Averted Transfers in Rural Emergency Departments Using Telemedicine: Rates and Costs Across Six Networks

Abstract

Objective:

This analysis identified the rate of transfers and averted transfers and their associated costs across multiple emergency department telemedicine (teleED) networks.

Methods:

This study is a prospective cohort analysis in six teleED networks operating in 65 hospitals in 11 states across the United States. Each submitted uniform data on all teleED encounters for a 26-month period to a data co-ordinating center. Averted transfers were identified if an encounter met specific criteria. Cost savings from averted transfers were estimated from hospital-specific costs of transferred patients.

Results:

A total of 4,324 teleED encounters were reported. Excluding patients who died, 1,934 (46.2%) were transferred to another inpatient facility. Records of the remaining 2,248 teleED patients were examined and 882 (39.2% of nontransfers; 20.4% of all teleED cases) teleED patients met the criteria for an averted transfer. Of the averted transfer cases, 53.3% were admitted to the local inpatient facility, and 43.5% were discharged. Patients who averted transfer had lower levels of severity and less billed services than those who were transferred. Transport savings for averted transfers were estimated to total $1,074,663 annually across the six teleED networks. Average estimated transport savings were $2,673 for each averted transfer.

Conclusions:

In a large cohort of teleED cases, 39% of nontransfer cases were averted transfers (20% of all teleED cases). Importantly, 43% of these patients were routinely discharged rather than being transferred. Averted transfers saved on average $2,673 in avoidable transport costs per patient, with 63.6% of these cost savings accruing to public insurance.

Introduction

Rural hospital emergency departments (EDs) often have low volumes and as such face multiple challenges, including limited medical equipment, technology, and other structural resources.^1
–3 In addition, because of chronic health care workforce shortages in rural areas,⁴ there is an overall shortage of physicians practicing in rural EDs.⁵ In many rural areas of the United States, the majority of providers covering the ED are not emergency physicians, but instead are family physicians or advanced practice providers from the local community^6
–8 who share coverage of the ED in addition to a full clinic and hospital practice.

Emergency department telemedicine (teleED) is a telemedicine application that provides specialized emergency medicine consultation in a hub-and-spoke model between a tertiary center (hub) and a lower-volume ED (spoke), usually in small rural or remote hospitals.⁹ TeleED has been shown to have multiple benefits, including improved quality and timeliness of patient care.¹⁰ A growing body of research evidence supports its use, but less frequently studied is its effect on health care cost, especially linked to transfers from low-volume EDs to higher-volume hospitals with more advanced resources. Not only are transfers costly and often disruptive for the patient and their family, but many transfers have been judged to be clinically unnecessary.^11,12 TeleED has been hypothesized to reduce the rate of clinically unnecessary transfers by averting transfers through expert consultation. Yet only two studies have examined the effect of teleED on the rate of clinically unnecessary transfers^13,14 and only two studies have examined the cost savings from averted transfers.^14,15 Two of these studies were quite small and all involved a single teleED network, which points to the need for additional well-designed more generalizable studies to address this important question. The objective of this analysis is to identify the rate of transfers and averted transfers and their associated costs across six rural teleED networks operating in 11 states in the United States.

Materials and Methods

Sample

This study is a prospective cohort study of patients being treated in 65 spoke hospital EDs across 6 teleED networks. These six teleED networks received funding between 2014 and 2018 from the Health Resources and Services Administration (HRSA) Federal Office of Rural Health Policy (FORHP) under the Evidence-Based Telehealth Network Grant Program (EB TNGP) to operate teleED services that improve rural access to high-quality ED care and generate evidence about teleED. The six teleED networks were (1) Avera Health, (2) Saint Vincent Healthcare, (3) Union Hospital, (4) University of California–Davis, (5) University of Kentucky, and (6) University of Virginia. They provided teleED services to 65 spoke hospitals in 11 states—California, Indiana, Iowa, Kansas, Kentucky, Minnesota, Montana, Nebraska, North Dakota, South Dakota, and Virginia. All spoke hospitals were general medical and surgical hospitals and were either nonprofit (74%) or local government (mostly county)-owned. It is important to note that the six networks provided teleED services customized to the needs and resources in their respective service areas and no effort was made to align their practices other than to use a common data collection tool and definitions. The study protocol was approved by the University of Iowa Institutional Review Board (IRB) and all grantee IRBs. The findings are reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.¹⁶

Data Collection

A standard data collection instrument was developed and distributed to the six teleED networks. Over a 26-month period (November 1, 2015 to December 31, 2017), each teleED network submitted ED visit-level data on all their teleED encounters to the data co-ordinating center (the FORHP-funded Rural Telehealth Research Center). For the purposes of this study, teleED was defined as an immediate synchronous interactive audio/video connection between an ED originating site (spoke) and a distant site where a specialist is located (hub). The data comprised 49 elements. Each data element was defined in a data element dictionary, with specific response options and criteria to guide uniform data abstraction efforts. Data were submitted periodically by each network using a custom-made MS-Excel-based tool (Microsoft Corporation, Redmond, WA). The data co-ordinating center used data checking algorithms and worked iteratively with the six teleED networks to address missing and out-of-range data submissions. Data elements used in these analyses include age, gender, race, ethnicity, primary type of insurance coverage, weekday and time of ED visit, Emergency Severity Index (ESI), ED Current Procedure and Terminology (CPT) code, ED disposition, transfer mode of transport, transfer distance, referring hospital, and whether or not a transfer was averted.

Criteria for Averted Transfer

The criteria for coding a case as an averted transfer were agreed upon by the six teleED networks before data collection. As stated in the data element dictionary, an averted transfer must meet the following three conditions: (1) staff at the rural ED activated teleED and stated they wish to transfer a patient, have arranged a transfer, are considering transfer, or are questioning whether a patient should or should not be transferred; (2) the teleED hub team has a meaningful interaction with an ED physician or another consulting clinician at the rural ED; and (3) the patient is not transferred to another facility. In addition, the data element dictionary specified the following exclusion criteria: (1) the local ED staff and family were never planning to transfer the patient; (2) the local ED staff only received nursing documentation or transfer support from the teleED hub and the patient was not seen on video for consultation; and (3) the patient was transferred during or within 2 h of the video session (or the transfer was at least ordered if not yet completed due to weather); and/or (4) the patient died during the video session or unexpectedly thereafter. The data element dictionary also provided examples of scenarios leading to an averted transfer, including but not limited to the following: a patient's family wanting to transfer the patient but changed their minds after visiting with the teleED physician/staff; or the patient was expected to transfer, but because of expert opinion or conversation with family, decided on comfort care only for the patient at the end of life.

Identification of Cost Savings for Averted Transfers

To estimate cost savings for averted transfer, an algorithm was used that estimated the cost that would have occurred if the transfer had not been averted based on the cost of actual transfers from the same hospital. For each hospital, all actual transfers among teleED cases were first examined to identify the one-way distance from the originating hospital to each destination hospital and the mode of transportation used. GoogleMaps^™ (Alphabet Company, Mountain View, CA) was used to derive driving miles for ground ambulance transport or for car transfer; Euclidean distances from city center latitudes and longitudes were used for rotary and fixed wing transfers (ambulance miles/fees to and from airports/helipads were not included). These actual transfer distances and transport modes were then applied to the averted transfers from the same hospital to provide hospital-specific estimates of the mileage and mode of transport that would have occurred if the transfer had not been averted.

The Centers for Medicare and Medicaid Services (CMS) Ambulance Fee Schedule¹⁷ was used to calculate transport costs for ground, rotary wing, and fixed wing transport for a one-way transfer. Private insurance reimbursement rates are usually proprietary, so CMS rates are recommended for cost analysis¹⁸ through the use of published geographically specific base rates to Part A Medicare Administrative Contractors. Because the data collection period spanned 2016 and 2017, an average of rates across these 2 years was used. CMS reimbursement uses a combination of mileage rates and geographically specific base rates, specified for each mode of transport. Across the 11 states represented in the data, averages for 2016/2017 base rates for ground transport ranged from $395 to $547, rotary wing transport ranged from $4,225 to $5,349, and fixed wing transport ranged from $4,912 to $6,219, with Kentucky having the lowest base rates and Northern California having the highest base rates. Mileage rates are uniform across geographic locations and the average for 2016/2017 was $7.34 per ground transport mile, $34.14 per rotary wing transport mile, and $12.80 per fixed wing transport mile. Federal mileage reimbursement rates were used for personal car and law enforcement transport.

Results

Frequency of Patients Meeting the Criteria for Averted Transfer

Over the 26-month data collection period, the 6 teleED networks reported a total of 4,324 ED encounters where teleED was used. Excluded from subsequent analyses were patients who died in the ED (N = 142, 3.3%). Of the remaining 4,182 teleED cases, 1,934 patients (46.2%) were transferred to another inpatient facility. The 2,248 patients who were not transferred or who did not die in the ED were examined for averted transfer. Applying the three criteria listed earlier, 882 teleED patients had an averted transfer (39.2% of nontransfers; 20.4% of all cases), 1,331 (59.2%) did not meet the criteria of an averted transfer, and 35 (1.6%) were unclear or unknown.

Characteristics of Patients Who Averted Transfer

There was significant variation in averted transfer rates across the six teleED networks (p < 0.0001). To examine sources of variability, teleED patients who averted transfer (N = 882) were compared with those who were transferred (N = 1,934) on key characteristics, as shown in Table 1. Day of week and time of day of ED arrival did not differ significantly between patients who averted transfer compared with those who were transferred. Likewise, primary payer did not differ significantly between the two groups, with roughly 40% covered by Medicare, 28% covered by private insurance, and 20% covered by Medicaid. Age, gender, race, and ethnicity did differ significantly with averted transfer patients more likely to be female, white, unknown ethnicity, and adult age than patients who were transferred. As expected, transferred patients had more serious ESI indicating greater urgency of needed care and predicted use of ED resources¹⁹ than those who averted transfer (p < 0.0001). Transferred patients also had higher levels of CPT code on a seven-level billing system indicating more complexity (p < 0.0001) than those who averted transfer.

Table 1.

Characteristics of Emergency Department Telemedicine Patients Who Were Transferred Compared with Emergency Department Telemedicine Patients Who Averted Transfer

VARIABLE	TRANSFERRED (N = 1,934), %	AVERTED TRANSFER (N = 882), %	p
Age (N = 2815)
<1	3.41	1.36	<0.0001
1–14	11.33	4.54
15–17	3.05	0.91
18–24	6.67	8.62
25–44	13.40	18.03
45–64	28.71	27.55
65–74	16.14	17.80
75 and above	17.28	21.20
Gender (N = 2,816)
Female	43.17	50.91	0.0001
Male	56.83	49.09	0.0001
Race (N = 2,816)
White	80.77	85.49	<0.0001
Black/African American	2.79	4.99
American Indian/Alaska Native	7.45	1.93
Asian	0.31	0.45
Multiracial	0.26	0.00
Native Hawaiian/Other Pacific Is	0.05	0.00
Unknown	8.38	7.14
Ethnicity (N = 2,738)
Hispanic/Latinx	3.79	2.31	0.0448
Not Hispanic/Latinx	80.13	79.10
Unknown	16.08	18.59
Primary payer (N = 2,797)
Medicaid only	21.99	18.99	0.0961
Medicare	38.28	42.35
Other/Indian Health Service/VA/CHAMPUS	3.37	2.19
Private insurance	28.79	28.88
Self-pay/uninsured	7.57	7.59
ED visit—arrival day of week (N = 2,816)
Monday	14.22	16.33	0.2931
Tuesday	14.58	12.93
Wednesday	12.10	13.49
Thursday	14.99	13.38
Friday	14.99	13.38
Saturday	15.46	15.19
Sunday	13.65	15.31
ED visit—arrival time (N = 2,816)
Business hours (0730–1730)	55.12	53.74	0.4959
Not business hours	44.88	46.26	0.4959
Emergency Severity Index (N = 2,175)
Resuscitation	6.52	4.81	<0.0001
Emergent	66.27	56.07
Urgent	24.54	34.18
Less urgent	1.89	4.41
Nonurgent	0.77	0.53
CPT code (N = 2,226)
99281	0.18	0.19	<0.0001
99282	0.41	3.65
99283	4.75	18.23
99284	24.87	36.66
99285	53.67	38.58
99291	10.15	2.30
99292	5.98	0.38

CPT, Current Procedure and Terminology; ED, emergency department; VA, Veterans Administration; CHAMPUS, Civilian Health and Medical Program of the Uniformed Services.

Averted Transfer Cost Savings

Table 2 shows annualized transport cost for patients who transferred and estimated annualized transport costs for patients who averted transfer. On average, transport costs were $3,339 for transferred patients and would have been $2,672 for averted transfers. Although the mileage and mode of transport for transferred patients at each hospital were used to model these values for averted transfer patients, the numbers of each differed within hospitals. For example, hospitals with further distances and more air transport for their transferred patients generally had fewer averted transfers than hospitals with shorter distances and more ground transport, thus leading to lower average estimated cost for averted transfers.

Table 2.

Annualized Transport Cost of Emergency Department Telemedicine Patients Who Were Transferred Compared with Emergency Department Telemedicine Patients Who Averted Transfer

TRANSPORTATION MODE OF TRANSFER	TRANSFERRED		AVERTED TRANSFER
TRANSPORTATION MODE OF TRANSFER	ANNUALIZED NO. OF CASES	ANNUALIZED SUM	ANNUALIZED NO. OF CASES	ANNUALIZED SUM
Air—fixed-wing	93	$629,884	14	$94,985
Air—rotary	258	$1,840,371	120	$772,100
Ambulance	486	$453,351	258	$207,122
Other	6	$260	4	$145
Personal car	34	$1,722	6	$313
Total	876	$2,925,588	402	$1,074,663

Total may not equal sum due to rounding.

The values shown for averted transfers are cost savings since these expenses were avoided. Based on the insurance status of the patients, 63.6% of these cost savings would have accrued to public insurance (Medicare, Medicaid, Indian Health Service, Veterans Administration, etc.), 28.8% would have accrued to private insurance, and 7.6% would have accrued to patients' self-pay or those covering cases with no insurance.

Discussion

This analysis examined the rate of averted transfers using carefully specified criteria involving meaningful communication about the appropriateness and usefulness of transfer. Of the teleED patients who were not transferred, more than one-third (39.2%) were judged to be averted transfers. The degree to which telemedicine affects ED disposition is an important outcome having implications for patient satisfaction, ED throughput, and health care costs. Previous studies have reported that teleED reduced transfer rates^20,21 but did not examine how. Two studies did specifically examine unnecessary transfers and found reductions after teleED activation.^13,14 In particular, Pedragosa et al. defined unnecessary transfers in stroke patients as those who did not receive thrombolysis after being transferred to a stroke center and who could be retransferred to the referring hospital within 24 h.¹³ This rate of unnecessary transfers fell from 51% to 20% after teleED implementation. Tripod et al. defined unnecessary transfers in hand trauma patients as those who were immediately discharged home without admission/surgery after being transferred to a regional trauma center.¹⁴ This rate of unnecessary transfers fell from 48% to 32% after teleED implementation. These two studies help provide the rationale for why averted transfers are important and how teleED consultations can help reduce unnecessary transfer.

In this study, compared with patients who were transferred to another inpatient facility, patients who averted transfer had lower level ESI and CPT codes, indicating that they had less serious conditions, especially for those who were routinely discharged instead of being admitted locally. These findings help support the validity of the important clinical disposition decisions inherent in ED practice. Among the 882 patients having averted transfers, 53% were admitted to the local hospital rather than being transferred. Importantly, 43% were discharged rather than being transferred, suggesting either that definitive care was provided during the initial local ED encounter or that alternative non-ED locations of follow-up were established. Thus, the rates of averted transfers were high and consequential for patients, their families, providers, and insurers.

Estimated transport savings for averted transfers were substantial, totaling $1,074,663 annually across the six teleED networks. Average transport savings were $2,673 for each averted transfer. This average across six teleED network systems is between the average transport cost of $1,382 reported by Tripod et al.¹⁴ and the average transport savings of $3,838 reported by Natafgi et al.¹⁵ The considerable difference in these average transport savings appears to derive primarily from geographic locale reflected in the differences in transport mode estimated in these three studies with higher averted transport costs in more remote areas. In particular, Tripod et al. estimated a 15% rate for air transport,¹⁴ the current analysis estimated a 33% rate, and Natafgi et al. estimated a 50% rate.¹⁵ Given the far more expensive cost of air transport, the location and relative remoteness of the sample hospitals could largely explain the differences in average transport cost across studies. In addition, the Natafgi et al. transport costs included round-trip ground transport for someone accompanying the patient and bringing them home, which the other two analyses did not include.¹⁵

This difference in transport cost estimates points to an important factor. Essentially all of the previous research on transfer rates and averted transfers derive from analysis of single teleED networks. A unique feature of the current analysis is that it pools data on teleED cases in a 26-month period from 6 teleED networks operating in 11 states. We found that there was significant variation in averted transfer rates across the six teleED networks, which is not surprising given that these six teleED networks had different operating structures and goals. For example, two networks added teleED to hospitals with existing robust telephone transfer services and continued to have high transfer rates since part of their teleED network goal was to facilitate transfer operations. The differing rates across the six teleED networks point to the need to draw conclusions about important outcomes from multiple telemedicine services and thus, this large, heterogeneous sample strengthens the generalizability of these findings.

There are several limitations to this study. The study data elements included mileage and mode for transfers, so analyses were limited to transport costs estimated directly from these reported data. In addition, costs beyond transport were not included, and these factors (e.g., lodging/transport for family members, lost wages for patients and family members) add substantially to cost as described by Natafgi et al.,¹⁵ and subsequently to averted transfer impact. Costs of repeated medical tests and communication barriers across inter-hospital transfer also have not been included.

TeleED has been shown to produce multiple benefits,⁹ but cost savings have often been neglected in empirical studies.¹⁰ Based on a large multi-network sample and carefully defined criteria, the current analysis conservatively estimates transport cost savings per averted transfer patient of $2,673. This translates to annual cost savings of nearly $180,000 generated by each of the six teleED networks with nearly $115,000 of this accruing to public insurance payers annually in reimbursable transport costs alone.

The current findings that 43% of the patients who were originally considered for transfer were routinely discharged rather than being transferred after teleED consultation and communication are important. Not only does this save nontrivial transport costs, but also considerable burden on the patients and their families plus the cost of an impatient stay. Averted transfer transport costs for payers and patients are just part of the potential savings that teleED generates. Other substantial savings may come from teleED's ability to meet workforce shortages in rural areas, which has been shown to save considerable operating costs for rural hospitals.²² Furthermore, the local health care system is strengthened when patients are cared for in their community.

Footnotes

Disclosure Statement

The authors have no commercial associations that might create a conflict of interest in connection with this article.

Acknowledgments

The authors thank Amanda Bell [principal investigator (PI)], Luke Mack, Amy Wittrock from Avera Health; Eric Pollard (PI), Martha Nikides from St. Vincent Healthcare; Stephanie Laws (PI), Hicham Rahmouni, Daniel Hardesty, Amanda O'Brien from Union Hospital; James Marcin (PI), Jamie Mouzoon from University of California-Davis; Roger Humphries (PI), Brian Dennis, Theresa Mims, Rob Sprang from University of Kentucky; and Nina Solenski (PI), Tracy Blount from University of Virginia for contributing data for these analyses.

Funding Information

The study described in the article was funded by the U.S. Department of Health and Human Services (HHS), Health Resources and Services Administration (HRSA) under co-operative agreement number UICRH29074. Funding for delivering teleED services and data collection was provided under grant numbers GO1RH27868, G01RH27869, G01RH27870, G01RH27871, G01RH27872, and G01RH27873. The views expressed in this article are those of the authors and do not necessarily reflect the official policies of HHS or HRSA, nor does mention of the department or agency names imply endorsement by the U.S. Government.

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