSION: Triage nurses can accurately predict likely discharge in specific subgroups of ED patients. This supports the role of triage nurses in appropriately identifying patients suitable for 'fast track' or streaming.