Factors associated with Interhospital transfers of emergency general surgery patients from emergency departments

Abstract

BACKGROUND

Emergency general surgery (EGS) conditions account for over 3 million or 7.1% of hospitalizations per year in the US. Patients are increasingly transferred from community emergency departments (EDs) to larger centers for care, and a growing demand for treating EGS conditions mandates a better understanding of how ED clinicians transfer patients. We identify patient, clinical, and organizational characteristics associated with interhospital transfers of EGS patients originating from EDs in the United States.

METHOD

We analyze data from the Agency for Healthcare Research and Quality Nationwide Emergency Department Sample (NEDS) for the years 2010–2014. Patient-level sociodemographic characteristics, clinical factors, and hospital-level factors were examined as predictors of transfer from the ED to another acute care hospital. Multivariable logistic regression analysis includes patient and hospital characteristics as predictors of transfer from an ED to another acute care hospital.

RESULTS

Of 47,442,892 ED encounters (weighted) between 2008–2014, 1.9% resulted in a transfer. Multivariable analysis indicates that men (Odds ratio (OR) 1.18 95% Confidence Interval (95% CI) 1.16–1.21) and older patients (OR 1.02 (95% CI 1.02–1.02)) were more likely to be transferred. Relative to patients with private health insurance, patients covered by Medicare (OR 1.09 (95% CI 1.03–1.15) or other insurance (OR 1.34 (95% CI 1.07–1.66)) had a higher odds of transfer. Odds of transfer increased with a greater number of comorbid conditions compared to patients with an EGS diagnosis alone. EGS diagnoses predicting transfer included resuscitation (OR 36.72 (95% CI 30.48–44.22)), cardiothoracic conditions (OR 8.47 (95% CI 7.44–9.63)), intestinal obstruction (OR 4.49 (95% CI 4.00–5.04)), and conditions of the upper gastrointestinal tract (OR 2.82 (95% CI 2.53–3.15)). Relative to Level I or II trauma centers, hospitals with a trauma designation III or IV had a 1.81 greater odds of transfer. Transfers were most likely to originate at rural hospitals (OR 1.69 (95% CI 1.43–2.00)) relative to urban non-teaching hospitals.

CONCLUSION

Medically complex and older patients who present at small, rural hospitals are more likely to be transferred. Future research on the unique needs of rural hospitals and timely transfer of EGS patients who require specialty surgical care have the potential to significantly improve outcomes and reduce costs.

1. Introduction

Emergency general surgery (EGS) involves treating common conditions such as complicated diverticulitis, intestinal obstruction, and appendicitis.¹ These conditions account for over 3 million (or 7.1%) hospitalizations per year and have increased 150% over the last 10 years.^2,3 As the population ages and access to emergency surgical care declines, patients are increasingly transferred to larger centers for care.^1,2,4,5 Most of these transfers originate from smaller community or freestanding emergency departments (EDs) that are challenged by limited capacity and resources to care for these patients.⁶ The declining availability of on call specialists as well as the consolidation of healthcare services will further lead to increased transfers. Consequently, the growing demand for treating these conditions and disparities in access to these services mandates a better understanding of how ED clinicians transfer patients.

Despite the need for community hospitals to transfer patients, there are no clear guidelines to inform either patient selection or the information that should be included in hospital communications to ensure high quality handoffs. This gap in guidance has led to inconsistent transfer decision making and worse outcomes for EGS patients who are transferred, creating an imperative for further study.^2,4,7 Prior research suggests that 20% of surgical transfers are deemed potentially unnecessary either because patients did not need specialty surgical intervention or because patients were too sick to benefit from a higher level of care.⁸ At the same time, delays in transfers have been shown to lead to worse outcomes for patients. This, coupled with recent evidence that suggests that on average EGS patients admitted to centers with high quality trauma programs or to hospitals with high volume EGS admissions have lower mortality rates, suggests a need for a better approach to identify patients in need of transfer and that they end up in an appropriate center capable of treating these patients succesfully.^9,10 EGS patients have the potential to benefit from transfer protocols designed to facilitate timely transfer and streamline interfacility communication to confer better outcomes, much in the way that trauma and myocardial infarction patients have.^11–13

We identify clinical and organizational characteristics associated with interhospital transfers of EGS patients originating from the ED. We utilize National Emergency Department Sample (NEDS) data, which, to the best of our knowledge, have not been used previously to characterize patient transfers from a clinical decision-making perspective.¹⁴ We anticipate that our results will help to inform the development of protocols that facilitate the early identification of EGS patients requiring transfer.

2. Methods

2.1. Study Design and Setting

We analyzed data from the Agency for Healthcare Research and Quality Nationwide Emergency Department Sample (NEDS) for the years 2010–2014. We chose NEDS to answer our question of interest because it is the largest all-payer emergency department (ED) database in the United States and is designed to produce national estimates of hospital-based ED visits. The NEDS is a Healthcare Cost and Utilization Project database and is created by sampling the State Inpatient Databases and the State Emergency Department Databases. The NEDS includes information on clinical and resource relevant variables and contains approximately 31 million ED visits per year (unweighted). We identified adult patients (≥18 years old) with EGS conditions using American Association for the Surgery of Trauma (AAST) ICD-9-CM diagnosis codes (n=47,442,892).^1,15 We used these data to describe referring hospital and patient characteristics, employing weights to provide national estimates. The discharge weights are provided with the data and were calculated by stratifying NEDS hospitals on the variables used to create the sample: Geographic region, trauma center designation, urban/rural location, teaching status, and ownership.¹⁴ A weight was calculated for each stratum by dividing the number of national ED visits in that stratum (from American Hospital Association data) by the number of NEDS visits in the stratum. The weighted estimates thus reflect the number of ED visits nationwide.

2.2. Measurements

We characterized patients based on EGS diagnosis indicator variables defined by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes categorized into the following diagnosis or systems-based groups: resuscitation, abdominal conditions, upper gastrointestinal tract, intestinal obstruction, hepatic-pancreatic-biliary, colorectal, hernias, soft tissue, vascular, cardiothoracic, and other. These categories are described in detail elsewhere.¹⁶ Patients’ sociodemographic characteristics included sex, age, insurance type (Medicare, private insurance, Medicaid, self pay, no charge, other), and the quartile of the ZIP code-level median income for the patient’s residence. Patient-level clinical characteristics included Charlson comorbidity index, any surgical procedure performed before transfer (defined using ICD-9-CM procedure codes), and whether the admission occurred on a weekend.^3,15,17,18 Hospital-level characteristics included total number of ED visits (irrespective of diagnosis), trauma center status, rural or urban location, teaching status, region of the US (northeast, south, midwest, west), and hospital ownership (government, non-profit, private/investor-owned).

2.3. Outcomes

Our primary outcome variable was any transfer to an acute care hospital. Patient-level sociodemographic and clinical factors as well as hospital-level factors were examined as predictors of transfer from the ED to another acute care hospital. Missing values were excluded listwise.

2.4. Analysis

We report summary statistics for patient and hospital characteristics as percentages for categorical variables and as means/standard errors or medians/interquartile ranges for continuous variables. All estimates are weighted to be nationally representative.¹⁴ We describe bivariate differences between patients who were transferred and patients who were not transferred using Chi-squared analyses, t-tests, and Wilcoxon-Mann-Whitney tests as appropriate. Multivariable analysis includes patient and hospital characteristics as predictors of transfer from an ED to another acute care hospital. We use a multilevel, logistic regression model to assess predictors of transfer. Our approach uses a competing risk analysis to account for death and transfer to non-acute care facilities.¹⁹ In analyses that assess EGS diagnosis groups that predict transfer, absence of the diagnosis is used as the reference. Data analysis was performed using SAS 9.2 software. This study was deemed exempt by the University of Wisconsin-Madison Institutional Review Board.

3. Results

Of 47,442,892 ED encounters (representing approximately 5% of ED visits, weighted) for EGS conditions between 2008–2014, 1.9% resulted in a transfer. Bivariate analysis is summarized in Table 1. On average, transferred patients were older than patients who were not transferred (56 years old vs. 42 years old; p<.0001) and were more likely to be covered by Medicare. Transferred patients also had a greater comorbidity burden than patients who were not transferred. The most common EGS diagnoses in the overall ED patient population were general abdominal conditions, soft tissue conditions, and upper gastrointestinal tract conditions. Upper GI tract and hepatobiliary conditions were more prevalent in the transferred patient population (upper GI 21% vs. 3%; hepatobiliary 14% vs. 4% p<.0001).

Table 1.

Characteristics of Emergency General Surgery Patients Transferred to Acute Care Facilities in the Nationwide Emergency Department Sample 2010–2014

	Not Transferred (n=46534407)	Transferred (n=908485)	P value
Age (years, mean (standard error))	42.3 (0.05)	57.0 (0.42)	<0.0001
Gender, % (n)
Female	58.4 (27166343)	52.6 (477748)	<0.0001
Day of the week of admission, % (n)
Monday-Friday	72.6 (33791032)	71.1 (645704)	<0.0001
Saturday-Sunday	27.4 (12743375)	28.9 (262781)
Primary payer, % (n)
Medicare	18.7 (8723865)	45.2 (410385)	<0.0001
Medicaid	23.5 (10937725)	14.2 (129346)
Private insurance	30.3 (14091917)	26.5 (240524)
Self-pay	22.3 (10372674)	9.0 (81375)
No charge	1.0 (481699)	1.0 (7556)
Other	4.1 (1926527)	4.3 (39298)
Median household income national quartile, % (n)
0–25th	34.2 (15931095)	35.7 (324007)	<0.0001
26th–50th	27.7 (12896753)	34.4 (312876)
51st–75th	22.4 (10420030)	19.5 (177572)
76th–100th	15.7 (7286530)	10.4 (94029)
Charlson Comorbidity Index, % (n)
0	84.4 (39108948)	68.2 (619674)	<0.0001
1	11.8 (5493910)	17.9 (163039)
2	2.7 (1234985)	7.6 (69390)
3	1.5 (696564)	6.2 (56381)
Diagnosis group description, % (n)
Hepatic-pancreatic-biliary	4.3 (2021676)	13.6 (123419)	<0.0001
Upper gastrointestinal tract	3.3 (1538094)	21.0 (190672)
Soft tissue	32.0 (14902138)	14.8 (134285)
Colorectal	7.0 (3241168)	6.0 (54403)
Intestinal obstruction	0.6 (294591)	9.7 (88349)
General abdominal conditions	50.0 (23253145)	28.6 (259964)
Vascular	0.6 (285903)	2.4 (21762)
Cardiothoracic	0.1 (34192)	1.2 (10691)
Hernias	1.9 (875857)	1.9 (17713)
Other	0.2 (84989)	0.3 (2890)
Resuscitation	0.0 (4337)	0.3 (2655)

Hospital characteristics are summarized in Table 2. Transferred patients were less likely to originate at a Level I or II trauma center (p<0.001). Lower volume EDs were more likely to transfer patients (p<0.0001). Transfers were most common in the midwestern US, and rural hospitals were most likely to transfer patients followed by urban non-teaching hospitals (p<0.0001). Hospital ownership was not significantly associated with transfer.

Table 2.

Characteristics of the Hospitals that Admitted Emergency General Surgery Patients Transferred to Acute Care Facilities in the Nationwide Emergency Department Sample 2010–2014

	Not Transferred (n=46534407)	Transferred (n=908485)	P value
Trauma Level			<0.0001
I or II	27.8 (12951821)	7.2 (65488)
≥ III	72.2 (33582586)	92.8 (842996)
Annual visits, % (n)
<25K	17.5 (8132878)	59.3 (538967)	<0.0001
25K–50K	31.9 (14821622)	23.4 (212193)
50001–75K	25.5 (11873659)	10.0 (90475)
>75K	25.2 (11706247)	7.4 (66850)
Region of hospital, % (n)
Northeast	17.6 (8213303)	9.8 (88890)	<0.0001
Midwest	22.9 (10638692)	41.2 (379566)
South	40.4 (18798632)	30.0 (270695)
West	19.1 (8883780)	18.6 (169333)
Control/ownership of hospital, % (n)
Government, nonfederal	6.7 (3131485)	14.9 (135732)	<0.0001
Government or private, collapsed	64.5 (29996713)	44.9 (408324)
Private, non-profit	16.6 (7738609)	16.8 (153043)
Private, collapsed	3.8 (1789309)	15.7 (143071)
Private, investor-owned	8.3 (3878291)	7.5 (68314)
Location/teaching status of hospital, % (n)
Rural	16.8 (7821583)	50.5 (458419)	<0.0001
Urban nonteaching	40.0 (18590774)	35.0 (317885)
Urban teaching	43.2 (20122050)	14.5 (132180)

The results of our multivariable analysis are summarized in Table 3. Patients’ sociodemographic characteristics were significantly associated with odds of transfer. Men were more likely to be transferred (Odds ratio (OR) 1.18 95% Confidence Interval (95% CI) 1.16–1.21), as were older patients (OR 1.02 (95% CI 1.02–1.02)). Relative to patients with private health insurance, patients covered by Medicare (OR 1.09 (95% CI 1.03–1.15) or other insurance (OR 1.34 (95% CI 1.07–1.66)) had a higher odds of transfer. Relative to patients in the lowest income zip codes, patients residing in zip codes in the two highest household income groups were less likely to be transferred. Odds of transfer increased with a greater number of comorbid conditions, with patients with three or more comorbidities significantly more likely to be transferred (OR 2.30 (95% CI 2.18–2.43)) compared to patients with an EGS diagnosis alone; the odds of transfer for patients with 2 (OR 1.76 (95% CI 1.68–1.84)) or 1 (OR 1.25 (95% CI 1.20–1.29)) comorbidity(ies) were somewhat attenuated. From a clinical standpoint, EGS diagnoses that led to transfer most frequently included resuscitation (OR 36.72 (95% CI 30.48–44.22)), cardiothoracic conditions (OR 8.47 (95% CI 7.44–9.63)), intestinal obstruction (OR 4.49 (95% CI 4.00–5.04)), and conditions of the upper gastrointestinal tract (OR 2.82 (95% CI 2.53–3.15)). Weekend admissions were slightly more likely to result in transfer (OR 1.03 (95% CI 1.01–1.04).

Table 3.

Multivariable Analysis Predicting Transfer of Emergency General Surgery Patients to Acute Care Hospitals in the Nationwide Emergency Department Sample 2010–2014

Parameter	Unadjusted Odds Ratio	Unadjusted 95% CI	Adjusted Odds Ratio	Adjusted 95% CI
Gender
Male	1.27	1.23–1.30	1.18	1.16–1.21
Female	1.00		1.00
Age	1.040	1.038–1.042	1.023	1.021–1.024
Expected primary payer
Medicare	2.76	2.48–3.07	1.09	1.03–1.15
Medicaid	0.69	0.63–0.77	0.95	0.87–1.04
Self-pay	0.46	0.40–0.53	0.71	0.62–0.80
No charge	0.92	0.42–2.03	1.72	0.76–1.89
Other	1.20	0.97–1.47	1.34	1.07–1.66
Private insurance	1.00		1.00
Household income of patient’s zip code (median)
26th to 50th percentile	1.19	1.08–1.31	0.96	0.88–1.05
51st to 75th percentile	0.84	0.75–0.93	0.89	0.81–0.97
76th to 100th percentile	0.64	0.53–0.77	0.82	0.69–0.99
0–25th percentile	1.00		1.00
Charlson Comorbidity Index
1	1.87	1.78–1.97	1.25	1.20–1.29
2	3.55	3.31–3.80	1.76	1.68–1.84
3	5.11	4.74–5.51	2.30	2.18–2.43
0	1.00		1.00
EGS diagnosis group
Resuscitation Yes	83.8	73.3–95.8	36.72	30.48–44.22
Resuscitation No	1.00		1.00
General abdominal conditions Yes	0.40	0.37–0.44	0.40	0.35–0.46
General abdominal conditions No	1.00		1.00
Intestinal obstruction Yes	16.91	15.88–18.01	4.49	4.00–5.04
Intestinal obstruction No	1.00		1.00
Upper gastrointestinal tract Yes	7.77	7.32–8.25	2.82	2.53–3.15
Upper gastrointestinal tract No	1.00		1.00
Hepatic-pancreatic-biliary Yes	3.46	3.29–3.65	1.92	1.72–2.15
Hepatic-pancreatic-biliary No	1.00		1.00
Colorectal Yes	0.85	0.83–0.88	0.47	0.42–0.53
Colorectal No	1.00		1.00
Hernias Yes	1.04	0.99–1.09	0.56	0.50–0.63
Hernias No	1.00		1.00
Soft tissue Yes	0.37	0.35–0.39	0.31	0.27–0.35
Soft tissue No	1.00		1.00
Vascular Yes	3.97	3.74–4.22	1.77	1.58–1.98
Vascular No	1.00		1.00
Cardiothoracic Yes	16.2	14.9–17.6	8.47	7.44–9.63
Cardiothoracic No	1.00		1.00
Day of Admission
Admitted Saturday-Sunday	1.08	1.07–1.09	1.03	1.01–1.04
Admitted Monday-Friday	1.00		1.00
Total number of visits	1.000	1.000–1.000	1.000	1.000–1.000
Trauma Level
≥III	4.96	4.03–6.11	1.81	1.38–2.37
I or II	1.00		1.00
Hospital Region
Midwest	3.30	2.68–4.06	2.06	1.56–2.72
South	1.33	1.13–1.57	1.08	0.79–1.46
West	1.76	1.47–2.12	1.27	0.97–1.66
Northeast	1.00		1.00
Hospital Ownership
Government, nonfederal	3.18	2.73–3.72	1.22	0.99–1.52
Private, invest-own	1.29	1.1–1.52	0.84	0.65–1.10
Private, not-profit	1.45	1.25–1.69	1.00	0.77–1.30
Private, collapsed category	5.87	5.02–6.88	1.09	0.90–1.31
Government/private, collapsed	1.00		1.00
Hospital Location/Teaching Status
Rural	3.43	2.92–4.02	1.69	1.43–2.00
Urban nonteaching	1.00		1.00
Urban teaching	0.38	0.31–0.48	0.75	0.56–1.01

Relative to Level I or II trauma centers, hospitals with a trauma designation III or IV had a 1.81 greater odds of transfer. The odds of transfer were more than twice as high in the Midwest (OR 2.06 (95% CI 1.56–2.72)) relative to the Northeast, and the odds of transfer were slightly higher in the western (OR 1.27 (95% CI 0.97–1.66)) and southern US (OR 1.08 (95% CI 0.79–1.46)) relative to the northeast. Relative to government or privately owned hospitals, transfers were less likely at private, investor owned hospitals (OR 0.84 (95% CI 0.65–1.10)). Transfers were most likely to originate at rural hospitals (OR 1.69 (95% CI 1.43–2.00)) relative to urban non-teaching hospitals.

4. Discussion

We analyzed data from the National Emergency Department Sample to inform efforts to identify priority emergency general surgery (EGS) populations and to develop protocols for streamlining interfacility transfers from emergency departments (EDs). To our knowledge, this is the first study to characterize interhospital transfers for EGS patients using the NEDS database, a nationally representative database of ED visits. Our results indicate that older patients are more likely to be transferred from EDs, perhaps because they have care already established elsewhere or their family has a preference regarding where they receive care. Transferred patients are also more likely to have multiple comorbid conditions and certain EGS diagnoses, including resuscitation, cardiothoracic conditions, intestinal obstruction, and upper GI tract conditions. This is consistent with previous research showing that transferred patients from inpatient settings tend to be older, male, and have more chronic conditions.^{6,16, 20–23} In addition to their comorbidity burden, this population experiences greater delays in transfer, making them high value targets for early identification and timely transfer planning protocols.^24–25

We also found that patients with public insurance and in lower income ZIP codes tend to be transferred more frequently. Previous studies demonstrate that uninsured and publicly insured patients have 1.5 to 2 times the odds of transfer relative to privately insured patients.^26–27 Although the watershed 1986 legislation EMTALA (Emergency Medical Treatment and Active Labor Act) prohibits the transfer of patients based on their ability to pay for treatment, the persistent association between socioeconomic indicators and transfer, even after controlling for measures of underlying patient illness, suggests that socioeconomic disadvantage remains a risk factor for interhospital transfer. This potentially occurs because the hospitals to which these patients are transferred have greater capacity for un- or under-compensated care even after controlling for hospital facility characteristics.²⁸ However, this phenomenon warrants further study. In contrast to previous work, we found that patients without insurance (self pay) were less likely to be transferred, possibly because these patients are more likely to visit the hospital for less severe conditions that could be managed on an outpatient basis.²⁶ Establishing protocols for transfer decision-making based on clinical indications will help ensure candidates of transfer are identified early and systematically to mitigate biases.

Our results indicate that hospitals in rural areas, those with a Level III or IV trauma designation, and facilities in the Midwest were more likely to transfer patients out of their EDs. This rural effect is robust across health systems, and has increased over time owing to the consolidation of hospitals and the declining availability of on-call specialitsts.^2,22 For EGS patients who are transferred to a higher level of care, fewer than half require surgery.² Therefore, potential drivers of transfer for these patients may include rural surgeons’ or anesthesiologists’ discomfort operating on medically complex patients and the absence of critical care resources in small and rural hospitals.² Protocols and training tailored to help rural community hospitals care for medically complex patients who do not need specialty surgical intervention have the potential to improve resource use and patient outcomes. In addition there may be a role for telemedicine consultation both in the ED and in-hospital to prevent an unnecessary transfer and provide additional management guidance.

Despite accepting facilities having more resources, transfers frequently confer worse outcomes and higher costs even among propensity score-matched cohorts.^20,29–31 Given the complexity of EGS patients who are transferred from EDs, they stand to benefit both from standardized protocols to streamline transfer communication and procedures, and also from stable transfer relationships with specific tertiary care centers. Existing research demonstrates that smaller hospitals typically refer to many different facilities.³² This is problematic because ED providers waste time calling different hospitals for transfer. Moreover, there is substantial nationwide variability in (1) whether transfers occur for EGS patients, (2) the lengths of stay for patients who are ultimately transferred, and (3) interhospital communication to facilitate transfers.^21,33–36 Gaps in communication are associated with higher mortality.³⁵ Therefore, a standardized system for assessing patients and initiating interhospital transfers for EGS patients has the potential to reduce unwarranted variability in this process and improve outcomes.

Because EDs rely on timely care processes and are often the first place patients present with EGS conditions, they are a natural fit for developing and testing protocols to improve and standardize the EGS transfer process. Nacht and colleagues comprehensively summarized the need to examine populations that are predisposed to transfer from EDs as essential to characterizing “three critical aspects of emergency care systems: (1) regionalization, including prehospital destination protocols and transferring patients for specialized care; (2) resource utilization and distribution, including protocols for diagnostic tests and interventions, workforce planning, and opportunities for telemedicine; and (3) planning for surge capacity.”³⁷ The authors further note that ED beds are a limited resource, with throughput being of prime importance to regulators yet 66% of transferred patients stayed in the ED for more than 3 hours. However, interventions to facilitate interhospital transfers are scant. A single study of a one-page handoff communication tool yielded reductions in length of stay and mortality for all transferred patients, and the majority of efforts to improve handoffs from the ED have focused on communication with outpatient providers and establishing follow-up rather than transfers to other facilities.^38–39 Recently, a published opinion on EGS transfers recommended a three part assessment of whether transfer is indicated based on (1) underlying disease (2) the severity of physiologic derangement, and (3) available hospital resources. Intervention development to improve and standardize interhospital transfers for EGS patients has significant potential to reduce mortality, reduce morbidity, and promote the efficient use of resources.⁴⁰ The resulting intervention at the point of care could involve standardized handoff checklists, comprehensive telephone scripts, or a combination thereof to support successful transfers in which patients are transferred swiftly and benefit unequivocally from a higher level of care, including specialty surgical care.

Our study has some important limitations that contextualize our results. First, NEDS does not allow us to characterize the post-transfer hospitalization. As a result, we cannot qualify the outcomes of EGS patients who are transferred from EDs, including morbidity, mortality, and cost. Because NEDS is a population-level data set and is not validated to address specific clinical problems, our results warrant additional validation in the clinical setting. Moreover, we cannot identify how many different hospitals each facility transfers to nor can we characterize the clinical services available and surgical capacity at transferring facilities. Our data are from 2014 and may represent practices that have recently shifted. However, because a formalized ICD-10 definition of EGS has not yet been established, 2014 is the most recent year for which we can characterize EGS using a consensus definition. Overall, our analysis provides a comprehensive, representative picture of the factors that predispose patients with an EGS condition to transfer.

Overall, we have shown that the burden of transfer disproportionately falls on medically complex and older patients who present at small, rural hospitals. Efforts to improve the interhospital transfer of ED patients with EGS conditions are overdue and would answer a longstanding call to improve handoffs from the ED more generally.⁴¹ Moreover, smaller emergency departments are closing, and more health systems are operating free-standing EDs.⁴² Therefore, it is worthwhile for EDs and referring hospitals to prepare joint protocols for transfers. At a minimum, there is evidence to support pre-arranged transfer relationships between small, community hospitals and larger referral centers, standard communication templates to facilitate interhospital communication, and expedited transfer for specific, priority populations. Future research on the unique needs of rural hospitals and timely transfer of EGS patients who require specialty surgical care have the potential to significantly improve outcomes and reduce costs.