Article, Emergency Medicine

Freestanding emergency departments in Texas do not alleviate congestion in hospital-based emergency departments

a b s t r a c t

Objectives: Ever since the passage of the Texas Freestanding Emergency medical care Facility Licensing Act in 2009, freestanding Emergency Departments (FrEDs) have spread throughout Texas. This study aims to deter- mine whether the entry of FrEDs has been associated with less congestion in hospital-based EDs.

Methods: The dependent variables of interest were hospital-based ED annual visit volume, median wait time, length of visit for discharged patients and the percent of patients who Left without being seen . The ex- planatory variables of interest were the numbers of FrEDs within the same local market of each hospital-based ED, and an indicator variable for whether the hospital owned satellite FrEDs in outlying areas.

Results: Hospital ED visits, wait times, length of visit for discharged patients, and LWBS rates were not associated with the number of competitor FrEDs in the local market. Hospitals that opened satellite FrEDs had significantly higher visit volume in general, but did not experience shorter wait times, length of visit or LWBS rates if located in large metropolitan areas.

Conclusions: The entry of FrEDs did not help relieve congestion in nearby hospitals in major metropolitan areas in Texas. By offering more treatment options to patients, FrEDs are associated with increased usage of emergency services.

(C) 2019 The Authors. This is an open access article under the CC BY-NC-ND license (http://

creativecommons.org/licenses/by-nc-nd/4.0/).

  1. Introduction
    1. Background

The past decade has witnessed a growing trend in emergency care use. Based on the National Hospital Ambulatory Medical Care Survey [1], the number of Emergency Department (ED) visits reached 136.9 million nationally (0.433 visits per person) in 2015, while the number in 2008 was 123.8 million (0.414 visits per person). The number of ED visits in the U.S. increased 10.6% from 2008 to 2015. It has been argued that the sharp rise in ED visits limits access to timely emergency care [2]. In an effort to relieve hospital emergency congestion and help pa- tients access care in emergency service shortage areas, many states allowed the introduction of freestanding EDs (FrEDs) [3]. FrEDs, which are structurally separate and distinct from hospitals, have been found

? Presentations: American Society of Health Economists 2018 Conference Poster Session, Atlanta, Georgia June 2018.

?? Financial support: N/A.

* Corresponding author at: Rice University, MS 22, 6100 Main Street, Houston, TX 77005, United States of America.

E-mail address: [email protected] (Y. Xu).

to locate in higher income urban areas with higher shares of insured res- idents [4,5].

Two types of FrEDs, independent FrEDs and hospital-affiliated satel- lite FrEDs, operate in Texas. The first independent FrED opened in June 2010 after the 81st Texas State legislature passed the Texas Freestand- ing Emergency Medical Care Facility Licensing Act [6]. Independent FrEDs are not affiliated with a hospital and can be operated for-profit. Satellite FrEDs are owned and operated by their parent hospitals or hos- pital systems. Distinct from independent FrEDs, satellite FrEDs receive Medicare and Medicaid reimbursement through their hospital certifica- tion. By the end of 2016, the state had over 300 FrEDs, and about two- thirds were privately owned, for-profit independent facilities.

Importance

The proliferation of FrEDs has provided both opportunities and chal- lenges for healthcare providers, legislators, and payers. FrEDs provide timely emergency care without long wait times often encountered in hospitals. For those patients with low-acuity conditions, a shorter wait time at FrEDs is attractive. However, critics argue [7,8] that the facilities increased overall healthcare spending, by serving as supplements rather than substitutes to traditional emergency departments. Offering more choices in the healthcare market is likely to increase utilization and

https://doi.org/10.1016/j.ajem.2019.05.020

0735-6757/(C) 2019 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

spending [9]. By locating in wealthy communities, FrEDs were more likely to attract privately insured patients [4,5]. The cost at FrEDs was 10 times higher than urgent care centers for 15 common diagnoses [10]. The billed amounts from FrED services are similar to full-service hospital EDs, even though FrEDs often provide less resource-intensive care [10,11]. A retrospective comparison suggested an urban tertiary care hospital ED showed a trend towards a 20% higher admission rate compared with its satellite FrEDs [12]. Additional research also con- cluded that patients in FrEDs had fewer comorbidities, shorter length of stay and lower Hospital admission rates [13]. Both the 2017 and 2018 MedPAC reports to Congress [14,15] suggested reducing Medicare payment rates for visits to satellite FrEDs in urban areas. Any revision in Medicare payments might also trigger changes in private insurance re- imbursements. Blue Cross Blue Shield, one of the biggest insurers in Texas, made a controversial announcement that they would not pay for non-emergency ER visits to out-of-network emergency care facilities for HMO customers in early 2018 [16].

Though many physicians and policy makers claimed that FrEDs would reduce patient volume at hospitals, the literature contains only limited quantitative studies about the impact of FrEDs on access to emergency care. Different from California and many other states with restrictive state regulations towards FrEDs [3], Texas has a relatively loose policy and a range of cities with different sizes. As the second most populous state with more than 300 FrEDs, Texas is a good example to study the phenomenon of emergency market competition after intro- ducing FrEDs.

Overall work

This study aims to determine whether the entry of FrEDs has been associated with less congestion in hospital-based EDs. We hypothesize that the entry of FrEDs in a local market is associated with decreased ED visits, wait times, length of visit for discharged patients and patients who left without being seen (LWBS) in nearby hospital EDs. Entry was measured in two ways: the number of competitor FrEDs in each hospital’s local market, and whether the hospital built its own satellite FrEDs. We examined all hospitals in Texas and measured the association between the presence of new FrEDs and hospital-based ED outcomes.

  1. Methods
    1. Study design

This was a retrospective cohort study of hospital EDs in Texas that experienced different amounts of entry of FrEDs in their local market between 2010 and 2016. This study was determined to be exempt by our university’s Institutional Review Board (IRB).

Study setting and population

Locations and entry/exit dates for independent FrEDs were obtained from online licensing information posted by the Texas Department of State Health Services (DSHS) [6]. The Texas DSHS does not license hos- pitals’ satellite FrEDs. Locations for satellite FrEDs were obtained by vis- iting the website for each hospital and searching for affiliated satellite FrED(s). Website searches or phone calls to each satellite FrED were performed to determine opening dates. This search process identified 325 independent FrEDs and 120 satellite FrEDs between 2010 and 2016.

Study protocol

The main outcomes for this study were annual hospital ED efficiency measures including emergency department wait time, length of visit for discharged patients and rate of patients who left without being seen (LWBS) in the hospital EDs. The measurements were obtained from the Centers for Medicare and Medicaid Service (CMS) “Hospital Com- pare Timely and Effective Care Survey” from 2012 (the earliest year available) to 2016. The wait time was the median time from door to di- agnostic evaluation by a qualified medical professional. Length of visit for discharged patients (short for “discharge time” thereafter) mea- sured the time from ED arrival to ED departure for discharged patients. The LWBS rate was the percentage of patients that left without being seen. These indicators were chosen, because they are commonly used as predictors for emergency department crowding [17]. Wait time and discharge time were missing for 94 hospitals, and LWBS was missing1 for 100 hospitals in the CMS survey when matching hospitals in the AHA list.

The explanatory variables of interest were the numbers of competi- tor FrEDs (excluding any owned satellite FrEDs) within the same local market of each hospital-based ED, and an indicator variable for whether the hospital owned any satellite FrEDs. We counted the number of FrEDs that had been open for at least one full calendar year, which ex- cluded current-year entry of FrEDs. Using full-year presence adjusted for potential bias from late entry in a year and took market learning into consideration. That is, any facility that opened after January would not have a full year of impact on nearby hospital EDs. Local mar- kets were defined based on U.S. Census Public Use Microdata Area (PUMA) borders. The advantage of using PUMAs is that they are larger in land area than zip codes, which may not encompass all the relevant facility choices for a prospective patient; and smaller than counties (in urban areas), which are too large in land area to accurately reflect the set of facilities that a patient is likely to choose from in an emergency [4]. For example, the city of Houston contains 178 zip codes and roughly 50 PUMAs. The number of FrEDs within a 3-mile distance band from each hospital-based ED was included as an explanatory variable in sen- sitivity analyses.

Major metropolitan areas were defined as metropolitan statistical areas with population over 2 million, and non-major metropolitan areas were defined as the remaining areas in Texas. There are 25 metro- politan statistical areas in Texas2 in 2017. The four largest metropolitan areas in Texas (Fig. 1) are Dallas-Fort Worth-Arlington (population 7.4 million), Houston-The Woodlands-Sugar Land (population 6.9 million), San Antonio-New Braunfels (population 2.5 million) and Austin-Round Rock (population 2.1 million).3 Other metropolitan areas in Texas are relatively small and isolated cities with less than one million people.

PUMA-level data on population; average Household income; per- centage of residents who were Hispanic or Black; and percentage of res- idents with age above 65 were obtained from the 2010 to 2016 American Community Surveys.

Data analysis

Geographic maps (Fig. 1) in Texas and four major metropolitan areas were drawn to show emergency facility locations in 2016. To illustrate the growth trends in Texas, we list the numbers of hospital-based EDs and FrEDs from 2010 to 2016 and discuss the closures or acquisitions during the study period. Descriptive statistics are reported on the total

Information for hospital-based EDs and their annual visit volumes

were obtained from the American Hospital Association’s (AHA) Annual Survey from 2010 to 2016. For hospital EDs, the number of annual visits also included visits to affiliated satellite FrEDs. Military/behavioral hos- pitals were excluded from the sample. A total of 370 hospitals remained open during the study period.

1 Reasons for missing include: the number of cases is too few to report; results are based on a shorter time period than required; results are not available for this reporting period.

2 2017 United States Census Bureau. Metropolitan statistical area is defined as one or more adjacent counties or county equivalents that have at least one urban core area of at least 50,000 population.

3 San Antonio-New Braunfels and Austin-Round Rock are contiguous to each other.

Fig. 1. Location of facilities providing emergency care in Texas, 2016 (ArcGIS). Source: The analysis of data from the American Hospital Association and the Texas Department of State Health Services. NOTE: There were 420 hospital-based emergency departments (black cross), 275 independent freestanding emergency departments (red dot), and 120 hospital satellite freestanding emergency departments (blue dot) in 2016. The grey areas are four biggest metropolitan areas in Texas, with the represented cities Dallas (left-top), Houston (right-bottom), Austin and San Antonio (left bottom, together).

number of visits to Hospital EDs and visits per person in Texas from 2010 to 2016. Means of the dependent variables are listed as well.

We estimated a Multivariate linear regression model with hospital fixed effects to examine which factors were most closely associated with the changes in hospital ED outcomes. Hospital fixed effects were included to control for systematic differences across hospitals that are constant across years. To avoid multicollinearity, demographic charac- teristics with variance inflation factors N2.5 were removed from the re- gressions. Year indicator variables were included in the analyses to account for general trends in hospital ED outcomes over time.

To allow for differences in hospital sizes, wait time, discharge time and LWBS rate were weighted by hospital visit volume in the regres- sions. All standard errors were clustered at the hospital level. A two- tailed p value of b0.05 was considered statistically significant.

In cases where the coefficients on FrED counts were statistically in-

significant, Power calculations [18,19] were performed to verify that the sample was sufficiently large enough to avoid type II errors of incor- rectly accepting the null hypothesis. We conducted a sensitivity analysis for ED visits that excluded hospitals with satellite FrED(s) open in that year to assess the effects of owning satellite FrEDs. We also performed three additional analyses: 1) using a 3-mile distance band from each hospital to define local markets; 2) using non-weighted specifications of the regressions for wait time, discharge time and LWBS rate; 3) sep- arating hospitals in the four major metropolitan areas versus non-major metropolitan areas.

The regressions were estimated using Stata (version 15.1), and loca- tional information was mapped by ArcMap (version 10.5).

the state. Most of the satellite FrEDs were built relatively close to their parent hospitals.

A total of 288 independent FrEDs opened in Texas between 2010 and 2016, while 68 independent FrEDs closed before the end of 2016. The number of independent FrEDs accelerated in Texas between 2014 and 2016 (Table 1 and Appendix Fig. 1). Though satellite FrEDs were avail- able before the licensing Act in Texas, their presence also increased dra- matically between 2010 and 2016; more than 100 new satellite FrEDs were opened during this time period.

3.2. Descriptive analysis

The descriptive statistics in Table 2 demonstrate that average hospi- tal-based ED visits increased over the 7-year study period. The annual growth rate of visits was 2.3%. Wait times in hospital-based EDs and overall LWBS rates decreased from 2012 to 2016. However, the dis- charge time changed only slightly.

3.3. Regression results

The results in Table 3 reveal that the annual number of visits to hos- pital EDs was not associated with the entry of FrEDs in the same PUMA. Neither the total number of FrEDs, nor the separate counts of

Table 1

Numbers of hospital-based emergency departments and freestanding emergency depart- ments from 2010 to 2016.

3. Results

Year

Hospital-based EDs

Independent FrEDs

Satellite FrEDs

2010

431

22

12

3.1. Geographic analysis

2011

427

28

20

2012

427

52

31

Fig. 1 shows the four major metropolitan areas in Texas, covering

2013 426 88 39

2014 422 139 48

204 out of 275 independent FrEDs and 100 out of 120 satellite FrEDs

2015

417

208

66

in 2016. Independent FrEDs and satellite FrEDs were clustered around

2016

420

275

120

major metropolitan centers: Houston, Dallas-Fort Worth, San Antonio and Austin. However, hospital-based ED were scattered throughout

Note: The number of independent FrEDs and satellite FrEDs includes newly entered FrEDs in the same year. Satellite FrEDs are hospital-owned freestanding EDs.

Table 2

Hospital-based emergency department visits, wait time, discharge time, and LWBS rate in Texas, from 2010 to 2016.

Year

Total visits (Texas)

Visits/Pop (Texas)

Avg. ED visits

Wait time

Discharge time

LWBS

rate

(N = 370)

(N =

(N = 276)

(N =

276)

270)

2010

10,403,602

0.412

26,683

2011

10,606,956

0.413

27,517

2012

11,021,832

0.423

28,793

31.4

139.1

2.7

2013

11,061,800

0.418

28,560

29.4

137.8

2.2

2014

11,168,465

0.414

29,657

26.7

142.8

2.3

2015

11,464,788

0.417

29,829

24.8

141.9

2.1

2016

11,824,246

0.424

29,361

22.3

140.7

2.0

Note: The average hospital-based emergency department visits, wait time, discharge time and left without being seen (LWBS) rate are based on hospitals in the sample for regres- sions. Center for Medicare & Medicaid Services started collecting Hospital Emergency De- partment Timely and Effective care measurements in 2012.

independent FrEDs and satellite FrEDs were associated with the number of hospital-based ED visits. There was also no significant association be- tween hospital-based ED wait time, discharge time, or LWBS rates and the presence of FrEDs in the same PUMA. Hospitals that opened satellite

Table 3

Estimates of the changes in hospital-based emergency departments, associated with nearby competitors and various factors in the same Public Use Microdata Area in Texas.

Variables

(1)

(2)

(3)

(4)

(5)

Visit

Visit

Wait time

Discharge

LWBS rate

volume

volume

time

Owns SEDs

0.165***

0.165***

-0.204*

-0.0525*

-0.0561

(0.0380)

(0.0380)

(0.0986)

(0.0259)

(0.0952)

# FrEDs in the

0.000904

0.00787

0.00302

-0.00462

PUMA

(0.0165)

(0.0241)

(0.00879)

(0.0263)

# IFEDs in the

0.00155

FrEDs had visit volumes that were 16.5% higher than hospitals that did not open satellite FrEDs (p b 0.01). The ownership of satellite FrEDs was also associated with 20.4% lower wait times and 5.3% lower dis- charge times. However, these associations were precisely estimated only for hospitals in non-major metropolitan areas (Table 4). Owning satellite FrEDs in major metropolitan areas was not associated with im- provement of hospital efficiency (Table 4 column 2-4).

The year indicator variables in Table 3 illustrate the trends in hospi-

tal visits and ED congestion over time. ED visits increased in each year compared to the base year 2010. The higher rates were statistically sig- nificant (p b 0.01), except for 2016. Contrary to visit volume, wait times and LWBS rates decreased significantly over time in spite of increased visits. However, the length of visit for discharged patients did not change. Changes in demographic characteristics were not associated with hospital ED visits.

The results were similar when local markets were defined using a 3- mile distance band from each hospital (Appendix Table 1). Non- weighted specifications of the regressions also yielded similar conclu- sions (Appendix Table 2). The absence of an association between the number of FrEDs and the number of hospital ED visits and other mea- sures of ED congestion remained when the sample was restricted to hospitals that did not have any satellite FrED open in a given year. Power calculations indicated that a sample size of 102 would have been sufficient to detect a 1% drop in the coefficients on the numbers of FrEDs in each PUMA with a p-value b 0.05 and a power level at 0.8 (Appendix Table 3).

  1. Discussion

In this study, we found no evidence that the entry of FrEDs was asso- ciated with reduced ED congestion in nearby hospitals. Our analysis of a large sample of hospital EDs in Texas finds that the entry of competitor FrEDs nearby did not help hospital-based EDs reduce visit volume, wait

time, length of visit or patient LWBS rate. By including hospital and year

PUMA

# SEDs in the PUMA

Avg. HH

income/10k

(0.0149)

(0.0151)

(0.0433)

(0.0122)

(0.0354)

Pop Density/10k

-0.660

-0.658

-0.708

0.235

1.425

(1.088)

(1.090)

(1.115)

(0.334)

(0.794)

% Hispanic

-0.684

-0.684

0.144

-0.155

0.133

(0.398)

(0.399)

(0.851)

(0.358)

(0.973)

% Black

-0.542

-0.542

-0.848

0.0812

-1.006

(0.320)

(0.320)

(0.891)

(0.322)

(1.135)

% Age above 65

1.540

1.538

-0.629

-0.392

-1.562

year = 2011

year = 2012

year = 2013

(0.898) 0.0441** (0.0150)

0.0671***

(0.0156) 0.0608**

(0.902) 0.0440** (0.0150)

0.0672***

(0.0157) 0.0610**

(1.563)

-0.0645*

(0.517)

-0.0124

(1.376)

-0.135***

(0.0232)

(0.0236)

(0.0281)

(0.00971)

(0.0420)

year = 2014

0.0588*

0.0591*

-0.250***

0.0224

-0.116*

(0.0232)

(0.0239)

(0.0442)

(0.0161)

(0.0500)

year = 2015

0.0717**

0.0719**

-0.391***

0.0139

-0.164**

(0.0264)

(0.0269)

(0.0694)

(0.0217)

(0.0583)

year = 2016

0.0397

0.0401

-0.485***

-0.00186

-0.229**

(0.0281)

(0.0287)

(0.0813)

(0.0246)

(0.0734)

Constant

10.95***

10.95***

3.959***

5.088***

0.846

(0.151)

(0.151)

(0.982)

(0.394)

(1.009)

Hospitals

370

370

276

276

270

Observations

2590

2590

1380

1380

1350

Year Fixed Effect

Yes

Yes

Yes

Yes

Yes

Hospital Fixed

Yes

Yes

Yes

Yes

Yes

Effect Weights

No

No

ED visits

ED visits

ED visits

(0.0178)

-0.00378

(0.0486)

0.00568 0.00561 0.0137 -0.00319 -0.0367

fixed effects in the regressions, the coefficient estimates measure the as- sociation between within-hospital increases in the number of FrEDs nearby and hospital outcomes, controlling for confounding that could result from comparing changes in outcomes across hospitals with differ- ent market characteristics. This finding suggests that FrEDs are not com- plete substitutes for care delivered by traditional hospital-based EDs. Instead, FrEDs are increasing the total amount of emergency care deliv- ered to the community.

Hospitals that opened satellite FrEDs had significantly higher visit volumes. The AHA does not require hospitals to report separate counts of ED visits to their hospital facility versus satellite FrEDs they may own, so both visit types are included in ED visit volumes for hospitals with satellite FrEDs. The indicator variable for ownership of satellite FrEDs in the regression therefore adjusts for the expected higher ED visit volume for hospitals with satellite FrEDs. Operating satellite FrEDs may provide hospitals a way to attract patients and gain market share [20]. During the study period, many hospitals built new satellite FrEDs, acquired independent FrEDs, or affiliated with independent FrEDs in local markets, including Houston Methodist, CHI St. Luke’s Health, Texas Health Resource [21] and Adeptus Health.

The regression results find no association between satellite FrED ownership and hospital ED efficiency in major metropolitan areas. This finding suggests that the congestion problem remained for ED ser- vices in big cities, despite the fact that most FrEDs entered in those met- ropolitan areas where emergency service was already available. However, the ownership of satellite FrEDs was associated with im- proved ED efficiency in non-major metropolitan areas. The decreased

Notes: SED and IFED are short for satellite freestanding emergency department and inde- pendent freestanding emergency department. The number of FrEDs (satellite FrEDs or in- dependent FrEDs) represents facilities open for 1+ calendar years. Owns SEDs: =1 if hospital owns satellite emergency department(s); =0 otherwise. ***p b 0.001, **p b 0.01, *p b 0.05. Standard errors, adjusted for clustering at the hospital level, are reported in the parentheses.

wait times, length of visit and LWBS rates suggested satellite FrEDs in

small cities served as substitutes to their parent hospitals. To ensure ap- propriate use of emergency services and avoid over-payment for low- acuity emergency visits, the 2018 MedPAC report [15] suggested that Medicare payment rates for visits to satellite FrEDs that are within

Table 4

Estimates of the changes in hospital-based emergency departments, associated with nearby competitors and various factors in the same Public Use Microdata Area in Texas (Major Met- ropolitan Areas vs. Non-major Metropolitan Areas).

Variables Major Metropolitan Areas in Texas Non-major Metropolitan Areas in Texas

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Visit volume

Wait time

Discharge time

LWBS rate

Visit volume

Wait time

Discharge time

LWBS rate

Owns SEDs

0.109*

-0.102

-0.0165

0.0772

0.242***

-0.432*

-0.124*

-0.310**

(0.0455)

(0.102)

(0.0279)

(0.119)

(0.0637)

(0.198)

(0.0496)

(0.108)

# FrEDs in the PUMA

-0.0169

-0.0344

-0.0142

0.0146

0.0101

0.0368

0.0189

-0.0177

(0.0242)

(0.0472)

(0.0142)

(0.0425)

(0.0237)

(0.0291)

(0.0119)

(0.0372)

Avg. HH income/10k

0.000647

0.0125

-0.0149

-0.0442

-0.0187

0.0517

0.0435

0.0921

(0.0157)

(0.0511)

(0.0124)

(0.0441)

(0.0217)

(0.0645)

(0.0287)

(0.0633)

Pop Density/10k

-1.463

-0.438

0.0918

1.178

1.882

-0.264

1.374

7.935

(1.146)

(1.118)

(0.311)

(0.933)

(1.092)

(3.864)

(0.842)

(4.581)

% Hispanic

-1.054

0.177

-0.501

-0.224

-0.109

0.123

0.727

1.187

(0.659)

(1.043)

(0.384)

(1.295)

(0.235)

(1.189)

(0.723)

(1.386)

% Black

-0.529

-0.768

0.0368

-0.187

-0.564

-0.984

0.369

-1.225

(0.368)

(1.291)

(0.330)

(1.291)

(0.752)

(1.163)

(0.705)

(1.728)

% Age above 65

2.600

-0.105

-0.0173

-2.343

0.497

-0.395

0.0675

3.572

(1.520)

(2.027)

(0.589)

(1.914)

(0.826)

(2.730)

(1.050)

(2.574)

year = 2011

0.101**

0.00994

(0.0344)

(0.00808)

year = 2012

0.126***

(0.0290)

0.0382*

(0.0171)

year = 2013

0.132**

-0.0360

-0.0138

-0.154*

0.0395

-0.105**

-0.0114

-0.163***

(0.0464)

(0.0381)

(0.0119)

(0.0693)

(0.0241)

(0.0407)

(0.0162)

(0.0465)

year = 2014

0.138***

-0.277***

0.0158

-0.209**

0.0410

-0.207***

0.0276

-0.0703

(0.0399)

(0.0606)

(0.0191)

(0.0695)

(0.0284)

(0.0601)

(0.0240)

(0.0635)

year = 2015

0.152***

-0.410***

0.0302

-0.224**

0.0659*

-0.374***

-0.0227

-0.210**

(0.0468)

(0.0995)

(0.0252)

(0.0854)

(0.0333)

(0.0836)

(0.0330)

(0.0777)

year = 2016

0.132*

-0.509***

0.0104

-0.328***

0.0202

-0.490***

-0.0496

-0.241**

(0.0525)

(0.109)

(0.0277)

(0.100)

(0.0307)

(0.104)

(0.0417)

(0.0845)

Constant

10.73***

4.913***

6.137***

2.764***

11.10***

3.828*

3.721***

-3.494

(0.323)

(1.078)

(0.252)

(0.849)

(0.204)

(1.725)

(1.016)

(2.432)

Hospitals

156

138

138

139

214

138

138

131

Observations

1092

690

690

695

1498

690

690

655

Year Fixed Effect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Hospital Fixed Effect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Weights

No

ED visits

ED visits

ED visits

No

ED visits

ED visits

ED visits

Major Metro

Yes

Yes

Yes

Yes

No

No

No

No

Notes: Major metropolitan areas are Houston, Dallas-Fort Worth, San Antonio and Austin Metropolitan Statistical Areas and non-major metropolitan areas are the remaining areas in Texas. SED is short for satellite freestanding emergency department. The number of FrEDs (satellite FrEDs or independent FrEDs) represents facilities open for 1+ calendar years. Owns SEDs: =1 if hospital owns satellite emergency department(s); =0 otherwise. ***p b 0.001, **p b 0.01, *p b 0.05. Standard errors, adjusted for clustering at the hospital level, are reported in the parentheses.

6 miles of a hospital ED be reduced by 30%. If this reduction reduces the propensity for hospitals to open satellite FrEDs within 6 miles of their main location in large metropolitan areas, the results from this study suggest that this action would not have a detrimental effect on hospital ED efficiency.

The descriptive statistics and year indicator variables in our analysis

indicate that wait times and LWBS rates in the hospital-based EDs de- creased during the study period, regardless of the number of FrEDs that entered the local market. Hospitals might have made efforts to re- duce wait times and LWBS rates, because these measures are featured in the CMS’s Hospital Compare survey. Hospitals often advertise their cur- rent ED wait times on their website to attract patients. However, our study showed the amount of time until patients are discharged did not change significantly. Therefore, concerns regarding the availability of prompt emergency care may remain in spite of the entry of FrEDs.

Our results might not be applicable to FrEDs in rural areas. One study

[22] in Maryland showed that the opening of a FrED in Queenstown was associated with a decrease in ambulance turnaround time and shorter out-of-service intervals. This isolated FrED had no other EDs within 20 miles, and it was included in the ambulance system and received local government funds. Our study focused on all FrEDs in Texas, where most are located in major metropolitan areas (Graph 1). In Texas, FrEDs were more likely to locate in higher income neighborhoods [4], where emergency service was already available. The current situa- tion in Texas may not meet the goal to “Improve efficiency and preserv- ing access to emergency care in rural areas” [23].

  1. Limitations

Our research has a number of limitations. The first is the inability to distinguish the visits in main hospital EDs from those in a hospital’s sat- ellite FrEDs. The regression includes an indicator variable for ownership of satellite FrEDs to account for the increase in ED visits resulting from satellite FrED sites. Though there was a significant increase in visits as- sociated with owning satellite FrEDs, one cannot conclude definitively that the increased visits were fully contributed by the satellite FrEDs. We also cannot rule out the possibility that the inclusion of satellite FrED visits in total visits was masking a change in visits to the main hos- pital-based EDs. A previous study suggested that a health care system with a tertiary care hospital in Ohio that opened two satellite FrEDs

9.6 and 12 miles away experienced a significant drop in ED admission rates and volume in its main hospital-based ED, but the overall ED vol- ume increased for the health care system [24].

The AHA survey does not ask hospitals about their ED capacity or pa- tient casemix. Therefore, one cannot determine whether ED visit vol- ume was at hospital capacity. In addition, without the availability of patient-level data, we cannot observe changes of patient casemix in each hospital. It is possible that the entry of FrEDs changed the patient casemix in traditional EDs by attracting low-acuity and private-insured patients away from hospitals, making hospitals financially vulnerable [25].

The provider data only contains the locations of hospital-based EDs and two types of FrEDs. We do not have entry and exit data of urgent

care centers, or physician offices. If available, the number of those pro- viders in the markets could be another explanatory variable in our anal- yses that influences market competition. We also lack data on the number of visits and their characteristics for FrEDs. The shortcoming prevents a direct comparison of visit volume and services between hos- pital EDs and FrEDs.

Finally, we do not have detailed billing information from hospitals and their satellite FrEDs when several belong to a large hospital system. We cannot validate which hospital campus was responsible for patients in their satellite FrEDs. We manually assigned each satellite FrED to its closest parent hospital(s) if there was more than one campus under the hospital system. For example, the Houston Methodist satellite FrED in the Sugar Land area, which is more than 20 miles away from downtown Houston, was assigned to the Houston Methodist- Sugar Land campus.

  1. Conclusion

Our research shows that the entry of FrEDs was not associated with reduced ED congestion in nearby hospitals. The competitor FrEDs in local markets neither reduce patient visit volume, nor improve timeli- ness of care in hospital-based EDs. This study also found that opening hospital-affiliated satellite FrEDs increased owner hospitals’ visits, but it did not help with the congestion problems in their main hospitals in major metropolitan areas. However, the ownership of satellite FrEDs in small cities might help improve hospital efficiency. These findings convey valuable information for the current debate over the cost and regulations towards FrEDs in the U.S. Regulators must closely consider how to implement effective low-cost solutions to ED crowding.

Future research should examine how FrEDs impact patient out- comes and Healthcare costs within a community, or how patient casemix changes within hospital EDs. Our work also raises questions re- garding the benefits from the patients’ perspective, and how the FrEDs will respond to a reduction in insurance reimbursements.

Author contributions

Concept and design: YX, VH Acquisition of the data: YX, VH. Analysis: YX.

Interpretation of the data: YX. Drafting of the manuscript: YX.

Critical revision of the manuscript: VH. Statistical expertise: VH.

Declaration of Competing Interest

YX reports no conflict of interest. VH reports that she is a volunteer member of the Board at Community Health Choice.

Supplementary Materials

Supplementary tables to this article can be found online at https:// doi.org/10.1016/j.ajem.2019.05.020.

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