Can Triage Nurses Accurately Predict Patient Dispositions in the Emergency Department?

Effect of Emergency Severity Index Annual Competency Assessment on Mistriage

BACKGROUND

There is limited evidence identifying best practices to promote competency of accurate assignment of the Emergency Severity Index (ESI) acuity level to patients who present to the emergency department (ED) triage.

LOCAL PROBLEM

Triage-trained nurses do not receive competency training in an ESI triage tool.

METHODS

A retrospective chart review of 150 patients was completed to evaluate mistriage rates before and after triage-trained nurses completed an ESI competency assessment.

RESULTS

The retrospective chart review showed no statistically significant difference in mistriage from pre- to postintervention (P = .8535).

CONCLUSIONS

Implementation of an ESI annual competency assessment aligns well with an emerging theme in the literature that ED nurses should be provided with ongoing education that reinforces knowledge and implementation of ESI triaging.

Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department

Increasing demand and changing case-mix have resulted in bottlenecks and longer waiting times in emergency departments (ED). However, many process improvement efforts addressing the bottlenecks have limitations, as they lack accurate models of the real system as input accounting for operational complexities. To understand the limitation, this research modelled granular procedural information, to analyse processes in a Level-1 ED of a 1200-bed teaching hospital in the UK. Semi-structured interviews with 21 clinicians and direct observations provided the necessary information. Results identified Majors as the most crowded area, hence, a systems modelling technique, role activity diagram, was used to derive highly granular process maps illustrating care in Majors which were further validated by 6 additional clinicians. Bottlenecks observed in Majors included awaiting specialist input, tests outside the ED, awaiting transportation, bed search, and inpatient handover. Process mapping revealed opportunities for using precedence information to reduce repeat tests; informed alerting; and provisioning for operational complexity into ED processes as steps to potentially alleviate bottlenecks. Another result is that this is the first study to map care processes in Majors, the area within the ED that treats complex patients whose care journeys are susceptible to variations. Findings have implications on the development of improvement approaches for managing bottlenecks.

Prospective comparison of AMB, GAP AND START scores and triage nurse clinical judgement for predicting admission from an ED: a single-centre prospective study

BACKGROUND

It is postulated that early determination of the need for admission can improve flow through EDs. There are several scoring systems which have been developed for predicting patient admission at triage, although they have not been directly compared. In addition, it is not known if these scoring systems perform better than clinical judgement. Therefore, the aim of this study was to validate existing tools in predicting hospital admission during triage and then compare them with the clinical judgement of triage nurses.

METHODS

To conduct this prospective, single-centre observational study, we enrolled consecutive adult patients who presented between 30 September 2019 and 25 October 2019 at the ED of a large teaching hospital in Milan, Italy. For each patient, triage nurses recorded all of the variables needed to perform Ambulatory (AMB), Glasgow Admission Prediction (GAP) and Sydney Triage to Admission Risk Tool (START) scoring. The probability of admission was estimated by the triage nurses using clinical judgement and expressed as a percentage from 0 to 100 with intervals of 5. Nurse estimates were dichotomised for analysis, with ≥50% likelihood being a prediction of admission. Receiver operating characteristic curves were generated for accuracy of the predictions. Area under the curve (AUC) with 95% CI for each of the scores and for the nursing judgements was also calculated.

RESULTS

A total of 1710 patients (844 men; median age, 54 years (IQR: 34-75)) and 35 nurses (15 men; median age, 37 years (IQR: 33-48)) were included in this study. Among these patients, 310 (18%) were admitted to hospital from the ED. AUC values for AMB, GAP and START scores were 0.77 (95% CI: 0.74 to 0.79), 0.72 (95% CI: 0.69 to 0.75) and 0.61 (95% CI: 0.58 to 0.64), respectively. The AUC for nurse clinical judgement was 0.86 (95% CI: 0.84 to 0.89).

CONCLUSION

AMB, GAP and START scores provided moderate accuracy in predicting patient admission. However, all of the scores were significantly worse than the clinical judgement of the triage nurses.

Real-time prediction of patient disposition and the impact of reporter confidence on mid-level triage accuracies: an observational study in Israel

AIM

The emergency department (ED) is the first port-of-call for most patients receiving hospital care and as such acts as a gatekeeper to the wards, directing patient flow through the hospital. ED overcrowding is a well-researched field and negatively affects patient outcome, staff well-being and hospital reputation. An accurate, real-time model capable of predicting ED overcrowding has obvious merit in a world becoming increasingly computational, although the complicated dynamics of the department have hindered international efforts to design such a model. Triage nurses' assessments have been shown to be accurate predictors of patient disposition and could, therefore, be useful input for overcrowding and patient flow models.

METHODS

In this study, we assess the prediction capabilities of triage nurses in a level 1 urban hospital in central Israeli. ED settings included both acute and ambulatory wings. Nurses were asked to predict admission or discharge for each patient over a 3-month period as well as exact admission destination. Prediction confidence was used as an optimisation variable.

RESULT

Triage nurses accurately predicted whether the patient would be admitted or discharged in 77% of patients in the acute wing, rising to 88% when their prediction certainty was high. Accuracies were higher still for patients in the ambulatory wing. In particular, negative predictive values for admission were highly accurate at 90%, irrespective of area or certainty levels.

CONCLUSION

Nurses prediction of disposition should be considered for input for real-time ED models.

Performance of the rapid triage conducted by nurses at the emergency entrance

Objective:

to compare the performance of the rapid triage conducted by nurses at the emergency entrance and of the Manchester Triage System (MTS) in identifying the priority level of care for patients with spontaneous demand and predicting variables related to hospitalization.

Method:

a cross-sectional study carried out in an Emergency Department (ED) of a university hospital in São Paulo. The priority levels established in the rapid triage performed by nurses were high priority (patients of spontaneous demand directed to the emergency room) or low priority (those referred to the institution’s usual flow). Diagnostic accuracy measures were calculated to assess the performance of the indexes.

Results:

of the 173 patients (52.0% female, with mean age of 60.4 ± 21.2 years old) evaluated, it was observed that rapid triage was more inclusive for high priority and had better sensitivity and worse specificity than the MTS. The probability of non-severe patients being admitted to the emergency observation unit was lower due to the rapid triage. For the prediction of the other variables, the systems presented unsatisfactory results.

Conclusion:

the nurses overestimated the classification of patients as high priority, and rapid triage performed better than MTS in predicting admission to the emergency observation unit.

Ability of triage nurses to predict, at the time of triage, the eventual disposition of patients attending the emergency department (ED): a systematic literature review and meta-analysis

Introduction

Exit block is the most significant cause of poor patient flow and crowding in the emergency department (ED). One proposed strategy to reduce exit block is early admission predictions by triage nurses to allow proactive bed management. We report a systematic review and meta-analysis of the accuracy of nurse prediction of admission at triage.

Methodology

We searched MEDLINE, Cochrane, Embase, CINAHL and grey literature, up to and including February 2019. Our criteria were as follows: prospective studies analysing the accuracy of triage nurse intuition—after gathering standard triage information—for predicting disposition for adult ED patients. We analysed the results of this test—nurse prediction of disposition—in a diagnostic test analysis review style, assessing methodology with the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. We generated sensitivity, specificity and likelihood ratios (LRs). We used LRs and pretest probability of admission (baseline admission rate) to find positive and negative post-test probabilities.

Results

We reviewed 10 articles. Of these, seven had meta-analysable data (12 282 participants). The studies varied in participant selection and admission rate, but the majority were of moderate quality and exclusion of each in sensitivity analyses made little difference. Sensitivity was 72% and specificity was 83%. Pretest probability of admission was 29%. Positive and negative post-test probabilities of admission were 63% and 12%, respectively.

Conclusion

Triage nurse prediction of disposition is not accurate enough to expedite admission for ED patients on a one-to-one basis. Future research should explore the benefit, and best method, of predicting total demand.

Validating Service Quality (SERVQUAL) in Healthcare: Measuring Patient Satisfaction Using their Perceptions in Jordan

Patient satisfaction in the developing world has not received sufficient interest in the healthcare literature. More importantly, models predicting patient satisfaction seldom incorporates patient perspectives into their measurement providing ill-suited metrics for healthcare administrators to make decisive decisions concerning service quality improvements. The current analysis utilizes original data collected from 336 patients in Jordan. This paper tests whether service quality (SERVQUAL) is suitable to be used in the new context and concluded that SERVQUAL is reliable and valid in supplying stakeholders with reliable and valid information concerning patient satisfaction. Further, the analysis suggests a large gap between perceived and expected services performed by Jordanian hospitals signalling the need to service quality enhancement. The study calls for the adoption of agile and rapid patient screening models in emergency departments to reduce wait times and decrease the number of patients left without being seen. This study constitutes an emerging attempt at better understanding how service quality influences patient satisfaction, and more importantly, introduce affordable and cost-effective solutions capable of improving satisfaction in the short run.

Development and evaluation of a code frame to identify potential primary care presentations in the hospital emergency department

OBJECTIVE

A major challenge in evaluating the appropriateness of ED presentations is the lack of a universal and workable definition of patients who could have received primary care instead. Our objective was to develop a standardised code frame to identify potential primary care patients in the ED.

METHODS

A standardised code frame to identify which patients could potentially be treated in a primary care setting was developed and tested on all patient episodes of care who presented to the ED of the St George Hospital, Sydney, between December 2016 and February 2017. Sensitivity and specificity of the code frame were performed. The code frame was then tested on all presentations from 2011 to 2016 in the St George Hospital and The Sutherland Hospital in Sydney.

RESULTS

Of 19 916 ED presentations, 5810 (29%) were potential primary care presentations. The code frame had a sensitivity of 99.9% and a specificity of 49.0%. Results were consistent (28%) when applied to 5 years of presentations (601 168 presentations).

CONCLUSION

This standardised code frame enables accurate retrospective local and national data estimations. The code frame could be used prospectively to evaluate interventions such as diverting patients to primary care settings, and to identify populations for specifically targeted interventions. The conservative nature of the code frame ensures that only those that can safely receive care in a primary care setting are identified as potential primary care.