Advanced imaging and trends in hospitalizations from the emergency department.

OBJECTIVE: The proportion of US emergency department (ED) visits that lead to hospitalization has declined over time. The degree to which advanced imaging use contributed to this trend is unknown. Our objective was to examine the association between advanced imaging use during ED visits and changes in ED hospitalization rates between 2007-2008 and 2015-2016.
METHODS: We analyzed data from the National Hospital Ambulatory Medical Care Survey. The primary outcome was ED hospitalization, including admission to inpatient and observation units and outside transfers. The primary exposure was advanced imaging during the ED visit, including computed tomography, magnetic resonance imaging, and ultrasound. We constructed a survey-weighted multivariable logistic regression with binary outcome of ED hospitalization to examine changes in adjusted hospitalization rates from 2007-2008 to 2015-2016, comparing ED visits with and without advanced imaging.
RESULTS: ED patients who received advanced imaging (versus those who did not) were more likely to be 65 years or older (25.3% vs 13.0%), non-Hispanic white (65.3% vs 58.5%), female (58.4% vs 54.1%), and have Medicare (26.5% vs 16.0%). Among ED visits with advanced imaging, adjusted annual hospitalization rate declined from 22.5% in 2007-2008 to 17.3% (adjusted risk ratio [aRR] 0.77; 95% CI 0.68, 0.86) in 2015-2016. In the same periods, among ED visits without advanced imaging, adjusted annual hospitalization rate declined from 14.3% to 11.6% (aRR 0.81; 95% CI 0.73, 0.90). The aRRs between ED visits with and without advanced imaging were not significantly different.
CONCLUSION: From 2007-2016, ED visits with advanced imaging did not have a greater reduction in admission rate compared to those without advanced imaging. Our results suggest that increasing advanced imaging use likely had a limited role in the general decline in hospital admissions from EDs. Future research is needed to further validate this finding.

Introduction

Background

Advanced imaging has become an integral part of the modern emergency department (ED). By 2005 EDs across the US have had near universal access to computed tomography (CT) with a growing presence of magnetic resonance imaging (MRI) availability [1]. The use of advanced imaging grew exponentially over the early 2000s, with imaging rates tripling between 1996 and 2007 [2]. The increased use of advanced imaging have raised concerns about the negative impacts of overuse, including radiation exposure associated with CT scans [3] and their associated high costs. However, whether the increased use of advanced imaging has provided additional value remains debated.

One way to evaluate the value of increased advanced imaging utilization in the ED is whether it has led to cost savings through avoided hospitalizations. With inpatient care accounting for nearly one-third of the US national health expenditure [4], numerous policies have aimed to reduce inpatient hospitalizations, including the 2010 Recovery Audit Contractor program and 2013 Two-Midnight Rule disincentivized short-stay admissions [5]. These policies have created a substantial pressure on EDs to shift care towards the outpatient setting as hospitalizations originating from the ED increased to more than 80% of hospitalizations by 2009 [6]. From 2006 to 2014, while ED visits increased by 18%, hospitalization rates of ED visits have declined by nearly 10% [7]. Although this decrease in hospitalization rates coincided with the rapid expansion of advanced imaging use, whether advanced imaging has contributed to the declining admission rates remains unexplored.

In this study, we utilized the data from a nationally representative sample of US ED visits to examine the association between advanced imaging use and the trends in ED hospitalization rates. Prior studies have shown that advanced imaging use rose sharply between 1997 to 2007 [2], but, to our knowledge, no study have examined whether this growth has continued. Furthermore, the potential link between advanced imaging and the decrease in ED hospitalization rates has not been examined. We hypothesized that, compared to ED visits without advanced imaging, ED visits with advanced imaging were associated with a greater decline in admission rate.

Methods

Dataset

We analyzed the cross-sectional data of the National Hospital Ambulatory Medical Care Survey ED sample (NHAMCS-ED), a multistage, probability sample of US ED visits administered by the National Center for Health Statistics (NCHS) from 2007 to 2016. NHAMCS-ED uses a four-stage sampling design: 1) county-level geographic region as primary sampling units (PSU), 2) hospitals within each PSU, 3) emergency service areas served by each hospital, and 4) 100–150 patient records from a randomly assigned four-week period of the survey year within each emergency service area. NCHS excluded federal, military, and Veterans Administration hospitals. Final samples included from 267 to 408 responding EDs reporting a total of 25,000 to 30,000 ED visits annually. Probability weights and survey design variables were assigned to every visit to allow the calculation of nationally representative estimates and standard errors. Full details of the NHAMCS methodology are available online [8]. This study was exempt from review by the institutional review board of the authors’ institutions.

Outcomes

The primary outcome of interest is ED hospitalization. We defined ED hospitalization as inpatient admission, observation stay, or hospital transfer. We categorized observation stays as hospitalization because it reflects the ED physician’s determination that patients could not be safely discharged. Furthermore, in absence of an ED-based observation unit, patients would often be cared for in an hospital floor setting indistinguishable from inpatient care [9]. We also considered hospital transfer as equivalent to the decision to hospitalize. In transferring, the ED clinicians likely believed that there was a need for higher levels of care and the patients could not be safely discharged.

Key variables

We defined advanced imaging to include CT, MRI, and ultrasound. Owing to a lack of direct potential harm and relatively lower costs, ultrasound is often omitted when examining the use and overuse of advanced imaging. However, in this context, we included ultrasound because, like CT and MRI, it is an imaging modality that is high-cost and often not immediately available in the outpatient context.

NHAMCS data contains patients’ presenting symptoms or complaints. Previous studies examining the value of care have often been limited by retrospective administrative claims data which contains only the diagnoses obtained after a completed medical evaluation. This limitation is highlighted by National Quality Forum’s recent move towards complaint-based quality measures [10]. We adopted the definitions developed by Kocher et al, who identified the 20 most common presenting symptoms using the primary reasons for visit variable in NHAMCS (S1 Table) [2].

We included patient characteristics as covariates in our analysis, including patient age, sex, race/ethnicity, and insurance status. We combined the indicators for self-reported race and ethnicity to generate race categories of non-Hispanic white, non-Hispanic Black, Hispanic, and others. We defined patient insurance status using the multinomial variable “expected payment type.” In most years, NCHS used a hierarchy that assigned visits by Medicaid and Medicare dual-eligible beneficiaries to Medicare. But in data year 2007, this hierarchy was different in that these visits were assigned to Medicaid. To maintain consistency, we reassigned patients visits in 2007 with dual Medicare and Medicaid coverage to Medicare.

We also used visit characteristics as covariates, including whether the visit was seen by a physician assistant or nurse practitioner (PA/NP), whether a resident was among the physician team, and hospital geographic region. Triage category has changed in NHAMCS over time. To minimize inconsistency, we collapsed the categories into urgent/emergent and others. We identified the arrival time and day of the week for each visit and categorized each visit as weekday, defined as 8AM to 5PM, Monday through Friday, and nights/weekends, defined as all other hours outside of weekdays.

Statistical analysis

All analyses incorporated survey design and weights assigned within NHAMCS. We first calculated the weighted proportion of ED visits across patient and visit characteristics, stratified by whether advanced imaging was obtained during the ED visit. We then calculated and plotted imaging and hospitalization rates in bi-annual intervals.

We modeled the probability of receiving advanced imaging during ED visits as a binary outcome using survey-weighted multivariable logistic regression, with an indicator for 2007–2008 versus 2015–2016, controlling for patient and visit characteristics. We used the marginal estimating method to calculate the probability of receiving advanced imaging in the 2007–2008 and 2015–2016 time periods and then calculated the adjusted risk ratio.

Next, we used a survey-weighted multivariable logistic regression to model the probability of hospital admission versus discharge. To examine the association between advanced imaging and the trends in hospitalization, we included an indicator for receiving advanced imaging, an indicator for 2007–2008 versus 2015–2016, and the interaction between the two, controlling for patient and visit characteristics. We used marginal estimating method to calculate adjusted annual hospitalization rates for visits with and without advanced imaging in 2007–2008 and 2015–2016, as well as the adjusted risk ratio and relative proportional change in hospitalization rates comparing visits with and without advanced imaging.

We repeated the analysis for visits with each of the 20 most common presenting symptoms. We also performed sensitivity checks with two different specification, 1) only accounting for inpatient admissions and 2) only considering CT/MRI as advanced imaging. All tests were two-sided, and we considered an alpha of less than 0.01 as significant, consistent with NCHS-recommended practices. STATA 15/MP (College Station, TX) was used for all analyses.

Results

Study population

Between 2007 and 2016, a total of 289,188 ED visits were included in the NHAMCS dataset with 110,152 visits in the years 2007–2008 and 2015–2016. From 2007 to 2016, total ED visits in the US increased from an estimated 116.8 million annually to 145.6 million. Overall 18.9% of ED visits (95% CI 18.4–19.5) included advanced imaging. Compared to ED patients who did not receive advanced imaging (Table 1), ED patients who received advanced imaging were more likely to be 45 years or older (52.3% vs 33.7%, p<0.001), female (58.4% vs 54.1, p<0.001), non-Hispanic white (65.3% vs 58.5%, p<0.001), and insured by private insurance (35.1% vs 32.6%, p<0.001) or Medicare (26.5% vs 16.0%, p<0.001). Imaged visits were slightly more likely to be during office hours (37.9% vs 34.6, p<0.001) but much more likely to be urgent or emergent (61.5% vs 39.7%, p<0.001).

Table 1

Demographic characteristics of study population by use of advanced imaging, 2007 to 2016.

	Advanced Imaging (n = 52,942)			No Advanced Imaging (n = 236,246)
Characteristics	n	Weighted %	(95% CI)	n	Weighted %	(95% CI)	P
Age							<0.001
<15	2,797	5.4	(5.0, 5.8)	51,274	22.3	(21.3, 23.3)
15–24	7,162	13.5	(12.9, 14.1)	37,408	15.9	(15.6, 16.2)
25–44	15,509	28.9	(28.3, 29.5)	67,183	28.0	(27.5, 28.5)
45–64	14,211	27.0	(26.4, 27.7)	49,647	20.7	(20.3, 21.1)
65–74	5,128	10.0	(9.6, 10.4)	13,556	5.8	(5.6, 6.1)
> = 75	8,135	15.3	(14.7, 15.9)	17,178	7.2	(6.9, 7.6)
Female	31,005	58.4	(57.7, 59.1)	126,561	54.1	(53.8, 54.5)	<0.001
Race							<0.001
Non-Hispanic White	33,837	65.3	(63.6, 67.0)	135,410	58.5	(56.5, 60.4)
Non-Hispanic Black	9,602	18.2	(16.6, 20.0)	55,344	23.2	(21.1, 25.3)
Hispanic	7,498	13.6	(12.4, 14.9)	36,676	15.4	(14.0, 16.8)
Other	2,005	2.8	(2.4, 3.3)	8,816	3.1	(2.7, 3.5)
Insurance							<0.001
Privatea	18,581	35.1	(34.0, 36.2)	77,648	32.6	(31.5, 33.6)
Medicare	14,033	26.5	(25.6, 27.4)	37,662	16.0	(15.4, 16.6)
Medicaid	10,687	19.5	(18.6, 20.5)	70,463	29.2	(28.1, 30.4)
Uninsured/self-pay	6,464	12.0	(11.4, 12.7)	33,373	14.3	(13.6, 15.0)
Unknown	3,177	6.8	(5.7, 8.2)	17,100	8.0	(6.8, 9.3)
Visit Characteristics
Time of visit							<0.001
Office Hours	18,257	37.9	(37.4–38.5)	77,403	34.6	(34.3–35.0)
Weeknights	13,655	27.9	(27.3–28.4)	65,829	30.1	(29.8–30.4)
Weekends	16,836	34.2	(33.7–34.7)	77,741	35.3	(35.0–35.5)
Triage Level							<0.001
Urgent/Emergent	33,453	61.5	(58.8, 64.1)	96,443	39.7	(38.2, 41.4)
Non-urgent	8,033	14.8	(13.7, 16.0)	80,607	34.6	(33.2, 36.1)
Unknown/Not triaged	11,456	23.7	(21.1, 26.5)	59,196	25.6	(23.2, 28.2)
Seen by PA/NP	8,000	15.9	(14.4, 17.4)	40,325	18.8	(17.3, 20.3)	<0.001
Seen by Resident	6,394	10.5	(9.2, 11.9)	23,514	8.4	(7.3, 9.5)	<0.001
Hospital Region							0.044
Northeast	11,568	17.8	(15.8, 20.1)	52,987	17.7	(15.6, 20.0)
Midwest	12,608	23.6	(20.4, 27.2)	53,297	22.6	(19.7, 25.8)
South	17,834	36.8	(33.0, 40.9)	83,032	39.2	(35.3, 43.2)
West	10,932	21.8	(19.2, 24.6)	46,930	20.5	(18.2, 23.1)

Private insurance status includes worker’s compensation. Weeknights were defined as Mon-Thursday after 5 through 8am the next day. Weekends defined as Friday after 5pm to Monday 8am.

Abbreviations: CI, confidence interval; PA, physician assistant; NP, nurse practitioner.

Trends in advanced imaging use

Overall advanced imaging use in the ED increased, from 17.1% (95% CI 16.2–18.0) in 2007–2008 to 21.3% (95% CI 20.2–22.4) in 2015–2016. This increase was driven by the continued growth in CT/MRI use and, to a smaller degree, by growing use of ultrasound (Fig 1).

Fig 1

Proportion of ED visits that received CT/MRI or ultrasound increase while those leading to hospital admission decreased.

Weighted bi-annual proportions calculated from the National Hospital Ambulatory Medical Care Survey.

In our modeling, we found that the overall adjusted imaging rate increased by 32% (adjusted risk ratio [aRR] 1.32, 95% CI 1.23–1.40, p<0.001; Table 2). Among the 20 most common presenting complaints, the adjusted advanced imaging rate increased significantly in ED visits for injury (aRR 1.35; 95% CI 1.23–1.48, p<0.001), upper respiratory symptoms (aRR 1.54; 95% CI 1.13–1.95, p = 0.009), abdominal pain (aRR 1.18; 95% CI 1.08–1.28, p<0.001), leg symptoms (aRR 1.35; 95% CI 1.13–1.57, p = 0.002), neck/back pain (aRR 1.39; 95% CI 1.18–1.61, p<0.001), and dizziness/syncope (aRR 1.23; 95% CI 1.06–1.40, p = 0.009). There were no presenting complaints where advanced imaging use decreased.

Table 2

Imaging rate by Presenting symptom in 2007–2008 and 2015–2016.

	% of total ED visits			Adjusted Imaging Rate (%; 95% CI)				Adjusted Risk Ratio
				2007–2008		2015–2016
	n	Weighted %	(95% CI)	%	(95% CI)	%	(95% CI)		(95% CI)	p-value
Overall	110,152			16.5	(15.8, 17.3)	21.8	(20.7, 22.9)	1.32	(1.23, 1.40)	<0.001
Injury	16,157	14.6	(14.0, 15.2)	14.7	(13.7, 15.6)	20.0	(18.5, 21.3)	1.35	(1.23, 1.48)	<0.001
Psychiatric	9,740	8.5	(8.3, 8.8)	32.6	(30.4, 34.8)	33.7	(31.3, 36.0)	1.03	(0.94, 1.13)	0.48
Upper Respiratory	9,425	8.7	(8.4 9.2)	3.0	(2.43, 3.54)	4.6	(3.7, 5.5)	1.54	(1.13, 1.95)	0.009
Abdominal Pain	8,200	8.0	(7.7, 8.3)	41.3	(38.6, 43.9)	48.8	(46.3, 51.3)	1.18	(1.08, 1.28)	<0.001
Leg Symptoms	5,600	5.0	(4.8, 5.2)	12.1	(10.6, 13.5)	16.3	(14.4, 18.2)	1.35	(1.13, 1.57)	0.002
Chest pain	5,398	5.3	(5.0, 5.5)	15.9	(14.1, 17.7)	17.8	(15.4, 20.2)	1.12	(0.92, 1.32)	0.25
Neck/Back pain	5,313	4.9	(4.7, 5.1)	17.1	(15.4, 18.8)	23.9	(21.0, 26.7)	1.39	(1.18, 1.61)	<0.001
Fever	4,436	4.2	(3.9, 4.6)	4.5	(3.4, 5.6)	5.6	(4.2, 7.0)	1.24	(0.82, 1.67)	0.26
Nausea/Vomiting/Diarrhea	4,333	4.1	(3.9, 4.3)	15.6	(13.8, 17.4)	19.5	(17.2, 21.8)	1.25	(1.04, 1.46)	0.018
Shortness of Breath	4,057	3.7	(3.5, 3.9)	11.9	(10.1, 13.7)	17.1	(14.1, 20.1)	1.44	(1.10, 1.78)	0.012
Arm Symptoms	3,854	3.4	(3.2, 3.7)	6.8	(5.2, 8.3)	10.3	(8.0, 12.5)	1.52	(1.03, 2.00)	0.037
Headache	3,456	3.3	(3.1, 3.4)	36.6	(33.1, 40.0)	38.0	(34.6, 41.3)	1.04	(0.91, 1.17)	0.57
Skin Complaints	2,961	2.6	(2.5, 2.8)	2.8	(1.9, 3.6)	3.8	(2.8, 5.3)	1.38	(0.68, 2.09)	0.29
Dizziness/syncope	2,284	2.1	(2.0, 2.3)	36.1	(32.6, 39.7)	44.4	(40.1, 48.7)	1.23	(1.06, 1.40)	0.009
Pregnancy Problems	1,563	1.1	(1.0, 1.2)	36.3	(31.1, 41.5)	46.6	(38.5, 54.7)	1.28	(1.01, 1.56)	0.046
Flank Pain	1,374	1.4	(1.3, 1.4)	48.6	(43.3, 53.9)	57.9	(53.3, 62.5)	1.19	(1.02, 1.36)	0.028
General Weakness	1,203	1.2	(1.1, 1.3)	29.6	(25.8, 33.4)	33.9	(28.2, 39.6)	1.14	(0.90, 1.39)	0.24
Neurological Symptom	1,169	1.0	(1.0, 1.1)	50.2	(45.2, 55.1)	55.2	(48.8, 61.6)	1.10	(0.93, 1.27)	0.25
Convulsions	1,054	1.0	(0.9, 1.0)	37.9	(33.0, 42.9)	39.3	(33.5, 45.1)	1.04	(0.84, 1.24)	0.71
Vaginal Bleeding	770	0.7	(0.6, 0.7)	33.2	(27.3, 39.0)	37.4	(29.6, 45.2)	1.13	(0.81, 1.45)	0.44

Adjusted imaging rate and risk ratios calculated using multivariable survey-weighted logistic regression and marginal estimation methods, adjusting for patient and visit characteristics.

Abbreviation: ED, emergency department; CI, confidence interval.

Advanced imaging use and trends in hospitalization rates

Hospitalization rates declined during the study period from 16.2% (95% CI 15.0–17.4) in 2007–2008 to 12.2% (95% CI 10.9–13.7) in 2015–2016 (Fig 1). Adjusted hospitalization rates among ED visits with and without advanced imaging decreased overall and for most presenting complaints (Table 3). Comparing hospitalization rates between ED visits with and without advanced imaging, the relative change in hospitalization rates between 2007–2008 and 2015–2016 was not significantly different (relative difference: -4.0%; 95% CI -11.2, 3.2; p = 0.27; Table 3). In the complaint-specific analyses, though no relative difference reached the a priori level of statistical significance at p<0.01, there were relative increases among visits for Neck/Back pain (65.3%; 95% CI 9.5, 121.2; p = 0.022), shortness of breath (30.4%; 95% CI 4.9, 55.9; p = 0.019), syncope/dizziness (29.2%; 95% CI 3.6, 54.8; p = 0.025), and general weakness (29.9%; 95% CI 3.5, 56.2; p = 0.026) that reached p<0.05. Notably, among these presenting complaints, there was a decrease in adjusted hospitalization rate among the unimaged ED visits while the adjusted hospitalization rates among visits with advanced imaging did not significantly change (Table 3).

Table 3

Changes in adjusted admission rates comparing 2007–2008 to 2015–2016.

	Visits with Imaging				Visits without Imaging
Presenting complaint	Adjusted Admission Rates (%)		Adjusted RR (95% CI)		Adjusted Admission Rates (%)		Adjusted RR (95% CI)		Relative Difference, % (95% CI)
	2007–8	2015–16			2007–8	2015–16					p
Overall	22.5	17.3	0.77	(0.68, 0.86)	14.3	11.6	0.81	(0.73, 0.90)	-4.0	(-11.2, 3.2)	0.27
Injury	12.2	8.7	0.72	(0.52, 0.91)	5.8	5.3	0.93	(0.74, 1.12)	-21.1	(-46.4, 4.3)	0.10
Psychiatric	24.3	21.8	0.90	(0.72, 1.07)	20.7	20.7	1.00	(0.83, 1.17)	-10.2	(-32.8, 12.4)	0.38
Upper Respiratory	17.4	11.5	0.66	(0.28, 1.04)	4.8	4.1	0.87	(0.62, 1.12)	-20.8	(-61.1, 19.5)	0.31
Abdominal Pain	27.8	18.2	0.65	(0.54, 0.77)	15.1	9.5	0.63	(0.47, 0.78)	2.8	(-15.2, 20.7)	0.76
Leg Symptoms	18.8	11.0	0.58	(0.36, 0.81)	9.5	7.2	0.76	(0.55, 0.96)	-17.6	(-49.2, 14.0)	0.27
Chest pain	45.5	29.4	0.65	(0.51, 0.79)	37.0	25.2	0.68	(0.56, 0.80)	-3.6	(-18.1, 10.9)	0.63
Neck/Back pain	10.5	12.3	1.18	(0.64, 1.71)	4.9	2.5	0.52	(0.28, 0.76)	65.3	(9.5, 121.2)	0.022
Fever	23.0	18.2	0.79	(0.36, 1.22)	8.3	7.9	0.96	(0.73, 1.20)	-16.9	(-65.0, 31.2)	0.49
Nausea/Vomiting/Diarrhea	25.9	20.3	0.78	(0.59, 0.98)	16.3	12.1	0.74	(0.54, 0.93)	4.5	(-18.5, 27.5)	0.70
Shortness of Breath	45.0	51.2	1.14	(0.88, 1.40)	40.6	33.8	0.83	(0.72, 0.94)	30.4	(4.9, 55.9)	0.019
Arm Symptoms	12.7	11.8	0.93	(0.30, 1.55)	3.9	4.9	1.24	(0.74, 1.74)	-31.2	(-101.4, 39.1)	0.38
Headache	9.1	8.9	0.98	(0.49, 1.47)	3.9	4.3	1.10	(0.40, 1.80)	-12.3	(-92.6, 68.0)	0.76
Skin Complaints	15.7	-	-	-	4.2	-	-	-	-	-	-
Dizziness, syncope	31.5	25.6	0.81	(0.60, 1.03)	22.5	11.7	0.52	(0.37, 0.67)	29.2	(3.6, 54.8)	0.025
Pregnancy Problems	7.5	6.2	0.83	(0.13, 1.53)	18.3	16.8	0.92	(0.46, 1.38)	-8.9	(-86.9, 69.0)	0.82
Flank Pain	13.3	8.4	0.63	(0.33, 0.93)	11.2	6.1	0.54	(0.21, 0.87)	8.5	(-33.7, 50.6)	0.70
General Weakness	52.1	54.1	1.04	(0.81, 1.27)	42.2	31.2	0.74	(0.59, 0.89)	29.9	(3.5, 56.2)	0.026
Neurological Symptom	42.1	34.2	0.81	(0.61, 1.02)	16.0	14.7	0.92	(0.47, 1.36)	-10.3	(-58.6, 38.0)	0.68
Convulsions	31.6	20.8	0.66	(0.38, 0.93)	18.1	8.1	0.45	(0.23, 0.66)	21.2	(-10.6, 53.0)	0.19
Vaginal Bleeding	-	-	-	-	10.5	7.2	0.68	(0.19, 1.17)	-	-	-

Adjusted admission rates, adjusted risk ratios, and absolute differences calculated from survey-weighted multivariable logistic regression and marginal estimating methods. All models adjusted for patient and visit characteristics. A negative absolute difference means admission rate reduced by greater proportion among imaged visits compared to visits without advanced imaging. Omitted admission rates (and the corresponding adjusted RR and absolute difference, had <30 observations, which were considered unreliable as recommended by the National Center for Health Statistics.

Abbreviations: RR, risk ratio; CI, confidence interval.

When we only considered inpatient admission and outside transfer as hospitalizations (excluding observation admissions), the results did not materially differ (S2 Table). When we restricted the definition of advanced imaging to only CT and MRI, results also remained stable (S3 Table). Furthermore, complaint-specific analysis showed similar relative increase for Neck/Back pain, shortness of breath, and general weakness that reached p<0.05.

Discussion

As EDs play an increasingly central role in the care of acute episodic illnesses, to further define the value of emergency care, we need to examine the relationship between the increased resource use in EDs and the changes in downstream costs such as reduced hospital admissions. Prior studies have found that the expansion of ED capabilities, including the rising use of advanced imaging, has occurred while ED hospitalizations declined [2, 7]. In this analysis, we found that high-cost advanced imaging use has continued to grow modestly, but advanced imaging was overall not associated with larger decline in ED hospitalization rates.

In our complaint-specific analyses, however, we found that, among ED visits for neck/back pain, syncope/dizziness, and generalized weakness, advanced imaging had weak association with higher admission rates. These findings were driven by a decrease in the hospitalization rates among visits without advanced imaging from 2007–2008 to 2015–2016, but no significant change in the hospitalization rates among visits with advanced imaging in the same time period.

Several explanations may be possible. Increased advanced imaging may have improved diagnostic yield, revealing diagnoses that may not have otherwise been detected and required hospital admission. However, improved diagnostic yield is unlikely given these associations were seen among presenting complaints where testing has been shown to have low diagnostic value such as neck/back pain [11] and syncope [12]. An alternative explanation may be that, over time, ED clinicians more liberally use advanced imaging among patients with higher complexity and, therefore, increased likelihood of hospital admission based on information obtained prior to imaging results. In other words, patients who previously would have been hospitalized without ED advanced imaging are now more likely to receive advanced imaging. Unfortunately, our cross-sectional analysis is unable to discern the direction of association. Future studies examining changes in decision making in the clinical context may help further elucidate the underlying drivers of our findings. Nevertheless, our findings do not support the hypothesis that the rise in ED advanced imaging contributed significantly to the decrease in ED hospitalization rates.

Over our study period, advanced imaging use continued to increase. Compared to the 3-fold increase in the decade prior,2 the increase we observed was much more modest and only significant in 5 of the 20 most common presenting complaints. However, advanced imaging use remained prevalent, particularly for the indications where they may provide limited clinical value, such as neck/back pain [11], syncope [12], and headache [13]. Society guidelines and campaigns such as Choosing Wisely® have sought to reduce advanced imaging use for these indications. Despite these efforts, we did not observe any downward trend in advanced imaging use. In addition, some limited evidence also suggests that these efforts likely did not contribute to the slowing growth in advanced imaging use [14].

Lastly, though not significantly associated with advanced imaging, ED hospitalization rates have nevertheless declined by 20–30% overall. In complaint-specific analyses, we further found ED hospitalization rates also reduced significantly across visits with and without advanced imaging for primary complaints of abdominal pain, chest pain, and injuries by up to 40%. While our results suggest that increased advanced imaging use may not have contributed to the decline in ED hospitalization rates, other clinical factors, such as outpatient clinical pathways [15, 16], and policy factors, including the rising scrutiny of short-stay admissions and improved access to follow-up as a result of coverage expansion may be have driven the decline in ED hospitalizations [17-19].

Our study has several limitations. National survey data may be susceptible to potential misclassification of presenting symptoms, ED care received, or discharge diagnoses [20]. However, the misclassification is unlikely to differ across between visits with and without advanced imaging. The cross-sectional nature of the dataset also does not allow us to discern whether visits may be return or repeat ED visits where decisions to pursue advanced imaging would be different from initial ED visits. There were limited data available to account for visits severity and comorbid conditions. Furthermore, we acknowledge that the decision of whether hospitalize after an ED evaluation is complex may not be fully accounted for in our analysis. Nevertheless, the NHAMCS dataset provides unique clinical data not available in typical insurance claims data, such as presenting complaints.

Conclusion

In this analysis of nationally-representative ED visits, we found that the growth in advanced imaging use has slowed substantially. However, we also found that visits with advanced imaging use did not experience a larger reduction in ED hospitalization rates compared to ED visits without advanced imaging. Our finding suggest that the rising advanced imaging use may not have accounted for the decline in ED admission rates, although further research is needed to replicate our findings.

Definition of presenting complaints by NCHS reason for visit codes.

(DOCX)

Click here for additional data file.

Changes in adjusted admission rates comparing 2007–2008 to 2015–2016, only inpatient hospitalization considered admission.

(DOCX)

Click here for additional data file.

Changes in adjusted admission rates comparing 2007–2008 to 2015–2016, advanced imaging included only CT or MRI.

(DOCX)

Click here for additional data file.

6 Jul 2020

PONE-D-20-04321

Advanced Imaging and Trends in Hospitalizations from the Emergency Department

PLOS ONE

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Reviewer #1: Yes

**********

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: This manuscript is very well-written and addresses an important topic regarding healthcare resource utilization. Having said that, this issue is complex and I have a few suggestions that would potentially help the paper reflect this complexity.

1. Hypothesis

I think your hypothesis - that advanced ED imaging would lead to a decline in admission rates - needs a bit more rationale earlier in the paper. Intuitively, and as you later mention in the discussion, advanced imaging could instead lead to an increase in hospitalization if more subtle but possibly dangerous pathology was identified. Although your paper did not show any statistical difference for imaging vs. hospitalization in either direction, I think some justification for your hypothesis would help the reader follow the paper.

2. Confounding variables

There are several variables that affect the decision to admit a patient to hospital. Of course, the disposition of patients at either end of the spectrum are obvious (ie. a fractured toe vs. a patient in septic shock), but much of emergency medicine operates in a grey area where two different providers could make two different, and equally justifiable, decisions. This is difficult to capture in a binary "admitted vs. discharge" outcome measure.

Additionally, admission can sometimes be a product of patient preference or lack of outpatient supports. I think that you have done a good job explaining some of these variables in the conclusion ("outpatient clinical pathways, and policy factors...") but can better underscore the many factors which are at play in the decision to admit a patient to hospital, and include this is a major limitation to your study.

3. Methods

How were patients who were seen in the ED and then discharged with a plan/appointment to return the next day for advanced imaging dealt with? Was this information reflected in the database? This is a relatively common practice in the EDs I have worked at for patients seen in the evening/overnight without critically emergent differential diagnoses.

4. Results

No further suggestions here - I was happy to see you include relevant high-level results for subgroups (ie. excluding observation admissions and excluding ultrasound) - I think this adds credence to the arguments brought forth in the paper.

5. Conclusion

You suggest that advanced imaging may not play a substantial role in the decline of admission rates. Despite your well-executed study, I am still not convinced of this, largely because of the many confounding variables, and so I think it would be more appropriate to state that more research is needed.

**********

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Reviewer #1: Yes: Shaun Mehta

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5 Aug 2020

Reviewer #1: This manuscript is very well-written and addresses an important topic regarding healthcare resource utilization. Having said that, this issue is complex and I have a few suggestions that would potentially help the paper reflect this complexity.

1. Hypothesis

I think your hypothesis - that advanced ED imaging would lead to a decline in admission rates - needs a bit more rationale earlier in the paper. Intuitively, and as you later mention in the discussion, advanced imaging could instead lead to an increase in hospitalization if more subtle but possibly dangerous pathology was identified. Although your paper did not show any statistical difference for imaging vs. hospitalization in either direction, I think some justification for your hypothesis would help the reader follow the paper.

Thank you for this suggestion, we reorganized the introduction to refocus the study’s emphasis on examining the value of increased advanced imaging through reduction in

hospital admissions.

2. Confounding variables

There are several variables that affect the decision to admit a patient to hospital. Of course, the disposition of patients at either end of the spectrum are obvious (ie. a fractured toe vs. a patient in septic shock), but much of emergency medicine operates in a grey area where two different providers could make two different, and equally justifiable, decisions. This is difficult to capture in a binary "admitted vs. discharge" outcome measure.

Additionally, admission can sometimes be a product of patient preference or lack of outpatient supports. I think that you have done a good job explaining some of these variables in the conclusion ("outpatient clinical pathways, and policy factors...") but can better underscore the many factors which are at play in the decision to admit a patient to hospital, and include this is a major limitation to your study.

In this revision, we acknowledge the limitation of our data to account for the complex decision of admitting a patient more explicitly.

“Furthermore, we acknowledge that the decision of whether hospitalize after an ED evaluation is complex may not be fully accounted for in our analysis.”

3. Methods

How were patients who were seen in the ED and then discharged with a plan/appointment to return the next day for advanced imaging dealt with? Was this information reflected in the database? This is a relatively common practice in the EDs I have worked at for patients seen in the evening/overnight without critically emergent differential diagnoses.

We are not aware that planned return ED visits is a commonplace practice, at least in the community sites where we work. Nevertheless, the NHAMCS data is consisted of a

cross-sectional sample of ED visits from EDs that were surveyed annually. The patients are thus not followed longitudinally across visits. Therefore, NHAMCS is unable to identify

visits that may be “return” or “repeat” visits. We additionally noted this limitation as considerations for imaging use would certainly be different for repeat or return visits.

“The cross-sectional nature of the dataset also does not allow us to discern whether visits may be return or repeat ED visits where decisions to pursue advanced imaging would be

different from initial ED visits.”

4. Results

No further suggestions here - I was happy to see you include relevant high-level results for subgroups (ie. excluding observation admissions and excluding ultrasound) - I think this adds credence to the arguments brought forth in the paper.

Thank you.

5. Conclusion

You suggest that advanced imaging may not play a substantial role in the decline of admission rates. Despite your well-executed study, I am still not convinced of this, largely because of the many confounding variables, and so I think it would be more appropriate to state that more research is needed.

We adjusted our tone in the CONCLUSION section to be more align our finding as preliminary and needs further replication. However, we do believe that our study design is

stronger exploratory compared to studies that simply observed that the decline in admission rates and the increase in advanced imaging occurred concurrently.

Submitted filename: Reviewer comments and response.docx

Click here for additional data file.

31 Aug 2020

Advanced Imaging and Trends in Hospitalizations from the Emergency Department

PONE-D-20-04321R1

Dear Dr. Shih-Chuan Chou,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Steve Lin

Academic Editor

PLOS ONE

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for taking the time to address my comments. I feel that you have addressed everything comprehensively and that this paper adds value to the body of scientific literature as it relates to emergency medicine.

Reviewer #2: This is a well designed study on a relevant topic. This observational study has a strong analytical methods to answer the question of whether increases in imaging use may have resulted in decreased hospital admissions. The comments of the reviewers were addressed.

A few outstanding comments:

1. There is an issue with the wording here: "we acknowledge that the decision of whether hospitalize after an ED evaluation is complex may not be fully accounted for in our"

2. The conclusion does not need to suggest a specific type of study such as a "replication study". "Replicate" could be changed for "support".

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Shaun Mehta

Reviewer #2: Yes: Samuel Vaillancourt

4 Sep 2020

PONE-D-20-04321R1

Advanced Imaging and Trends in Hospitalizations from the Emergency Department

Dear Dr. Chou:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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PLOS ONE