Telehealth Increases Access to Care for Children Dealing with Suicidality,Depression,and Anxiety in Rural Emergency Departments

Abstract

Background:

Targeted research efforts in implementation and evaluation of telemental health care for U.S. youth are needed to increase accessibility to care. Before telehealth, children and families may wait weeks for psychiatric evaluation.

Introduction:

Increasing numbers of pediatric patients are reporting the need for mental health care when they present to region's rural emergency departments (EDs). Outcomes of telemental health services were evaluated, with a focus on treatment throughput and referral.

Materials and Methods:

Observational 18-month program evaluation of outcomes for children age <18 years (N = 87) who received physical and mental health assessment by an ED physician. Children who subsequently received a mental health diagnosis were treated by a psychiatrist via telemental health visits (September 2017–May 2019) in 4 rural EDs.

Results:

The majority of children (ages 5–17) presented with depression- or anxiety-related disorders (49%) or suicidal ideation/attempt or self-harm (46%), with substance abuse accounting for 5% of cases. Mean ED wait times were 29 min [95% CI: 6–52 min] for children admitted to inpatient (IP) care compared with 33 min [95% CI: 22–43 min] for those discharged to outpatient (OP) care. Mean length of stay (LOS) of 8 h 56 min [95% CI: 166–906 min] was observed for children admitted to IP care compared with mean LOS of 6 h 58 min [95% CI: 382–454 min] for those discharged to OP care (p = 0.072). For suicidality cases, children who were subsequently admitted to IP care experienced a significantly longer mean LOS of 12 h 30 min [95% CI: 279–1221 min] compared with a mean LOS of 7 h 13 min [95% CI: 346–520 min; p = 0.015] for children discharged to OP care. Mean total payor reimbursements were significantly lower than actual ED costs (p < 0.001).

Discussion:

ED wait times and LOS were lengthy overall. Future evaluation of an evidence-based peds mental health triage screening tool is needed to support rural ED providers in peds mental health treatment.

Conclusion:

Additional resources and strategic policy supports are needed to bridge the mental health care treatment gap for rural children to address critical prevention, screening, and reimbursement needs.

Introduction

Families living in rural counties throughout the United States (U.S.) continue to report that access to quality health care is their top priority, with emergency department (ED) care, insurance coverage, and adequate mental health (MH) care highlighted as 3 of top 5 U.S. rural families' health concerns.¹ Compounding issues of rural patients' ready access to MH care is the fact that the majority of U.S counties have a shortage of psychiatrists to treat people with MH issues.² As of late 2018, there were 2,672 Mental Health Professional Shortage Areas (HPSAs) designated in rural areas, comprising 85% of U.S. counties (2672/3142).³ In light of the prevalence of MH care provider shortages across the U.S., the ED often becomes the clearinghouse for triage, initial screening, assessment, and treatment of many patients of all ages who present with MH issues.^4

–8

As the number of ED visits related to MH continues to increase,^2,5 some rural and urban EDs and health care systems are integrating telehealth-based MH care, or telemental health, in an effort to “virtually” deliver, coordinate, and evaluate telemental health care delivery for patients across the life span.^5

–8 Telemental health care allows for expedient, video-based access to a psych specialty provider, and has been highlighted as an efficient and timely method for delivery of MH care that is similar in effectiveness to in-person care.^5

–11 Once any emergent, life-saving physical needs have been addressed, the generalist ED (non-psych) providers can utilize telemental health care to subsequently address a patient's emergent psych care needs.

Telemental Health Care Delivery Process

Most commonly, the telemental health care delivery process involves utilizing live, video-based interaction (LVI) with a distant, appropriately licensed psych MH provider (psychiatrist, clinical social worker, psych MH nurse practitioner, psychologist), with the ED telehealth visit typically facilitated by the ED nurse.^4

–8 According to experts, ready access to the LVI method of telemental health care delivery in the ED supports numerous benefits to patients, families, providers, and health systems, including decreased wait/transfer times in the ED,^9,12,13 decreased length of stay (LOS),^9,14
–16 enhanced quality of care and care coordination,^{7
–9,14
–16} enhanced “learning effect” for the generalist health care providers collaborating with psych specialty providers via telehealth,^{9,12
–14,17} enhanced connection to outpatient (OP) resources,^14
–16 cost savings due to reduced number of hospital admissions,^14
–16 and decreased travel costs for families and MH professionals.^14
–16

Evaluating telemental health care processes is important to meet or exceed standards of care.^5

–11 Telehealth provides ready access to MH care in underserved areas, thus potentially “leveling the playing field” for participating rural ED patients and providers by mitigating the social determinants of health that often underlie rural health disparities. Social determinants of health include remote geographic location, provider shortage areas, socioeconomic disadvantages such as living at or below the poverty level, and a lack of insurance coverage.^5,12,17,18 For many patients and families in need, telemental health becomes the critical “point-of-care” access that makes timely, specialty-driven MH care treatment and referral possible.

Telemental Health and Children

The evidence-based utilization of telemental health care delivery for children presenting with behavioral health issues to EDs has been viewed as crucial “to address the worsening gap between available supply of qualified providers and demand for child psychiatric services.”^{5, p.467} Recently, Comer and Myers¹³ called for targeted research efforts in telemental health care for U.S. youth, “…to optimize the quality and transform the accessibility of MH services for all children, regardless of income or geography.”^17,p.296

Thus, attention must be paid to support increased access to MH care for children living in rural settings, with a special focus on prevention and wellness, to promote relevant methods of early screening, intervention, and referral, in an effort to avoid the progression of MH issues from childhood or adolescence into adulthood. The purpose of this prospective observational study was to evaluate the preliminary 18 months' results of telemental health outcomes for children ages 1–17 (N = 87) presenting to participating rural critical access hospital (CAH) EDs, to determine the types of MH issues facing children and families in these rural counties. Study data were also assessed regarding major diagnostic group trends by age range, time spent in ED, and discharge planning from the ED (inpatient [IP] admission or OP treatment referral).

Payor, total costs of care, and payor reimbursement data based on a major diagnostic group could also be obtained from one participating hospital as a substudy (n = 46). These data were evaluated for descriptive cost outcomes. Cost and reimbursement data will be requested from the remaining hospitals moving forward for future years of the study. The authors' hope and intention are that these efforts will help to inform public policy decision-making regarding children's MH screening and treatment, ED-, school-, and community-based educational prevention and wellness plans, as well as to support innovative, evidence-based children's telemental health funding needs.

Preliminary results for the adult MH patients participating concurrently in this study have been reported elsewhere (N = 273).¹⁹ Selected adult MH outcomes will also be reported here in the Discussion section for comparison purposes, to highlight notable differences among pediatric and adult MH outcomes for the first 18 months of the study.

Materials and Methods

Setting and Population

Based on previous research studies,^12,16 increasing numbers of the targeted region's patients are self-reporting the need for MH care when they present to the participating rural EDs. However, waits for psychiatric visits can take weeks or even months in this particular region, due to the shortage of child and adult psychiatrists in these rural counties. In response, the Wabash Valley Rural Telehealth Network (WVRTN) decided to evaluate utilization and outcomes of telehealth-based health services in an effort to increase access to mental health care, with a special focus on telemental health care treatment and subsequent referral across four of the region's CAH EDs. For this initial data-based evaluation, the assessment of telemental health treatment outcomes for children aged 1–17 years is reported as a baseline, to support ongoing longitudinal evaluation regarding outcomes (diagnostic group, age range trends, costs, and referral) for the region's pediatric subpopulation seeking MH care in the rural EDs.

The WVRTN serves some of the state's most economically disadvantaged and medically underserved counties in Indiana (Greene, Parke, Putnam, Sullivan, Vermillion, and Vigo), including a predominance of county-level federal HPSAs in MH care, and a disproportionate number of individuals and families living at or below the poverty level.^20
–22 Combined economic data for the targeted region reveal that 10.4% of the population are living under 100% of the federal poverty level (FPL), and 30.18% of the population are living at or below 200% of the FPL.^20
–22

Intervention

The WVRTN utilizes an on-demand design with a centralized “hub” of medical providers that delivers specialty-based psychiatric care via a regional telehealth network. For telemental health care delivery, the distant board-certified psychiatric providers comprise the hub that connects to the originating rural ED provider teams. The rural ED provider teams are led by the board-certified emergency physicians as the attending providers. For study purposes, the telemental health visit was ordered by the attending ED physician based on the initial physical and mental health assessment of the child. Based on the attending ED physician's order, the telemental health visit was then initiated by the registered nurse (RN) who was managing care for the peds patients and their family.

Telemental health visits consisted of 1:1 patient/teleprovider interviews utilizing LVI in a private ED examination room set up for telehealth visits with the distant psych specialist. The RN functioned in a facilitative “telepresenter” role as needed, with a family member present, unless the child was an emancipated minor age 16 years or older, and/or as needed as per the psych specialist. Once the telehealth-based visit was completed, the RN supported clinical documentation and patient discharge plan. Development and communication of a tailored behavioral health safety plan for the minor patient and the parent or guardian, relevant to the child's subsequent discharge plan, were also the responsibility of the RN, in coordination with the distant psych specialist and attending ED provider.

Study Sampling and Informed Consent

To be able to participate in the study, a telemental health visit was ordered by the attending ED physician. The facilitating nurse then explained the telemental health process to the child and family. The child was asked to provide written or verbal minor assent, and the parent or guardian was also asked to consent in writing, for the child to be treated via telemental health. Unless the family subsequently decided to leave against medical advice from the ED, all peds patient cases involving an MH diagnosis had a telemental health visit ordered by their attending physician, which was consented to by the child and the parent/guardian. For this study, 88 pediatric patients received a presenting MH diagnosis from the attending rural ED physician. Eighty-seven children were subsequently treated with a telemental health visit by a distant, board-certified psychiatrist, with one parent/guardian and pediatric patient leaving against medical advice before the telemental health visit could occur (N = 87/88; 99% participation rate).

Data Collection and Analysis

Patient records for the pediatric telemental health cases were deidentified internally and then retrieved on-site from each participating CAH's medical records department via electronic health records. Diagnosis codes on the medical records were from the International Classification of Diseases, the new ICD-10 version, which was launched during 2016.

After each ICD-10 coding was noted, all behavioral health cases were subsequently grouped based on broad behavioral health diagnostic categories for statistical analysis purposes. For example, suicide attempt, suicidal ideation, and self-inflicted or intentional injury were grouped together as the broad category of suicide and intentional self-inflicted injury for statistical evaluation. The following list presents the broad behavioral health category groups evaluated for the study based on the Clinical Classification Software categorization available from the Agency for Healthcare Research and Quality²³: (1) suicide and intentional self-inflicted injury, (2) substance abuse and overdose, and (3) anxiety, depression, and other mental health disorders (other = conduct disorder, n = 3).

Data were analyzed using IBM SPSS version 25.0 (IBM SPSS Statistics for Windows, Armonk, NY), and statistical significance was defined as α < 0.05. Variable relationships were evaluated utilizing descriptive, nonparametric, and parametric statistical tests. The parametric statistical analyses included the following: (1) Student's t test (two-tailed) to determine any statistically significant differences between discharge disposition from the ED (IP vs. OP) and telemental health outcomes for participants; and (2) analysis of variance (ANOVA) to determine any statistically significant differences within and across three broad categories of behavioral health diagnoses in relation to patient demographics, ED throughput (temporal) variables, patient discharge status, total ED costs, and primary payor and percent reimbursement. The nonparametric statistical analyses involved chi-square tests to determine any potential relationships between (a) age range and category of MH diagnosis and (b) primary payor for IP and OP subgroups. Cases with missing data for variables of interest were not included in the analyses.

The current study was approved by the regional university's institutional review board (IRB). Sampling, data, and results of statistical analyses are reported based on guidelines established by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.²⁴ The project is currently funded by the Health Resources and Services Administration, Grant #H1WRH31447.

Limitations

This study had several limitations, and thus, results should be interpreted cautiously. Utilization of an observational study design, rather than a randomized controlled trial approach, for enrolling participants in the study meant that all pediatric MH patients presenting to the rural CAH EDs were able to access telemental health care, allowing for no case/control to be observed concurrently to establish a “telehealth versus non-telehealth” controlled comparison based on diagnostic group. This approach was preferred by the reviewing IRB, so that all children had access to specialist-based psych care in the rural CAHs, due to the urgent MH needs of participating communities that had been observed in prior studies.^12,16,19

While the authors believe that it is important to note and discuss the emerging trends for school-age children in this regional study, the results of this study are not necessarily generalizable to other regions or groups of rural hospitals.

Study Results

Demographics

Demographic results by age range and behavioral diagnostic group are outlined in Table 1. The majority of children presented with depression- or anxiety-related disorders (49%) or suicidal ideation/attempt or self-harm (46%), whereas substance abuse/overdose accounted for 5% of cases. Distribution of pediatric cases increased in number as the age increased, with the highest number of cases (63%) treated in the 14–17 years (high school) age range. Females (66%, n = 57) outnumbered males (34%, n = 30) in the sample nearly 2:1. Racial ethnicity for total number of cases was ∼98.5% white, which is representative of the general population in participating counties.²⁰

Table 1.

Pediatric Patients' Major Diagnostic Group by Age Range and Gender

	DEPRESSION, ANXIETY		SUICIDAL IDEATION OR ATTEMPT SELF-HARM		SUBSTANCE USE/ABUSE/OVERDOSE
AGE RANGE	FEMALE	MALE	FEMALE	MALE	FEMALE	MALE
5–10	7 (27%)	1 (8%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
11–13	5 (19%)	3 (23%)	8 (32%)	4 (33%)	0 (0%)	0 (33%)
14–17	14 (54%)	9 (69%)	17 (68%)	8 (67%)	2 (100%)	2 (100%)
Total	26	13	25	12	2	2

Authors' analysis of aggregated electronic patient data. The pediatric age ranges have been approximated to match U.S. school-age groups for elementary, middle/junior high, and high school-age groups, respectively.

Primary Outcomes

Temporal outcomes by major diagnostic group and discharge plan

ED wait time (time-to-provider)

ED wait time was defined as the time from patient sign-in in the ED reception area to the initiation of care by the initial assessing provider. Table 2 presents the total number of pediatric MH cases by diagnostic group and time-based ED throughput variables for within-diagnostic group and between-diagnostic group comparisons. For ED wait time (time-to-provider), mean wait time was 29 min [95% CI: 6–52 min] for children who were subsequently admitted to IP care, and 33 min [95% CI: 22–43 min] for those subsequently discharged to OP care. While the wait times for the small number of substance abuse/overdose cases were much shorter on average (5–20 min) and thus clinically meaningful, the sample sizes in the IP and OP groups in this category were too small for inferential statistical analysis purposes.

Table 2.

Temporal Outcomes for Pediatric Inpatient Versus Outpatient Discharge Plan by Major Diagnostic Group

		INPATIENT (IP)		OUTPATIENT (OP)
		N	M [95% CI]	N	M [95% CI]	T TESTS (IP VS. OP)
ED wait time (time to provider), min	Total behavioral ED Visits	9	29 [6–52]	76	33 [23–43]	p = 0.815
	Diagnostic within-group differences
	Anxiety, mood, and other mental health disorders [A]	2	50 [11–88]^a	41	40 [23–57]	p = 0.800
	Suicide and intentional self-inflicted injury [B]	6	26 [1–51]	32	28 [17–38]	p = 0.912
	Substance abuse-related [C]	1^b	8	3	7 [−5 to 20]	N/A
	Across Diagnostic Groups: t test (IP) or ANOVA (OP)	p = 0.081		p = 0.303		—
	Across Diagnostic Groups: t test (IP) or ANOVA (OP)	Nonsignificant (t test [A][B])		Nonsignificant (ANOVA [A][B][C])		—
ED total length of stay (LOS), min	Total behavioral ED visits	9	536 [166–906]	76	380 [332–428]	p = 0.072
	Diagnostic within-group differences
	Anxiety, mood, and other mental health disorders [A]	2	55 [19–91]^a	41	343 [286–400]	p = 0.033^a
	Suicide and intentional self-inflicted injury [B]	6	750 [279–1221]	32	433 [346–520]	p = 0.015^a
	Substance abuse-related [C]	1^b	214	3	312 [67–558]	N/A
	Across Diagnostic Groups: t test (IP) or ANOVA (OP)	p = 0.695		p = 0.163		—
	Across Diagnostic Groups: t test (IP) or ANOVA (OP)	Nonsignificant (t test [A][B])		Nonsignificant ANOVA [A][B][C])		—
Length of telehealth visit, min	Total behavioral ED visits	10	63 [56–69]	75	59 [57–61]	p = 0.202
	Diagnostic within-group differences
	Anxiety, mood and other mental health disorders [A]	2	70 [60–80]^a	41	59 [57–61]	p = 0.080
	Suicide and intentional self-inflicted injury [B]	7	59 [53–66]	31	57 [54–61]	p = 0.132
	Substance abuse-related [C]	1^b	70	3	66 [32–100]^a	N/A
	Across diagnostic groups: t test (IP) or ANOVA (OP)	p = 0.667		p = 0.191
	Across diagnostic groups: t test (IP) or ANOVA (OP)	Nonsignificant (t test [A][B])		Nonsignificant ANOVA [A][B][C])

Authors' analysis of aggregated electronic patient data.

Denotes statistical significance for temporal IP versus OP outcomes within a diagnostic group. With only two IP cases, the minimum and maximum values were presented.

Thus making for paired group comparisons, whereas analysis of variance (ANOVA) was applied across all three diagnostic groups for OP data due to broader sampling.

CI is confidence interval. Bracketed letters [A], [B], and [C] denote results for comparisons across the three mental health diagnostic groups for IP and OP disposition from the ED; for IP comparisons, t test was utilized due to low sample size in substance abuse.

NA, not applicable.

ED length of stay

LOS was defined as the time from the initiation of treatment in the ED to discharge. Overall differences between LOS for children who were subsequently admitted to IP care versus discharged to OP care were nearly significant (p = 0.072). A mean LOS time of 8 h 56 min [95% CI: 166–906 min] was observed for children admitted to IP care compared with a mean LOS of 6 h 58 min [95% CI: 382–454 min] for those discharged to OP care. Significant differences in LOS were also revealed for children in depression, anxiety, or other MH disorder groups based on discharge status. Children in this category who were subsequently admitted to IP care experienced significantly shorter mean ED LOS of 55 min {95% CI: 55[(−)402–512 min]} compared with a mean LOS of 5 h 43 min [95% CI: 343(286–400 min); p = 0.033] for those who were discharged to OP care. This shorter LOS for IP care likely reflected less need for a psych bed on a locked psych unit, compared with IP admissions for suicidality or substance abuse/overdose, where more secure beds (i.e., detoxification or 24-h watch patient) may be needed. The fewest number of IP psych beds available in the region are on highly secured or locked psych patient units; thus, LOS is typically prolonged for patient/provider waits for this type of IP bed.

A significant difference in mean LOS was also observed for children diagnosed with suicidal ideation/attempt or self-harm. Children who were subsequently admitted to IP care experienced a mean LOS of 12 h 30 min [95% CI: 279–1221 min] compared with a mean LOS of 7 h 13 min [95% CI: 346–520 min; p = 0.015] for children who were discharged to OP care. The extremely long LOS for children with suicide attempt/self-harm diagnoses may have reflected the need for more labor-intensive assessment and/or treatment measures before a telemental health visit could be provided, in addition to the wait for a more secure psych IP bed, as described above.

Length of ED telehealth visit

There were no significant differences in mean length of ED telehealth visit in minutes based on the major MH diagnostic group. There were also no differences in mean length of telehealth visit based on the discharge plan from the ED. Children who were subsequently admitted to IP care experienced a mean length of 63 min per telehealth visit [95% CI: 56–69 min] compared with 59 min [95% CI: 57–61 min] per telehealth visit for children who were subsequently discharged from the ED to OP care.

Discharge plan (IP vs. OP) by major diagnostic group

Table 2 presents the total number of pediatric MH cases by major diagnostic group and IP or OP discharge plan. While the differences in IP versus OP disposition from the ED in comparison with temporal variables have been discussed previously, it is important to note that the vast majority of children in the first 18 months of the study were discharged to receive OP follow-up treatment (87%; n = 76/87) rather than IP admission.

Secondary Outcomes

Total ED costs and reimbursement by payor

As a secondary pilot, ED cost and reimbursement data could be obtained from Hospital A, the CAH ED with the highest number of peds participants (n = 46). The authors wanted to provide a baseline for the future and a general indication of costs and of payors' level of reimbursement for different types of pediatric MH cases being seen in the region's rural CAH EDs.

Total mean ED costs for pediatric MH patients have been stratified and are presented by payor (Medicaid, private pay, and self-pay/uninsured) and by IP versus OP discharge plan (Table 3). The mean ED costs for all cases for children who were subsequently admitted to IP care were ∼2 × –3 × higher than the mean ED costs for children who were subsequently discharged to OP care from the ED [(M = $8,303, 95% CI: $6,390–$10,216) vs. (M = $3,469, 95% CI: $3,145–$3,792); p < 0.001, respectively].

Table 3.

Pediatric Telemental Health Patients' Total ED Costs Compared with Payor Reimbursement and Discharge Planning

		INPATIENT		OUTPATIENT
		N	M [95% CI]	N	M [95% CI]	T TESTS (IP VS. OP)
Total visit billed, amount, USD	Total behavioral ED visits	6	8,303 [6,390–10,216]	40	3,469 [3,145–3,792]	p < 0.001^a
	Payors within-group differences
	Medicaid [A]	3	8,325 [5,140–11,510]	28	3,256 [2,930–3,583]	p < 0.001^a
	Private [B]	3	8,281 [1,868–14,694]	11	3,781 [3,042–4,521]	p = 0.001^a
	Self-pay/uninsured [C]^b	0^b	N/A	1^b	5,971	N/A
	Across payors: t test			p = .117		—
	Across payors: t test			Nonsignificant (t test [A][B])		—
Total reimbursement amount, USD	Total behavioral ED visits	6	3,665 [364–6,965]	40	710 [406–1,013]	p < 0.001^a
	Payors within-group differences
	Medicaid [A]	3	1,673 [−4,448 to 7,795]	28	227 [167–286]	p = 0.349
	Private [B]	3	5,656 [−800 to 12,113]	11	2003 [1,362–2,644]	p = 0.003^a
	Across payors: t test			p < 0.001^a		—
	Across payors: t test			Significant (t test [A][B])		—
Reimbursement, %	Total behavioral ED visits	6	42% [9–75]	40	19% [12–26]	p = 0.007^a
	Payors within-group differences
	Medicaid [A]	3	18% [(−)44–79]	28	7% [5–9]	p = 0.029^a
	Private [B]	3	66% [41–92]	11	51% [37–65]	p = 0.309
	Across payors: t test			p < 0.001^a
	Across payors: t test			Significant (t test [A][B])

Authors' analysis of aggregated electronic patient data.

Denotes statistical significance for temporal IP versus OP outcomes within a payor group (e.g., Medicaid IP vs. OP), and between payor groups (e.g., Medicaid OP compared with private payor OP).

Self-pay results were omitted from statistical analysis (N = 1 OP case).

CI is confidence interval. Bracketed letters [A] and [B] denote results for comparisons across the two payor groups, Medicaid and private payor, based on disposition from the ED.

NA, not applicable.

The mean total payor reimbursement amounts for pediatric MH patients in the ED were significantly lower than the actual ED costs, whether the subsequent patient discharge plan was IP [$3,665, 95% CI: ($364–$6,965)] or OP [$710, 95% CI: ($406–$1,013)] p < 0.001, respectively. Overall, percent reimbursement based on payor differed significantly, and ranged from 19% [95% CI: 12–26] in the case of OP discharge from the ED to 42% [95% CI: 9–75; p = 0.007] for children subsequently admitted to IP care. Percent reimbursement from Medicaid was significantly lower than private payors for both types of cases, that is, patients who were discharged to IP [95% CI: 18%[(−)44–79] vs. 66% (41–92)] and patients who were discharged to OP [95% CI: 7% (5–9) vs. 51% (37–65); p < 0.001, respectively]. There were not sufficient data in the self-pay payor category to include in the cost comparisons.

Figure 1 shows percent reimbursement by major diagnostic group. While the largest single group reflecting the lowest payor reimbursement was suicidal ideation/attempt or self-harm, there was a wide variation in percent reimbursement for depression- and anxiety-related disorders and suicidal ideation/attempt. There were not sufficient data in the substance abuse/overdose category to determine a trend.

Fig. 1.

Reimbursement percent by diagnostic group. ED, emergency department.

Discussion

Descriptive outcomes revealed that depression, mood- or anxiety-related disorders (49%), and suicidal ideation/attempt or self-harm (46%) accounted for 95% of the MH care needs that children presented with during the study. Prevalence of MH issues increased with age across the peds participants. Overall, high school-age students (14 years - < 18 years) comprised the greatest number of peds patients who presented with MH issues, which is consistent with the most recent national data-based trend for predominant age range of children seeking MH treatment.²⁵

Regional Results Compared with State and National Trends in Peds Mental Health

The most recent 2019 report, regarding the primary reasons for children ages 12–17 who sought MH services in the U.S. (rural and nonrural),²⁵ primarily included children presenting with depression (57.2%) and/or anxiety (29.4%).²⁵ These national rates of depression and anxiety were somewhat similar to the proportion of children seeking these MH services in the ED for the current study. The rate of pediatric suicidal ideation, attempt or self-harm reported for this pilot study exceeds the nationally reported average (46% vs. 31.6%, respectively).²⁵ The most recently reported need for substance abuse treatment in the U.S. for children ages 12–17 was at 3.7%,²⁵ which was slightly lower than the proportion of children reported to need substance abuse treatment in this study (5%). It should be noted that the current study included all children presenting with MH issues to the ED, ages 5–17, a broader age range than the national survey study, which may contribute to the study's higher incidence rates overall.

There is also an important caveat for the aforementioned national MH survey data for children ages 12–17: multiple MH diagnoses could be reported for a child on the survey,²⁵ and thus, the total percentages for the distribution of children's reported MH diagnoses exceed 100%. For the current study, the attending physician recorded only one major MH diagnosis, and may have also recorded one or more secondary diagnoses, but only the child's primary MH diagnosis is reported and utilized in statistical calculations for this study.

At the state level in Indiana, 13.8% of children (rural and nonrural) on average reported a major depressive episode in the past year (2018),²⁶ slightly lower than the national average of 14.4%.²⁵ Thus, when the MH survey data are comparatively evaluated at the state and national level utilizing separate diagnoses as defined by the child's MH status during “the past year,” the prevalence of reported depression appears high for this study. Prevalence of substance abuse disorder among children statewide (rural and nonrural, 3.3%)²⁶ for the past year was lower than the national average (3.7%)²⁵; however, the proportion of children presenting with substance abuse disorder in this study was slightly higher (5%).

Suicidality, Depression, and Anxiety Seen as Critical Mental Health Treatment Needs

Regardless of national and state proportional comparisons, suicidality, depression, anxiety, and substance abuse are emerging in this pilot study as critical preventive care and treatment needs that must be a top priority for children and parents living in this region. A recent study of 21 EDs in a rural- and community-based health system revealed some similarities in mix and proportion of MH cases, with 69 pediatric patients treated during 2015.⁷ The most commonly treated conditions for this study were substance abuse, anxiety, suicidality, thought disturbance, and mood (depression/bipolar) disorders. However, for this study, suicidality accounted for only 6%–9% of the MH cases treated across the rural EDs.⁷

Regional Pediatric MH Outcomes Compared with Adult MH Outcomes

For evidence-based comparison, a number of adult MH patients (≥18 years; N = 273) in the current study presented with depression- and anxiety-related diagnoses (34%), suicidal ideation, suicide attempt or self-harm (35%), and substance abuse disorder (31%) in similar proportions.¹⁹ While the number of female patients exceeded male patients nearly 2:1 in the pediatric sample, a trend that is also evident in the national pediatric survey sample,²⁵ numbers of male (49%; n = 134) and female (51%; n = 139) patients in the adult sample were equivalent. In addition to the dramatic increase observed in substance abuse cases in the adult study participants compared with peds participants, there were also two adult patients with homicidal ideation treated in the 25–44 age range in the rural EDs for the current study.¹⁹ Thus, future implementation of an evidence-based plan to promote MH wellness, preventive care, and education, as well as early triage and screening to support patient/provider safety,^5,9,11 becomes imperative for the region's rural EDs.

Pediatric Telemental Health Patient Costs, Payors, and Reimbursement

Based on ED cost and reimbursement data that could be obtained from Hospital A (n = 46) as a substudy, the average amount of $3,469 per pediatric telemental ED costs in 2018 for the current study is comparable with reported costs of care for a 2015 economic evaluation study of pediatric telehealth visits in rural EDs.²⁷ For the 2015 study, the mean reported cost per ED telehealth visit for all pediatric cases was $3,641 in 2013 for a total of 71 pediatric patients for whom telehealth was utilized across 8 rural EDs.²⁷

For the current study, the mean total payor reimbursement amounts for pediatric MH patients in the ED were significantly lower than actual ED costs, whether the subsequent patient discharge from the ED was to IP or OP (p < 0.001) (Table 3 and Fig. 1). The reimbursement percent from Medicaid was significantly lower than private payors for both IP and OP disposition cases (p < 0.001). Low reimbursement rates, including lower rates for rural “presenting” sites for telemedicine for behavioral health patients covered by Medicaid, as well as variable Medicaid reimbursement by MH provider type, have also been reported in several studies.^5,6,17,28

Conclusions

In the initial 18 months of this observational study, it has become evident that the participating rural EDs are treating increasing numbers of youth (and adults) with suicidality or mood- or anxiety-based MH issues, compared with earlier results of regional telehealth network studies dating back to 2010.^12,16,19 With substance abuse issues also trending upward during the high school years, it becomes clear that community stakeholders, policy makers, and funders need to promote a bold, committed focus on MH awareness, prevention, and treatment across all age groups in the schools and among families living in these communities.

As a region, health services research teams need additional resources for more extensive, collaborative MH prevention, screening, and educational efforts with community stakeholders, including medical and nonmedical psych providers, regional school corporations, regional, state, and national organizations, and legislators and policy makers, who are able to advocate for telemental health care awareness, prevention, and treatment to improve access to MH care across a broad range of evidence-driven initiatives. To address other challenges to MH care access for rural and medically underserved populations, Medicaid is the leading payor for MH services in the U.S. based on national claims data.²⁸ Similar to other recent studies, payor reimbursements for telemental health care in the ED were low in this study. Low reimbursements for MH care incentivizes MH care providers to ask for payment per visit up front, an issue that is understandable from the MH provider point-of-view, but one that can make MH care unaffordable from the underinsured or uninsured patient's perspective.

These issues of low reimbursement must be addressed through communicating data-based outcomes in telemental health care for medically underserved children and adults to relevant stakeholder groups at the state and federal levels. Since decreased number of hospital admissions and improved care coordination have been reported as benefits of telemental health implementation,^{5,7
–9,11,14
–16} higher reimbursement rates for telemental health care delivery merit consideration. As Comer and Myers¹² point out, “In addition to setting an agenda for child telemental healthcare research, payer issues and matters of reimbursement for remote care must be resolved in order for child telemental healthcare to fulfill its promise for expanding the reach of supported care to underserved individuals.”^12,p.298

To underscore the effect of the social determinants of health for families living in rural settings, a recent study of over 670,000 children admitted to pediatric hospitals revealed that compared with nonrural children (1) rural children are more likely to reside in a lower income zip code; (2) rural children are more likely to live in a health care provider shortage area; (3) rural children have a greater prevalence of complex chronic health conditions, and (4) rural children frequently experience worse health outcomes.¹⁸ However, recent interventional studies show that telehealth has great potential to improve access to high-quality specialty care that is similar to in-person care,^5

–8 especially in rural U.S. counties that are experiencing health care provider shortages in mental health.^9

–12,17 Additional research, resources, and policy supports are needed to bridge the gap in mental health care for children and families who need it.

Footnotes

Acknowledgments

The content and conclusions of this study are those of the authors and should not be construed as the official position or policy of, nor should any endorsement be inferred by, the HRSA, HHS, or the U.S. Government.

Disclosure Statement

D.H and H.R. are employed by Union Hospital, which serves as the hub for the WVRTN and provides telemedicine services. The other authors have no competing financial interests to report.

Funding Information

This study was supported by the Health Resource and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant number H1WRH31447 as part of an extension of the Tele-emergency Network Grant Program.

References

Bolin

, Bellamy

, Ferdinand

, et al. Rural healthy people 2020: New decade, same challenges. J Rural Health, 2015; 31:326–333.

McCance-Katz

, et al. Interdepartmental Serious Mental Illness Coordinating Committee (ISMICC). 2017. Report to Congress: “The Way Forward: Federal Action for a System That Works for All People Living with Serious Mental Illness (SMI) and Serious Emotional Disturbance (SME) and Their Families and Caregivers.” U.S. Department of Health and Human Services (DHHS), December 13, 2017. Available at https://www.samhsa.gov/sites/default/files/programs_campaigns/ismicc_2017_report_to_congress.pdf (last accessed August 12, 2019 ).

Health Resource Services Administration's (HRSA) Rural Health Information (RHI) Hub, “What are the workforce challenges in providing rural mental health services?” Available at https://www.ruralhealthinfo.org/topics/mental-health#statistics (last accessed September 3, 2019 ).

Moore

, Stocks

, Owens

. Trends in emergency department visits, 2006–2014. HCUP Statistical Brief #227. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ), 2017.

Butterfield

. Telepsychiatric evaluation and consultation in emergency care settings. Child Adol Psych Clin North Am, 2018; 27:467–478.

Marcin

, Shaikh

, Steinhorm

. Addressing health disparities in rural communities using telehealth. Ped Res, 2016; 79:1–8.

Meyer

, McKean

, Blegen

, Demaerschalk

. Emergency Department Telepsychiatry Service Model for a Rural Regional Health System: The First Steps. Telemed J E-Health, 2019; 25:18–24.

Sharma

, Fleishhut

, Barchi

. Telemedicine and its transformation of emergency care: A case study of one of the largest US integrated healthcare delivery systems. Intl J Emerg Med, 2017; 10:1–4.

Rachal

, Sparks

, Zazzaro

, Blackwell

. Highlight in telepsychiatry and behavioral health emergencies. Psychiatr Clin North Am, 2017; 40:585–596.

10.

Shore

, Yellowlees

, Caudill

, Johnston

, Turvey

, et al. Best practices in video-conferencing based telemental health April 2018. Telemed J E-Health, 2018; 24; 1–6.

11.

Salmoiraghi

, Hussain

. A systematic review of the use of telepsychiatry in acute settings. J Psychiatr Pract, 2015; 21:389–393.

12.

Fairchild

, Ferng

, Laws

, Hardesty

, Rahmouni

. Telehealth Decreases Rural Emergency Department Wait Time for Behavioral Health Patients in a Group of Midwestern Hospitals. Telemed J E Health, 2019; 25:1154–1164.

13.

Mohr

, Young

, Harland

, Skow

, Wittrock

, Bell

, Ward

. Emergency department telemedicine shortens rural time-to-provider and emergency department transfer times. Telemed J E Health, 2018; 24:582–593.

14.

Mohr

, Vakkalanka

, Ward

, et al. Telemedicine Use Decreases Rural Emergency Department Length of Stay for Transferred North Dakota Trauma Patients. Telemed J E-Health, 2018; 24:194–202.

15.

Narasimhan

, Druss

, Hockenberry

JU et al

. Impact of a telepsychiatry program at emergency departments statewide on the quality, utilization, and costs of mental health services. Psychiatr Serv, 2015; 66:1167–1172.

16.

Southard

, Neufeld

, Laws

. Telemental health evaluations enhance access and efficiency in a critical access hospital emergency department. Telemed J E Health, 2014; 20:664–668.

17.

Comer

, Myers

. Future Directions in the use of telemental health to improve the accessibility and quality of children's mental health services. J Child Adol Psychopharm, 2016; 26:296–300.

18.

Peltz

, Wu

, White

, Wilson

, Lorch

, Thurm

, Hall

, Berry

. Characteristics of rural children admitted to pediatric hospitals. Pediatrics, 2016; 137:1–9.

19.

Rahmouni

, Hardesty

, Ferng

, Fairchild

. Wabash Valley Rural Telehealth Network Mental Health Treatment, HRSA's Responding to the Rural Substance Use Crisis: Promoting Community Action and Tele-Behavioral Health: Preliminary Results Presentation. June, 2019, Rockville, MD.

20.

STATSAmerica. (2017). USA Counties in Profile. Available at http://www.statsamerica.org/uscp/default.aspx (last accessed August 7, 2019 ).

21.

Robert Wood Johnson Foundation (2019). County Health Rankings and Roadmaps. Available at http://www.countyhealthrankings.org/app/indiana/2018/overview. (last accessed August 6, 2019 ).

22.

Health Resources and Services Administration (HRSA) (2019). HRSA Data Warehouse, HPSA Find Results: State: Indiana; Discipline: Mental Health. Available at https://datawarehouse.hrsa.gov/tools/analyzers/HpsaFindResults.aspx. (last accessed July 28, 2019 ).

23.

Agency for Healthcare Research Quality (AHRQ). Clinical Classification software categorization guide. Available at https://www.hcupus.ahrq.gov/toolssoftware/ccs/CCSCategoryNames_FullLabels.pdf (last accessed January 20, 2019 ).

24.

von Elm

, Altman

, Egger

, Pocock

, Gøtzsche

, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. PLoS Med, 2007; 4:e296.

25.

SAMHSA. 2019. Report, National Survey on Drug Use and Health: Model-Based Prevalence Estimates, 50 States and the District of Columbia. Available at https://www.samhsa.gov/data/sites/default/files/cbhsqreports/NSDUHDetailedTabs2018R2/NSDUHDetTabsSect9pe2018.htm (last accessed August 10, 2019 ).

26.

2017 National Survey on Drug Use and Health: Detailed Tables. Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services (HHS), and RTI International, a registered trademark and trade name of Research Triangle Institute, Research Triangle Park, North Carolina. Work by RTI was performed under Contract No. HHSS283201300001C. Adams, KT, et al. State to Nat'l comparisons at: https://www.samhsa.gov/data/report/comparison-2008-2009-and-2016-2017nsduh-state-prevalence-estimates. (last accessed August 10, 2019 ).

27.

Yang

, Dharmar

, Yoo

, Leigh

, Kuppermann

, Roman

, Nesbitt

, Marcin

. Economic evaluation of pediatric telemedicine consultations to rural emergency departments. Med Decis Making, 2015; 35:773–783.

28.

Douglas

, Xu

, Heggs

, Wrenn

, Mack

, Rust

. Assessing telemedicine utilization by using Medicaid claims data. Psychiatric Serv, 2017; 68:173–178.