TERN Top Papers January 2023

The effect of a rapid assessment zone on emergency department operations and throughput

The aim of this study was to measure the effects of replacing traditional ED triage with a front-end flow model called the rapid assessment zone on the operational metrics of an emergency department of an urban hospital in the USA. This was a retrospective before and after study carried out at a single site over two six-month periods one year apart. Numbers compared were 43,847 consecutive ED visits were assessed in the pre-intervention period and 44,792 in the post intervention period.

The study found that when the system was in place, there was a statistically significant reduction in median times for ED length of stay (decrease by 15% from 203 to 171 hours), arrival to provider time (decrease by 53% from 28 to 23 minutes) and proportion of patients leaving without being seen (decrease from 3.1% to 0.% of overall presentations). Additional regression analysis concluded that the effects were consistent regardless of number of patients in the department, and across Emergency Severity Index Levels 2 to 5 with effects seen most in the lower severity levels. (Level 1 represents patients requiring immediate life saving intervention).

The new rapid assessment system didn’t require extra staff, however did include an 8 bed expansion which may not be possible in all departments. The authors disclosed possible confounding factors, due to several concurrent improvement projects running in the department which are unaccounted for, as well as a lack of a contemporaneous control.

Bottom Line

The results of this single site study show that a rapid assessment zone, which filters out patients suitable for ambulatory care, could help alleviate some of the initial bottlenecks which drive up patient waiting times.

Reference

Anderson, Jared S et al. The Effect of a Rapid Assessment Zone on Emergency Department Operations and Throughput. Annals of emergency medicine vol. 75,2 (2020): 236-245. doi:10.1016/

Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected data.

This paper examined a large volume of high frequency data from the daily situation reports (Sitreps), hospital episode statistics,and electronic staffing records (ESRs) of 138 major emergency departments (EDs) in England over 90 days from December 2016 to February 2017. The aim was to analyse factors that, after a review of current literature, were felt to be most associated with ED waiting times over 4 hours. Areas considered included hospital factors such as bed occupancy and the ratio of admission to discharge, inpatient types and control variables such as size and staffing of the ED, and attender profiles.

The authors found a positive correlation between higher inpatient bed occupancy and longer ED waiting times. Moreover, this relationship was non linear, with the wait time length accelerating above bed occupancy levels of 92% – a potential tipping point. This was particularly pertinent given the average bed occupancy level in England at the time was 92%. In addition, increased numbers of long stay patients (equal to or over 7 days) was also found to be associated with increased waiting times. The authors posited that ED waiting times may be impacted by both these variables due to access block.

Bottom line

This paper highlights the importance of tackling capacity and flow in the wider hospital, addressing very high bed occupancy levels, and increasing the capacity of local health and social care systems to decrease the time patients spend in the ED.

Reference

Paling, Steven et al. Waiting times in emergency departments: exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency medicine journal : EMJ vol. 37,12 (2020): 781-786. doi:10.1136/emermed-2019-208849

Effect of hospital interventions to improve patient flow on emergency department clinical quality indicators

This is a retrospective study conducted on data from 2015-2018 at Yeovil District hospital looking at the effects of hospital wide interventions upon Emergency Department (ED) Clinical Quality Indicators (CQIs) concerned with patient flow. The interventions were introduced in 2016 and developed in a previous study. They were: prioritising inpatient discharges on Monday mornings, formalised ward visits by head of flow on Tuesdays, review of patients with 14+ day stays on Wednesdays, addressing delayed transfer of care problems on Thursdays, establishing a goal of 30 bed availability for weekends (350 bed hospital), redesign of staffing to facilitate weekend discharges and enhanced ambulatory care capacity deployment.

The clinical quality indicators were: the 4 hour standard, median time to triage and assessment by decision-making clinician, <5% reattendance within 7 days optimising ambulatory care, patient experience and consultant sign off on key presentations.

The results demonstrated a gradual, consistent improvement in meeting the 4 hour standard with 92%.0 vs 97.9% of patients spending less than 4 hours in the ED (p=0.01), despite the rising trend of ED attendances. Median time to triage decreased from 15 to 9 minutes (p0.005) and median time to assessment by a decision-making clinician decreased from 65 to 46 minutes ( p=0.02). Reattendance remained below 5% but also decreased post interventions. Attendance at AEC increased. The ratio of positive vs negative patient feedback increased.

The data set, although from only one hospital, was large, comprising of 160373 patient attendances to ED. But it should be noted that Yeovil is a district hospital, smaller in size to the typical specialist centres. Improvements in CQIs were all significant, except in reattendance and patient feedback. The study authors noted that there was also an increase in staffing, particularly senior decision makers, within ED during the period of the study. However, the CQIs had already begun to improve from the start of intervention measures and the inference has been made that there was a connection between them.

Bottom Line

Generally, this study gives an indication of the likely effectiveness of organisational change on improvement of ED performance against CQIs, not solely putting the responsibility on our already overwhelmed departments.

Reference

Sethi, Simon et al. Effect of hospital interventions to improve patient flow on emergency department clinical quality indicators. Emergency medicine journal : EMJ vol. 37,12 (2020): 787-792. doi:10.1136/

Impact of Point-of-care Testing on Length of Stay of Patients in the Emergency Department: A Cluster-randomized Controlled Study

The study question is Does Point of Care Testing (POCT) in the ED result in reduced waiting times and reduced crowding? The study was undertaken in the ED of Piti-Salptrire University Hospital in Paris. This was a cluster-randomised controlled study with blood test processing randomised to intervention or control in 1 week periods. The intervention involved using POCT for blood analysis; including FBC, U&Es, LFTs within the ED, a trained technician present in the ED 24hrs and three POCT blood analysis machines. Any inconclusive results were sent to the laboratory. Thestudy period was 18 weeks. During control weeks samples were sent to the lab for analysis as per usual practice. The main outcome measure was length of stay in the ED.

During the study period 20,923 patient vistits were analysed for length of stay with equal numbers between groups.Mean length of stay (LOS) for those undergoing blood sampling was reduced by 17 minutes with a wide confidence interval of -34 to +0.6 minutes and was not significant (p=0.06). There was also a non-significant reduction of 9 minutes in mean LOS for all patients. The time to required result of investigation (TTR) was significantly reduced by 51 minutes (95% CI 55 to 48 p<0.001) . Therefore, the study concluded that an extended panel of POCT bloods may not reduce the LOS within the department but did have a significant impact on time to result of required blood test.

Secondary endpoints that were measured were ED crowding, as defined by waiting time to first medical contact and occupancy rate in department at certain points through the day. Overcrowding was defined as occupancy >150% of ED capacity. Neither measure of crowding was found to be significantly affected by POCT. Economic impact and patient satisfaction surveys were also evaluated. Economic impact calculations were rather wide ranging with a possible saving of 7-80 million euros per year. Patient satisfaction was higher during a POCT week compared to a control week. However, patient satisfaction was only measured in 2 weeks out of the 18-week study.

Bottom line

Although it significantly reduced time to receive results introducing more POCT did not have a significant effect on patient length of stay or crowding. it may lead to improved patient experience and cost benefits.

Reference

Hausfater, Pierre et al. Impact of Point-of-care Testing on Length of Stay of Patients in the Emergency Department: A Cluster-randomized Controlled Study. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine vol. 27,10 (2020): 974-983. doi:10.1111/acem.14072

Effects of staff grade, overcrowding and presentations on emergency department performance.

This paper examines the effects of staffing levels by experience and overcrowding on Key Performance Indicators (KPIs) in the Emergency Department at Napean Hospital, Sydney, Australia, over 5 months in 2019. Experience levels were divided into: Fellows of the Australasian College of Emergency Medicine (FACEMs), Non-FACEM Senior Decision Makers (SDMs), and non-SDMs including junior doctors and allied health professionals such as physiotherapists and nurse practitioners. Overcrowding was measured by the total number of patients attending ED each day and the number of admitted patients in the ED at 8am.

The ED KPIs examined for effect were the daily Emergency Treatment Performance (ETP), the daily numbers of patients admitted to inpatient wards, emergency short stay ward (ESSW), discharged from ED, those that left at their own risk, and triage performance. Multiple variable regression modelling was undertaken with daily staffing at each experience level considered among other variables, including overcrowding. . Multiple variable regression analysis uses two or more explanatory variables (e.g. staffing level of experience and overcrowding) to predict the outcome of a response variable (e.g. KPIs).

The findings, maybe predictably, indicated that an increase in senior decision makers, significantly with FACEMs, improved KPIs and overcrowding worsened KPIs. However, non-SDM staffing had minimal impact. The SDMs are involved directly or indirectly in all patients care in the ED and manage patient flow including into EMSS. Junior doctors are supervised by SDMs and this study indicates that an increase in supervision, as well as the other clinical and management skills of FACEMs, improves KPIs over and above increasing the staffing levels of junior doctors. Again predictably, overcrowding had a significant and detrimental effect on KPIs.

Bottom Line

Improving the numbers of senior decision makers improved ED performance as measured by KPIs.

Reference

Mallows, James L. Effects of staff grade, overcrowding and presentations on emergency department performance: A regression model. Emergency medicine Australasia : EMA vol. 34,3 (2022): 341-346. doi:10.1111/1742-6723.13889

Agreement and validity of electronic patient self-triage (eTriage) with nurse triage in two UK

The aim of this study was to assess the agreement and validity of eTriage (an automated digital check in triage solution) with a reference standard of nurse face-to-face triage. A secondary aim was to assess the ability of both systems to predict high and low acuity outcomes.

This was a retrospective study conducted over 8 months in two UK hospitals. Inclusion criteria were all ambulatory patients aged 18. All patients completed an eTriage and nurse-led triage using the Manchester Triage System (MTS).

There were 25 333 paired triages for the final cohort. Agreement between eTriage and nurse triage was low with a weighted Kappa coefficient of 0.14 (95% CI, 0.14-0.15) with an associated weak positive correlation (rs 0.321). Level of undertriage by eTriage compared with nurse triage was 10.1%, and overtriage was 59.2%. The sensitivity for prediction of high acuity outcomes was 88.5% (95% CI, 77.9-95.3%) for eTriage and 53.8% (95% CI 41.1-66.0%) for nurse MTS. The specificity for predicting low risk patients was 88.5% (95% CI, 87.4-89.5%) for eTriage and 80.6% (95% CI, 79.3-81.8%) for nurse MTS. The authors concluded further research is required to explore and validate the eTriage model as a potential tool to re-direct suitable patients to alternative healthcare pathways and its impact on ED crowding.

Bottom Line

There was little correlation between eTriage with the reference standard of nurse MTS. Patients using eTriage tended to over triage when compared to the triage nurse. As a result eTriage had a higher sensitivity for high acuity presentations and demonstrated similar specificity for low acuity presentations when compared to triage nurse MTS.

Reference

Dickson, Sarah J et al. Agreement and validity of electronic patient self-triage (eTriage) with nurse triage in two UK emergency departments: a retrospective study. European journal of emergency medicine : official journal of the European Society for Emergency Medicine vol. 29,1 (2022): 49-55. doi:10.1097/MEJ.0000000000000863

Analysis of time-to-disposition intervals during early and late parts of an emergency department shift.

This study was a retrospective review of 50,802 emergency department attendances to a single urban centre in the USA. The authors hypothesized that providers view the shift end as a key timepoint and attempt to leave as few dispositions as possible to the oncoming team, thereby making quicker decisions later in the shift. This study evaluated disposition distribution relative to when patients are assigned a provider during the course of a shift.

Of the 50,802 Attendances considered, 31,869 were of patients seen in the early half of a shift (hours 1-4) and 18,933 were seen in the later half (hours 5+). The authors ran a linear mixed model that adjusted for age, gender, emergency severity index score, time of day, weekend arrivals, quarter of arrival and shift type.

Median time-to-disposition for the early group was 3.25 h (IQR 1.90-5.04), and 2.62 h (IQR 1.51-4.31) for the late group. The authors conclude that in the later parts of the shift, providers take on average 15.1% less time to make a disposition decision than in the earlier parts of the shift. The authors suggest that this may be influenced by many factors, such as providers spending the early hours of a shift seeing new patients which generate new tasks and delay dispositions and viewing the end of shift as a landmark with a goal to maximize dispositions prior to sign-out.

Bottom Line

Patients picked up during the latter half of a shift were more likely to have a shorter time-to-disposition than similar patients seen in the first half of the same shift. This maybe important when considering ED staffing.

Reference

Stenson, Bryan A et al. Analysis of time-to-disposition intervals during early and late parts of an emergency department shift. The American journal of emergency medicine vol. 50 (2021): 477-480. doi:10.1016/

Delays in antibiotic redosing: Association with inpatient mortality and risk factors for delay.

In light of the increasing burden of boarding in Emergency Departments (ED) and subsequent need to re-dose antibiotic in the ED, the authors wished to examine the association between delayed second antibiotic dose administration and mortality among patients admitted from the ED with a broad array of infections and characterized risk factors.

This was a retrospective cohort study of patients admitted through five EDs in a single healthcare system from throughout 2018. The study included all patients, aged 18 years or older, who received two intravenous antibiotic doses within a 30hr period, with the first dose administered in the ED. Patients with end stage renal disease, cirrhosis and extremes of weight were excluded due to a lack of consensus on antibiotic dosing intervals for these populations. Delay was defined as administration of the second dose at a time-point greater than 125% of the recommended interval. The primary outcome was in-hospital mortality.

A total of 5605 second antibiotic doses, occurring during 4904 visits, met study criteria. Delayed administration of the second dose occurred during 21.1% of visits. After adjustment for patient characteristics, delayed second dose administration was associated with increased odds of in-hospital mortality (OR 1.50, 95%CI 1.05-2.13). Regarding risk factors for delay, every one-hour increase in allowable compliance time was associated with a 18% decrease in odds of delay (OR 0.82 95%CI 0.75-0.88). Other risk factors for delay included ED boarding more than 4 h (OR 1.47, 95%CI 1.27-1.71) or a high acuity presentation as defined by emergency severity index (ESI) (OR 1.54, 95%CI 1.30-1.81 for ESI 1-2 versus 3-5).

Bottom Line

This study shows delays in second antibiotic dose administration were frequent in the ED and early hospital course and were associated with increased odds of in-hospital mortality. ED boarding was associated with increased antibiotic delay.

Reference

Kemmler, Charles B et al. Delays in antibiotic redosing: Association with inpatient mortality and risk factors for delay. The American journal of emergency medicine vol. 46 (2021): 63-69. doi:10.1016/j.ajem.2021.02.058

Non-compliance with a nurses advice to visit the primary care provider: an exploratory secondary analysis of the TRIAGE-trial

The TRIAGE-trial is a Belgian study designed to determine the effectiveness and safety of nurse-led triage that assigns low-risk patients from an ED to the GP. This paper was a secondary analysis looking at the characteristic of patient that refused to attend GP. 599 (76.5%) patients accepted and were seen by the GP, compared to 183 (23.5%) patients who refused and were treated at the ED. 3 nurses had significantly higher refusal rates (52.8% vs 30% ) the authors hypothesized that this was a result of how this was communicated to the patient by those nurses. Patients living closer to hospital were more likely to accept redirection. Interestingly Patient refused redirection less if the ED was quiet. This was though to result from nurses having more time to explain reasons for redirection in calmer way. Patient were also more likely to refuse redirection in the evening when compared to day and night. Refusers cost more in invoicing than acceptors.

Bottom Line

How the reasons for redirection are communicated are an important factor in whether patient’s accept redirection.

Reference

Homburg, Ines et al. Non-compliance with a nurse’s advice to visit the primary care provider: an exploratory secondary analysis of the TRIAGE-trial. BMC health services research vol. 22,1 463. 8 Apr. 2022, doi:10.1186/s12913-022-07904-8

Relationship between emergency department and inpatient occupancy and the likelihood of an emergency admission: a retrospective hospital database study

This was a retrospective cross-section analysis of 13,14942 attendances in 13 hospital in NHS England. The study found that when compared with periods of average occupancy in ED, a patient attending during a period of very high (upper quintile) occupancy was 3.3% less likely (relative risk (RR) 0.967, 95% CI 0.958 to 0.977) to be admitted, whereas a patient arriving at a time of low ED occupancy was 3.9% more likely (RR 1.039 95% CI 1.028 to 1.050) to be admitted. In addition compared with periods of average emergency inpatient occupancy, a patient attending during a period of very high emergency inpatient occupancy was 1.0% less likely (RR 0.990 95% CI 0.980 to 0.999) to be admitted and a patient arriving at a time of very low emergency inpatient occupancy was 0.8% less likely (RR 0.992 95% CI 0.958 to 0.977) to be admitted.

Bottom Line

Admission thresholds are higher when the number of emergency inpatients is particularly high. This may indicate that riskier discharge decisions are taken when beds are full.

Reference

Wyatt, Steven et al. Relationship between emergency department and inpatient occupancy and the likelihood of an emergency admission: a retrospective hospital database study. Emergency medicine journal : EMJ vol. 39,3 (2022): 174-180. doi:10.1136/emermed-2021-211229

When the medium massages perceptions: Personal (vs. public) displays of information reduce crowding perceptions and outsider mistreatment of frontline staff

The authors of this study theorised that providing information for patients/ customers to read while they wait on a personal medium (e.g., a leaflet, a smartphone) reduces their crowding perceptions and mistreatment of frontline staff, compared to providing the same information on a public medium (e.g., poster, wall sign). They confirmed their findings in a field experiment in Emergency Departments (n = 939) and an online experiment simulating a coffee shop (n = 246).

Bottom Line

The media in which we present information on crowding may alter their perception of crowding and how they respond to frontline staff and perceive crowding.

Reference

Reyt, Jean-Nicolas et al. ”When the medium massages perceptions: Personal (vs. public) displays of information reduce crowding perceptions and outsider mistreatment of frontline staff”: Correction. Journal of occupational health psychology, 10.1037/ocp0000336. 14 Jul. 2022, doi:10.1037/ocp0000336