Impact of Emergency Department Crowding on Discharged Patient Experience

Yosef Berlyand, MD; Martin S. Copenhaver, PhD; Benjamin A. White, MD; Sayon Dutta, MD; Joshua J. Baugh, MD, MPP, MHCM; Susan R. Wilcox, MD; Brian J. Yun, MD, MBA, MPH; Ali S. Raja, MD, MBA, MPH; Jonathan D. Sonis, MD, MHCM

Disclosures

Western J Emerg Med. 2023;24(2):185-192.

Abstract and Introduction

Abstract

Introduction: While emergency department (ED) crowding has deleterious effects on patient care outcomes and operational efficiency, impacts on the experience for patients discharged from the ED are unknown. We aimed to study how patient-reported experience is affected by ED crowding to characterize which factors most impact discharged patient experience.

Methods: This institutional review board-exempt, retrospective, cohort study included all discharged adult ED patients July 1, 2020–June 30, 2021 with at least some response data to the the National Research Corporation Health survey, sent to most patients discharged from our large, academic medical center ED. Our query yielded 9,401 unique encounters for 9,221 patients. Based on responses to the summary question of whether the patient was likely to recommend our ED, patients were categorized as "detractors" (scores 0–6) or "non-detractors" (scores 7–10). We assessed the relationship between census and patient experience by 1) computing percentage of detractors within each care area and assessing for differences in census and boarder burden between detractors and non-detractors, and 2) multivariable logistic regression assessing the relationship between likelihood of being a detractor in terms of the ED census and the patient's last ED care area. A second logistic regression controlled for additional patient- and encounter-specific covariates.

Results: Survey response rate was 24.8%. Overall, 13.9% of responders were detractors. There was a significant difference in the average overall ED census for detractors (average 3.70 more patients physically present at the time of arrival, 95% CI 2.33–5.07). In unadjusted multivariable analyses, three lower acuity ED care areas showed statistically significant differences of detractor likelihood with changes in patient census. The overall area under the curve (AUC) for the unadjusted model was 0.594 (CI 0.577–0.610). The adjusted model had higher AUC (0.673, CI 0.657–.690]; P<0.001), with the same three care areas having significant differences in detractor likelihood based on patient census changes. Length of stay (OR 1.71, CI 1.50–1.95), leaving against medical advice/without being seen (OR 5.15, CI 3.84–6.89), and the number of ED care areas a patient visited (OR 1.16, CI 1.01–1.33) was associated with an increase in detractor likelihood.

Conclusion: Patients arriving to a crowded ED and ultimately discharged are more likely to have negative patient experience. Future studies should characterize which variables most impact patient experience of discharged ED patients.

Introduction

Emergency department (ED) crowding continues to be a major challenge in the United States, with important ramifications for patient experience, care quality, and staff experience.^[1–9] Crowding has been shown to have deleterious effects on patient care outcomes and operational efficiency.^[4,6,8–17] There have been numerous efforts to mitigate ED crowding such as leveraging alternative pathways to avoid hospital admissions, creation of full-capacity protocols to increase inpatient availability of beds, opening of nearby urgent care centers to offload low-acuity volume, and protocols triggering reductions in outside hospital transfers, direct admissions, and elective procedures.^[18–28]

While ED crowding has multiple negative operational impacts, the impact on patient experience for ED patients who are ultimately discharged has not been well studied. While long waits and throughput times have been shown to negatively impact experience, the aspects of crowding that most directly impact the experience of discharged ED patients are poorly understood. Several methods for modeling ED crowding have been previously used including index functions taking into account multiple variables,^{[11,14,29–31]} and simple measures such as the ED occupancy rate,^[32] boarder burden in the ED,^[8] or the number of concurrent ED arrivals, but none have been shown to impact patient experience.^[16,33]

A boarding inpatient in the ED ("boarder") is frequently defined as a patient who remains in the ED more than two hours after an inpatient bed request has been placed.^[8] Boarding inpatients occupy space and use scarce resources including nursing and clinician bandwidth that would otherwise be used for evaluation of new ED patients. A prior study from our ED found that increased inpatient boarders resulted in an increased length of stay (LOS) for patients who were discharged from the ED, demonstrating a negative impact of boarding on even low-acuity patients.^[15]

It is not known whether the operational impacts of crowding result in a worsened patient experience for patients discharged from the ED. We aimed to study how patient-reported experience is affected by ED crowding as measured by the ED census and boarder burden to better characterize which factors most impact discharged patient experience. We hypothesized that worsened ED crowding negatively impacts patient experience for patients discharged from the ED.

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Table 1. Description of emergency department care areas.
Care area	Brief description
A	Care area for rapid clinician assessment and intervention for patients not requiring higher acuity resources.
B	Care area for continuation of care for patients initially evaluated in Care Area A who are able to sit in this internal waiting space while awaiting testing results and/or consultation. There are a limited number of curtained bed spaces that can be used to care for non-ambulatory patients or boarding inpatients.
C	Care area for patients with a single-system complaint and without need for continuous monitoring.
D	Care area for low-acuity, ambulatory patients with single-system complaints that do not require monitoring. Primary focuses include stable orthopedic evaluations and minor procedures such as laceration repairs and abscess drainages.
E	Care area for Intermediate acuity patients with cardiopulmonary monitoring capabilities. Patients are not hemodynamically unstable and do not require immediate resuscitation capabilities.
F	Care area for major resuscitation of the highest acuity patients.
G	Care area for patients under the age of 22 who are behaviorally appropriate and do not require the resuscitation capabilities of Care Area F.
H	Emergency department observation unit designed for the continuation of care for patients with an expected length of stay less than 48 hours.

Table 2. Summary statistics on survey response and average number of patients (and boarders) at the time of a patient's arrival to their last care area.*
Last care area	Number of encounters with survey data (percent of total)	Detractor percentage	Average number of patients in area (SD)	Difference in area patient census means (SE)	Average number of boarders in area (SD)	Difference in area boarder means (SE)
A	645 (6.86)	13.95	6.20 (2.14)	0.74 (0.22)	0.00 (0.00)	0.00 (0.00)
B	2,907 (30.92)	17.65	26.01 (6.56)	1.22 (0.32)	5.69 (3.29)	0.20 (0.16)
C	1,877 (19.97)	12.47	7.66 (3.18)	0.21 (0.22)	0.31 (0.65)	0.00 (0.04)
D	485 (5.16)	10.52	6.69 (2.96)	1.24 (0.45)	0.01 (0.10)	0.01 (0.02)
E	829 (8.82)	16.28	28.46 (4.54)	−0.16 (0.41)	4.98 (3.65)	−0.66 (0.32)
F	750 (7.98)	10.00	21.31 (5.90)	0.57 (0.73)	5.97 (3.62)	−0.34 (0.39)
G	321 (3.41)	5.92	7.29 (2.72)	0.87 (0.59)	0.35 (0.66)	0.19 (0.24)
H	1,587 (16.88)	11.66	20.77 (4.94)	0.65 (0.40)	1.09 (1.22)	−0.07 (0.09)
Overall	9,401 (100.00)	13.85	131.28 (23.71)	3.70 (0.70)	18.77 (10.08)	0.69 (0.31)

*"Detractor percentage" is the percent of detractors among all patients with at least some survey data (i.e., non-response to the facility recommendation question is counted as a non-detractor). Differences are measured as mean patient census in care area for Detractors minus non-detractors. The 'Overall' row indicates the number of patients (and boarders, respectively) in the ED in total (ie, not localized to that specific area) at the time of the patient's arrival to their last care area.

Table 3. Logistic regression models for estimating a patient's detractor likelihood.*
Predictors	Unadjusted model			Adjusted model
Predictors	Odds ratios (SE)	CI	P value	Odds ratios (SE)	CI	P value
(Intercept)	0.15 (0.02)	0.12 – 0.19	<0.001	0.11 (0.02)	0.07 – 0.17	<0.001
Last location
A	1.00	reference		1.00	reference
B	1.38 (0.18)	1.07 – 1.78	0.013	0.71 (0.11)	0.52 – 0.96	0.025
C	0.92 (0.13)	0.71 – 1.22	0.562	0.63 (0.09)	0.47 – 0.85	0.002
D	0.71 (0.14)	0.48 – 1.04	0.085	0.63 (0.13)	0.42 – 0.93	0.023
E	1.26 (0.19)	0.94 – 1.71	0.125	0.68 (0.12)	0.48 – 0.96	0.03
F	0.72 (0.12)	0.51 – 1.00	0.053	0.43 (0.08)	0.30 – 0.63	<0.001
G	0.39 (0.11)	0.22 – 0.65	0.001	0.19 (0.05)	0.10 – 0.32	<0.001
H	0.85 (0.12)	0.65 – 1.13	0.258	0.40 (0.09)	0.26 – 0.62	<0.001
Patients in area (standardized) * Last location
A	1.47 (0.19)	1.15 – 1.91	0.003	1.34 (0.17)	1.04 – 1.74	0.027
B	1.21 (0.06)	1.10 – 1.33	<0.001	1.15 (0.06)	1.04 – 1.27	0.007
C	1.07 (0.07)	0.93 – 1.22	0.351	1.09 (0.08)	0.94 – 1.25	0.261
D	1.52 (0.23)	1.14 – 2.05	0.005	1.38 (0.21)	1.03 – 1.87	0.034
E	0.97 (0.09)	0.80 – 1.16	0.711	0.94 (0.09)	0.78 – 1.13	0.506
F	1.10 (0.13)	0.87 – 1.40	0.427	1.06 (0.13)	0.83 – 1.36	0.622
G	1.37 (0.33)	0.86 – 2.20	0.179	1.33 (0.32)	0.83 – 2.16	0.237
H	1.14 (0.09)	0.98 – 1.34	0.093	1.07 (0.09)	0.91 – 1.25	0.415
Age in years				0.99 (0.00)	0.98 – 0.99	<0.001
Gender
Female				1.00	reference
Male				0.60 (0.04)	0.52 – 0.67	<0.001
Survey completed in English				1.62 (0.16)	1.34 – 1.97	<0.001
Number of ED care areas visited				1.16 (0.08)	1.01 – 1.33	0.031
Number of ED waiting rooms visited				1.06 (0.07)	0.93 – 1.22	0.38
Placed in Observation status				1.08 (0.15)	0.82 – 1.43	0.575
Placed in hallway bed				1.07 (0.09)	0.91 – 1.25	0.409
Patient leaves AMA or LWBS				5.15 (0.77)	3.84 – 6.89	<0.001
Length of stay in hours (logarithm)				1.71 (0.11)	1.50 – 1.95	<0.001
AUC (CI)	0.594 (0.577 – 0.610)			0.673 (0.657 – 0.690)

*The number of patients present in the specific area is standardized (ie, mean is subtracted, and the result is divided by the standard deviation) to allow comparison across different areas; therefore, a unit increase equates to an increase in one standard deviation. P-values below 0.05 are bolded. Odds ratios greater than 1.0 correspond to increased likelihood of being a detractor.
SE, standard error; CI, confidence interval; ED, emergency department; AMA, against medical advice; LWBS, left without being seen; AUC, area under the receiver-operator characteristic curve.