Measuring Emergency Department Acuity

Yiadom, Maame Yaa A. B.; Baugh, Christopher W.; Barrett, Tyler W.; Liu, Xulei; Storrow, Alan B.; Vogus, Timothy J.; Tiwari, Vikram; Slovis, Corey M.; Russ, Stephan; Liu, Dandan

doi:10.1111/acem.13319

Cited by 22 publications

(15 citation statements)

References 17 publications

(32 reference statements)

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“…In past decades, various screening tools have been incorporated into the triage systems to identify patients at a higher risk of clinical deterioration in acute care settings [ 4 , 5 ]. These instruments use physiological parameters, such as vital signs, to measure illness acuity (general level of patient illness, urgency for clinical intervention and intensity of resource utilisation) [ 6 ]. Previous studies have shown that tools such as the National Early Warning Score (NEWS) and the quick Sequential Sepsis-Related Organ Failure Assessment (SOFA) can be used to identify patients with infection who are at a higher risk of mortality in the hospital [ 4 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

A fuller picture of COVID-19 prognosis: the added value of vulnerability measures to predict mortality in hospitalised older adults

et al. 2020

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Background Although COVID-19 disproportionally affects older adults, the use of conventional triage tools in acute care settings ignores the key aspects of vulnerability. Objective This study aimed to determine the usefulness of adding a rapid vulnerability screening to an illness acuity tool to predict mortality in hospitalised COVID-19 patients. Design Cohort study. Setting Large university hospital dedicated to providing COVID-19 care. Participants Participants included are 1,428 consecutive inpatients aged ≥50 years. Methods Vulnerability was assessed using the modified version of PRO-AGE score (0–7; higher = worse), a validated and easy-to-administer tool that rates physical impairment, recent hospitalisation, acute mental change, weight loss, and fatigue. The baseline covariates included age, sex, Charlson comorbidity score, and the National Early Warning Score (NEWS), a well-known illness acuity tool. Our outcome was time-to-death within 60 days of admission. Results The patients had a median age of 66 years, and 58% were male. The incidence of 60-day mortality ranged from 22% to 69% across the quartiles of modified PRO-AGE. In adjusted analysis, compared with modified PRO-AGE scores 0–1 (“lowest quartile”), the hazard ratios (95% CI) for 60-day mortality for modified PRO-AGE scores 2–3, 4, and 5–7, were 1.4 (1.1–1.9), 2.0 (1.5–2.7), and 2.8 (2.1–3.8), respectively. The modified PRO-AGE predicted different mortality risk levels within each stratum of NEWS and improved the discrimination of mortality prediction models. Conclusions Adding vulnerability to illness acuity improved accuracy of predicting mortality in hospitalised COVID-19 patients. Combining tools such as PRO-AGE and NEWS may help stratify the risk of mortality from COVID-19.

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Section: Introductionmentioning

confidence: 99%

A fuller picture of COVID-19 prognosis: the added value of vulnerability measures to predict mortality in hospitalised older adults

et al. 2020

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“…We hypothesize that factors such as time of day; number of active patients on a resident’s list; current National Emergency Department Overcrowding Scale (NEDOCS) score; 32,33 door‐to‐registration time; door‐to‐bed time; door‐to‐physician time; laboratory and imaging turnaround times; transportation times to laboratory, x‐ray, and CT; and location of service within the ED—such as high‐acuity zones, lower‐acuity zones, or fast‐track—may additionally affect the throughput metrics for a given visit and represent possible sources of variability in the outcome measures of the study. We considered controlling for acuity, however Emergency Severity Index (ESI) was the only readily available proxy measure for acuity and has been shown to have only modest correlation with acuity 34 . We therefore elected not to control for ESI because we felt that the additional complexity added to the models outweighed the modest benefit afforded by the ESI’s ability to discriminate acuity.…”

Section: Discussionmentioning

confidence: 99%

“…We considered controlling for acuity, however Emergency Severity Index (ESI) was the only readily available proxy measure for acuity and has been shown to have only modest correlation with acuity. 34 We therefore elected not to control for ESI because we felt that the additional complexity added to the models outweighed the modest benefit afforded by the ESI's ability to discriminate acuity. These unmeasured sources of variability in the endpoints serve as confounders that limit the ability to detect a difference in the control and intervention group.…”

Section: Discussionmentioning

confidence: 99%

Do Automated Reminders for Emergency Department Resident Physicians to Review Their Patient List Improve Efficiency?

Granata

Guillen

Lucero

et al. 2020

AEM Education and Training

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Objectives: Navigating the emergency department (ED) workflow in an efficient manner is an important skill every emergency physician or advanced provider must master. There is a paucity of research into ways to improve how efficiently an ED provider works amid these distractions. This study seeks to determine whether the addition of an hourly automated reminder for resident physicians to review their patient list improves throughput metrics.Methods: This a double-blinded randomized controlled trial in which resident physicians at a single community ED were randomly assigned to two groups: the intervention group, which received automated hourly notifications within the electronic medical record (EMR) to review their patient list for those whose workup is completed, and the control group, which received no notifications. We prospectively analyzed records for 25,255 encounters with 19,264 individual patients seen by 64 residents over the study period. Three-level mixed-effects regression models were used to examine whether notifications improved ED length of stay (ED-LOS), turnaround time to discharge (TAT-D), or turnaround time to admission (TAT-A).Results: There was no statistically significant difference in ED-LOS or TAT-D between groups, but the average TAT-A was 20.00 minutes longer in the intervention group compared to the control group (p < 0.001), after accounting for patient-and resident-specific effects. Secondary analysis demonstrated no statistically significant effect of residency specialty on the effect of notifications on ED-LOS, TAT-D, or TAT-A.Conclusions: Automated hourly notifications within the EMR reminding residents in the ED to review their patient list did not reduce the ED-LOS, TAT-D, or TAT-A. However, the TAT-A was 20.00 minutes longer in the intervention group compared to the control group. It is unclear whether this represents an unintended effect of the automated reminders or is simply a spurious correlation. E fficiency is an important skill all emergency medicine (EM) care providers (doctors and advanced practitioners) must master to successfully manage a busy emergency department (ED). EM care providers work in a fast-paced environment that is characterized by constant interruptions in their duties. 1 Care providers are constantly "task switching," wherein their attention, action, or both are constantly shifting from one task to another. 2,3 This phenomenon has become even more compounded by the advent of the From the

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“…As reflected in our study, a crucial factor which can impact ED waiting times is triage. The primary goal of triage in the emergency department is to facilitate the treatment prioritization of patients based on the urgency of patients’ symptoms and vital signs [23]. Acuity level is an important index used in triage where a lower acuity level equates to less severe symptoms and vital signs.…”

Section: Discussionmentioning

confidence: 99%

Multistate model of the patient flow process in the pediatric emergency department

et al. 2019

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Objectives The main purpose of this paper was to model the process by which patients enter the ED, are seen by physicians, and discharged from the Emergency Department at Nationwide Children’s Hospital, as well as identify modifiable factors that are associated with ED lengths of stay through use of multistate modeling. Methods In this study, 75,591 patients admitted to the ED from March 1 st , 2016 to February 28 th , 2017 were analyzed using a multistate model of the ED process. Cox proportional hazards models with transition-specific covariates were used to model each transition in the multistate model and the Aalen-Johansen estimator was used to obtain transition probabilities and state occupation probabilities in the ED process. Results Acuity level, season, time of day and number of ED physicians had significant and varying associations with the six transitions in the multistate model. Race and ethnicity were significantly associated with transition to left without being seen, but not with the other transitions. Conversely, age and gender were significantly associated with registration to room and subsequent transitions in the model, though the magnitude of association was not strong. Conclusions The multistate model presented in this paper decomposes the overall ED length of stay into constituent transitions for modeling covariate-specific effects on each transition. This allows physicians to understand the ED process and identify which potentially modifiable covariates would have the greatest impact on reducing the waiting times in each state in the model.

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Measuring Emergency Department Acuity

Cited by 22 publications

References 17 publications

A fuller picture of COVID-19 prognosis: the added value of vulnerability measures to predict mortality in hospitalised older adults

A fuller picture of COVID-19 prognosis: the added value of vulnerability measures to predict mortality in hospitalised older adults

Do Automated Reminders for Emergency Department Resident Physicians to Review Their Patient List Improve Efficiency?

Multistate model of the patient flow process in the pediatric emergency department

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