The emergency department prediction of disposition (EPOD) study

Impact of emergency department discharge stream short stay unit performance and hospital bed occupancy rates on access and patient flowmeasures: A single site study

“…Adherence to admission criteria in EDSSU is critical key factor in senior ED staff being able to manage ED flows and has been suggested in past literature as a key factor to success of observation units . We found that majority of patients admitted to EDSSU were admitted under ED specialist and the success rate in this group was 90.9%, slightly lower than that found in our past study of early prediction of outcomes at triage …”

“…reported on a concept of predicted outcome based (admission or discharge) patient streaming, while Vaghasiya et al . reported on the reliability of early disposition prediction by triage nurses, registrars and specialists in the ED . In our study, we found that the overall NEAT performance had stronger correlation with discharge NEAT, which reflects that higher proportion of patients who presented to ED were discharged out of hospital.…”

“…King et al reported on a concept of predicted outcome based (admission or discharge) patient streaming, 18 while Vaghasiya et al reported on the reliability of early disposition prediction by triage nurses, registrars and specialists in the ED. 19 In our study, we found that the overall NEAT performance had stronger correlation with discharge NEAT, which reflects that higher proportion of patients who presented to ED were discharged out of hospital. EDs cater for patients with varying acuity and needs while the majority of these patients are discharged, cohorts of discharge suitable patients need varying timelines of stays in ED, extending beyond the statutory 4 h deadline.…”

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

“…Studies are also required to compare model performance against clinician based prediction. One single centre study from Westmead Hospital demonstrated that senior clinicians predicted ED discharge with a positive predictive value of around 0.90 however the positive predictive value for in-patient admission prediction was only around 55% [13]. A study from Queensland used data analytics to predict ED demand based on day of week and previous total ED presentations with the aim of forecasting bed requirements on an administrative level [14].…”

Admission prediction rules: some limited promise, but far from proven

“…A study examining triage nurses’ ability to predict admissions, performed at a single Australian hospital, found a positive predictive value of 48.5%, implying possible room for improvement. (Physicians fared little better) 12. However, Peck et al 8 modelled several admission prediction rules including triage nurse opinion, and did not find drastic differences in performance, while Kim et al 9 found no difference between their rule and triage nurse opinion.…”