Telehealth-Facilitated Mental Health Care Access and Continuity for Patients Served at the Health Resources and Services Administration

Abstract

Objective:

The Health Resources and Services Administration (HRSA)–funded health centers provide critical behavioral health services to historically and medically underserved individuals with complex health and social needs. As health centers rapidly expanded telehealth in response to COVID-19, the objective of the study was to assess whether telehealth use was associated with utilization and continuity within mental health care received by patients of HRSA-funded health centers.

Methods:

Cross-sectional analyses, using a nationally representative sample of adult patients with mental health needs from the 2022 Health Center Patient Survey (n = 1,044), explored associations between telehealth use and utilization of mental health services from primary care providers (PCP) and continuity of counseling services. Multivariate logistic regression models accounted for predisposing, enabling, and need factors to assess the influence of telehealth use on utilization and continuity outcomes.

Results:

After adjusting for patient-level factors, telehealth users with mental health needs had statistically significant and higher odds of receiving mental health services from a PCP at a health center compared with nontelehealth users (adjusted odds ratios [aOR] = 2.60, p < 0.001; 95% confidence interval [CI] [1.50, 4.52]). Telehealth-using patients receiving counseling services had statistically significant and higher odds of receiving all counseling services at a health center compared with nontelehealth users (aOR = 3.65, p < 0.001, 95% CI [2.04, 6.53]).

Conclusions:

Telehealth facilitates mental health care utilization and continuity for historically and medically underserved patients at health centers and can be an important tool for care management and coordination for patients with mental health needs, particularly during and following public health emergencies.

Introduction

Telehealth, the use of telecommunication or video technology to provide health services, has been an important tool to reduce barriers and expand access to mental health care^1
–3 while providing comparable clinical outcomes.⁴ Telehealth has also facilitated integrated behavioral health care delivery to geographically isolated and medically underserved populations.^5

–9

The United State (U.S.) Department of Health and Human Services Health Resources and Services Administration (HRSA)–funded health centers are community-based and patient-directed organizations that provide comprehensive primary care—including behavioral health services—to historically and medically underserved communities regardless of a patient’s ability to pay.¹⁰ Health centers served over 30 million patients in 2022,¹¹ many of whom have complex social and health needs. Approximately one-half of health center patients report at least one mental health diagnosis.¹²

HRSA has advanced mental health care access at health centers by promoting behavioral health integration into primary care through supplemental funding, technical assistance, and training.¹³ Health centers have integrated delivery by increasing screening, directly providing on-site and virtual services, expanding the workforce, and developing referral systems.^5,13 Behavioral health integration at health centers has increased the provision of mental health care during primary care visits,¹⁴ increased access to mental health providers,¹⁴ and resulted in high patient satisfaction.^15,16

As part of integration, many health centers adopted and scaled telehealth prior to the COVID-19 public health emergency (PHE) despite a lack of reimbursement parity for telehealth services.¹⁷ With the onset of the COVID-19 PHE, increased patient demand and enacted policies providing reimbursement for virtual care facilitated rapid telehealth adoption and use at health centers: 43% of health centers offered telehealth in 2019 compared with 99% in 2020–2021.¹¹ Over half of health center mental health visits in 2020 and 2021 were provided virtually compared to 2% in 2019.¹¹

Previous studies have explored virtual mental health care provided by health centers since the increased use of telehealth in 2020. These studies have analyzed trends in telehealth utilization using electronic health records or claims-based data, evaluated pilots, and explored patient/provider perspectives on the shift to telehealth within specific service settings.^5,6,18
–20 There is an opportunity to better understand telehealth-facilitated utilization of integrated behavioral health services and mental health care among health center patients nationally.

To address this gap, our retrospective study’s objective was to assess whether telehealth use was associated with utilization and continuity within mental health care services received by health center patients. Based on previous studies,^6,21 we hypothesized that telehealth utilization would be associated with a higher likelihood of patients receiving mental health services and continuity within care.

Methods

DATA SOURCE AND SAMPLE

Our data source was the 2022 Health Center Patient Survey (HCPS). HCPS collects nationally representative data on the experiences of patients served by health centers funded by HRSA under Section 330 of the Public Health Service Act. The target population of the 2022 HCPS was residents of the 50 states and the District of Columbia who met the requirements of receiving services from an HRSA-funded health center. HCPS employed a three-stage sampling design (health centers, service sites, and then eligible patients). To be eligible, patients had to receive care in-person or virtually at least once in the 12 months before recruitment. The HCPS sought to increase the sample of patients who identified as American Indian/Alaska Native (AIAN), Native Hawaiian/Other Pacific Islander (NHOPI), or Asian race, as well as patients 65 years or older. Administration occurred in English, Spanish, Chinese, Tagalog, and Vietnamese. Data collection occurred between January 2021 and March 2022. The COVID-19 PHE necessitated a mixed-mode design: 63% of interviews occurred in-person and 37% by phone. The 2022 HCPS collected data from 102 unique organizations across 318 service sites with an 85% response rate resulting in 4,414 interviews. All patients gave informed consent for participation, and the Research Triangle International institutional review board granted ethical approval for data collection.²²

To identify patients with a need for mental health care, our analytic sample was adults (≥18 years of age) who responded that they or a physician thought they should see a professional about their mental health, emotions, or nerves in the last 12 months. We focused on adults due to the degree of missing data of interest for children/adolescents, proxy interviews for many child/adolescent patients, and overall differences between children/adolescents and adults in self-assessing the need for mental health care.²³ Our final analytic sample was n = 1,044, which included patients from all U.S. Census regions.

VARIABLES

Dependent variables

We used two dependent variables that measured the utilization and continuity of mental health care at the reference health center. The first was if a patient reported receiving mental health care from their primary care provider (PCP) in the last 12 months to reflect utilization. For a subset of patients that received mental health counseling services, the second dependent variable representing care continuity was if a patient received all counseling services from the same care team at the reference health center in the last 12 months.

Independent variable

Our primary independent variable was if a patient had at least one audio/video telehealth visit (versus none) from the reference health center in the last 12 months. All health centers reflected in the sample offered telehealth services according to the 2021 Uniform Data System.¹¹ In sensitivity analysis, we tested an alternative categorical specification of our independent variable measuring the intensity of telehealth utilization (total telehealth visits).

Covariates

Using a conceptual framework derived from Andersen’s model of health care utilization,²⁴ and a review of similar telehealth-focused studies using Andersen’s model,^25
–27 we identified potential covariates to control for predisposing, enabling, and need factors that may influence utilization.

Predisposing factors included the patient’s age (18–44, 45–65, and 65+ years),⁹ sex (male, female),²⁶ education (less than high school, high school, or more than high school),²⁶ and race/ethnicity (Hispanic/Latino [H], Non-Hispanic [NH]/H AIAN, NH/H Asian, NH Black/African American, NH/H NHOPI, NH White).⁹ Certain racial groups included both NH and H ethnicity to increase analytical sample sizes and retain as many racial groups as possible.

Enabling factors included insurance status (Medicare, Medicaid, other public insurance, private, or uninsured)²⁶ and income relative to Federal Poverty Guidelines (FPG) (≤100%, 101–200%, or >200% of FPG).⁹ We included language preference (English-only versus non-English language or non-English/English mix) and patient-reported location of residence (rural versus urban, suburban, or other) as they have been found to influence the utilization of telehealth.^{8,26,28

–33} To account for differential access to virtual care by unhoused patients,^34
–36 we included a variable if a patient had experienced homelessness in the last 12 months.³⁷ To control for the potential impact of travel time to a health center on telehealth use,³⁸ we created a dichotomous variable of high versus low travel time to the reference health center based on the median.

Need factors included a patient’s overall health status (excellent/very good/good versus fair/poor). To control for existing medical conditions and the concurrent need for medical services, we created a count-based variable of chronic medical diagnoses (hypertension, diabetes, cardiovascular disease, asthma, obstructive lung disease, kidney disease, cancer, and HIV/AIDS).³⁷ We included dichotomous variables if a patient ever received specific mental health diagnoses: depression, generalized anxiety, panic disorder, bipolar disorder, and schizophrenia. We also created a variable of total mental health diagnoses to explore cumulative diagnostic load. Given the period of data collection, we included a dichotomous variable assessing if the patient was impacted by COVID-19 (tested positive for COVID-19, unable to get care because of COVID-19, and/or unable to work because of COVID-19 versus not impacted).

STATISTICAL ANALYSIS

All analyses used weights that reflect HCPS’ complex survey design, including multistage sampling, clustering, and poststratification to align the final HCPS patient sample with the characteristics of the national health center population. We first conducted descriptive analyses for all variables of interest. We then conducted unadjusted bivariate analyses (chi-squared tests) to assess the associations between any telehealth utilization and dependent variables, as well as all covariates. Assessment of collinearity using Cramer’s V for all categorical predictors did not show evidence of collinearity. We fit multiple logistic regression models for each dependent variable accounting for complex survey design, progressively adding predisposing, enabling, and need covariates. We identified final covariates using our conceptual framework and Wald tests to identify the most parsimonious model. Final models controlled for age, sex, race/ethnicity, education, insurance status, rural location, overall health status, number of mental health diagnoses, and COVID-19 impact. Variance inflation factors for all models did not show multicollinearity of predictors. We used Stata Standard Edition version 17.0 and svy functions to conduct all analyses.³⁹

Results

Table 1 presents descriptive statistics of patients with mental health needs. Most patients were 18–44 years old (53.5%), female (63.6%), and NH White (52.6%), with 19.1% identifying as NH Black/African American, 14.8% Hispanic/Latino, 8.9% H/NH AIAN, 2.5% H/NH Asian, and 2.1% H/NH NHOPI. Across insurance coverage, 47.7% of patients had Medicaid coverage and 23.0% were uninsured.^40,41 Regarding need factors, 47.4% of patients with mental health needs reported being in excellent, very good, or good health; 32.1% reported two mental health diagnoses and 43.5% reported three or more diagnoses. The most common mental health diagnoses were depression (83.0%), generalized anxiety (74.5%), and panic disorder (33.6%); 30.6% and 9.8% reported a diagnosis of bipolar disorder and schizophrenia, respectively. Within the sample, 55.6% reported receiving telehealth services from the health center in the last year. Overall, 68.2% of patients reported receiving mental health care from their PCP at a health center. Among patients who received counseling for mental health needs, 44.0% received all counseling services at a health center.

Table 1.

Descriptive Statistics of Adult Health Center Patients Reporting Mental Health Needs (N = 1,044)

FACTOR	UNWEIGHTED OBSERVATIONS	WEIGHTED %	SE	95% CI
Predisposing factors
Age
18–44 years	409	53.5	3.2	47.2, 59.7
45–64 years	548	40.4	3.1	34.2, 46.5
65+ years	87	6.2	1.3	3.7, 8.6
Sex
Male	338	36.4	3.2	30.1, 42.7
Female	706	63.6	3.2	57.3, 69.9
Race/ethnicity
Hispanic (H)/Latino	267	14.8	3.0	8.9, 20.7
H/Non-Hispanic (NH) Asian	38	2.5	0.9	0.7, 4.3
H/NH American Indian/Alaska Native	97	8.9	2.1	4.7, 13.1
NH Black/African American	240	19.1	4.3	10.6, 27.6
H/NH Native Hawaiian/Other Pacific Islander	27	2.1	0.7	0.6, 3.5
NH White	373	52.6	5.1	42.4, 62.8
Education
Less than high school	284	25.0	2.8	19.4, 30.6
High school	329	31.8	2.9	26.1, 37.6
More than high school	431	43.2	3.2	36.9, 49.5
Enabling factors
Insurance status
Privately obtained insurance	109	16.1	2.4	11.4, 20.8
Medicare	241	11.6	1.5	8.6, 14.7
Medicaid	524	47.7	3.2	41.4, 54.0
Other public insurance	60	1.5	0.4	0.8, 2.3
Uninsured	110	23.0	3.2	16.8, 29.3
Income—Federal Poverty Guidelines (FPG)
Less than or equal to 100% FPG	624	53.4	3.2	47.1, 59.7
101–200% FPG	264	30.0	3.1	24.0, 36.0
200% or more FPG	147	16.6	2.3	12.1, 21.1
Language preference
English only	740	78.5	2.4	73.7, 83.3
Non-English language or non-English language/English mix	304	21.5	2.4	16.7, 26.3
Location of patient residence
Urban/suburban/other	778	57.7	3.3	51.3, 64.1
Rural	266	42.3	3.3	35.9, 48.7
Experiencing homelessness	257	9.0	1.2	6.6, 11.5
Above median travel time to health center	525	55.3	3.2	49.0, 61.6
Need factors
Overall health status
Fair/poor	579	52.6	3.2	46.3, 58.9
Excellent/very good/good	464	47.4	3.2	41.1, 53.7
Number of chronic medical diagnoses^a
0	268	32.1	3.0	26.1, 38.0
1	307	29.3	2.9	23.5, 35.0
2+	469	38.6	3.1	32.5, 44.7
Depression	889	83.0	2.6	77.9, 88.1
Generalized anxiety	766	74.5	2.8	68.9, 80.1
Panic disorder	392	33.6	3.0	27.7, 39.4
Bipolar disorder	350	30.6	2.9	24.9, 36.4
Schizophrenia	164	9.8	1.7	6.5, 13.1
Number of mental health diagnoses^b
0	68	9.5	2.3	5.0, 14.0
1	173	15.0	2.1	10.9, 19.0
2	306	32.1	3.0	26.2, 37.9
3+	497	43.5	3.2	37.2, 49.7
Impacted by COVID-19	377	34.9	3.1	28.7, 41.0
Independent variable
Telehealth use in the past 12 months	552	55.6	3.2	49.4, 61.9
Dependent variables
Visited primary care physician for mental health needs	713	68.2	3.0	62.3, 74.1
Received all mental health counseling at health center	285	44.0	3.8	36.4, 51.5

Source: Health Center Patient Survey, 2022.

Chronic medical diagnoses include hypertension, diabetes, cardiovascular disease, asthma, obstructive lung disease, kidney disease, cancer, and HIV/AIDS.

Mental health diagnoses include depression, generalized anxiety, panic disorder, bipolar disorder, and schizophrenia.

CI, confidence interval; SE, standard error.

Table 2 presents the results of an unadjusted bivariate analysis of our utilization outcomes by telehealth use. A statistically significant and higher proportion of patients who received mental health care from a PCP used telehealth (62.3% versus 37.7%, p < 0.01) as did patients who received all mental health counseling services at a health center (72.5% versus 27.5%, p < 0.001).

Table 2.

Mental Health Service Utilization Outcomes by Use of Telehealth Among Adult Health Center Patients Reporting Mental Health Needs

	NO TELEHEALTH USE		ANY TELEHEALTH USE
UTILIZATION OUTCOME	WEIGHTED %	SE	WEIGHTED %	SE	p-VALUE
Visited primary care physician for mental health needs	37.7	5.6	62.3	5.6	0.002
Received all mental health counseling at health center	27.5	6.9	72.5	6.9	0.001

Source: Health Center Patient Survey, 2022.

p-values reported from chi-squared tests account for complex survey design.

SE, standard error.

Table 3 presents adjusted odds ratios (aOR) from multivariate logistic regression models of associations between telehealth use and mental health service utilization outcomes. After adjusting for influential predisposing, enabling, and need factors, telehealth users with mental health needs had statistically significant and higher odds of receiving mental health care from a PCP at a health center compared to nontelehealth users (aOR = 2.60, p < 0.001; 95% confidence interval [CI] [1.50, 4.52]). Telehealth-using patients receiving counseling services had statistically significant higher odds of receiving all counseling services at a health center compared to nontelehealth users (aOR = 3.65, p < 0.001, 95% CI [2.04, 6.53]) after adjusting for influential patient-level factors. Sensitivity analyses confirmed patients with more telehealth visits generally had higher odds of both outcomes compared to nontelehealth users (Supplementary Table S1).

Table 3.

Multivariate Logistic Models of Association Between Telehealth Utilization and Mental Health Care Utilization Outcomes Among Adult Health Center Patients Reporting Mental Health Needs

FACTOR	VISITED PRIMARY CARE PHYSICIAN FOR MENTAL HEALTH NEEDS		RECEIVED ALL MENTAL HEALTH COUNSELING AT HEALTH CENTER
FACTOR	aOR	95% CI	aOR	95% CI
Telehealth use in the past 12 months (ref. none)	2.60^***	1.50, 4.52	3.65^***	2.04, 6.53
Age (ref. 18–44 years)
45–64 years	0.90	0.52, 1.57	1.52	0.79, 2.95
65+ years	0.85	0.34, 2.17	1.54	0.37, 6.37
Female (ref. male)	0.41^**	0.22, 0.77	2.15^*	1.11, 4.15
Race/ethnicity (ref. non-Hispanic/Latino White)
H/NH Asian	1.30	0.20, 8.38	1.41	0.17, 11.80
H/NH Native Hawaiian/Other Pacific Islander	8.65^**	1.95, 38.34	1.31	0.36, 4.82
NH Black/African American	0.74	0.37, 1.47	0.92	0.50, 1.70
Hispanic/Latino	0.96	0.49, 1.86	0.66	0.25, 1.75
H/NH American Indian/Alaska Native	1.85	0.81, 4.22	0.18^*	0.04, 0.84
Education (ref. high school)
Less than high school	0.45	0.19, 1.08	0.43	0.18, 1.05
More than high school	0.90	0.45, 1.83	1.01	0.46, 2.24
Insurance status (ref. privately insured)
Medicare	0.76	0.29, 1.99	1.68	0.54, 5.25
Medicaid	0.94	0.38, 2.32	1.82	0.66, 5.05
Other public insurance	1.66	0.40, 6.77	0.87	0.24, 3.20
Uninsured	1.69	0.58, 4.90	4.13^*	1.09, 15.63
Rural (ref. urban/suburban/other)	1.06	0.62, 1.81	0.61	0.35, 1.04
Health status (ref. excellent/very good/good)
Fair/poor	1.01	0.55, 1.83	0.46^*	0.23, 0.92
Number of mental health diagnoses^a	1.56^***	1.24, 1.97	0.80	0.59, 1.08
Impacted by COVID-19 (ref. not impacted)	1.06	0.47, 2.36	1.39	0.76, 2.55
Observations	1,014		690

Source: Health Center Patient Survey, 2022.

p < 0.05.

p < 0.01.

***

p < 0.001.

Mental health diagnoses include depression, generalized anxiety, panic disorder, bipolar disorder, and schizophrenia.

aOR, adjusted odds ratios; CI, confidence interval; H, Hispanic; NH, non-Hispanic.

In the adjusted model for receiving mental health care from a PCP, females had statistically significant and lower odds of this outcome compared to males (aOR = 0.41, p < 0.01, 95% CI [0.22, 0.77]), while those patients identifying as H/NH NHOPI had statistically significant higher odds of this outcome compared to NH White patients (aOR = 8.65, p < 0.01, 95% CI [1.95, 38.34]). The number of mental health diagnoses was positively associated with accessing mental health care from a PCP; for each additional mental health diagnosis, the odds of integrated behavioral health service use increased by 56% (aOR = 1.56, p < 0.001, 95% CI [1.24, 1.97]).

In the adjusted model for receiving all counseling services at a health center, female patients had statistically significant and higher odds of this outcome compared to males (aOR = 2.15, p < 0.05, 95% CI [1.11, 4.15]), as did uninsured patients compared to privately insured patients (aOR = 4.13, p < 0.05, 95% CI [1.09, 15.63]). Several factors were associated with significantly lower odds of receiving all counseling services at the health center. Patients identifying as H/NH AIAN had lower odds compared to NH White patients (aOR = 0.18, p < 0.05, 95% CI [0.04, 0.84]), and those in fair/poor health had lower odds compared with those in good/very good/excellent health (aOR = 0.46, p < 0.05, 95% CI [0.23, 0.92]).

Discussion

Our study found over half of health center patients with mental health needs used telehealth. Further, telehealth-users were more likely to receive mental health care from a PCP and receive all counseling services at a health center compared to nonusers. These findings suggest that virtual care at health centers was critical in providing a regular source of mental health care for patients with mental health needs, particularly during the COVID-19 PHE. As health centers continue to provide virtual care as a service delivery option,¹¹ telehealth may continue to be an instrumental factor in ensuring access to behavioral health care for patients with mental health needs.

Our findings that telehealth facilitated access to mental health care within a primary care setting is consistent with past literature indicating telehealth supports increased engagement of patients seeking mental health care at health centers.⁶ Previous research has also shown that patients may be more willing to accept behavioral health care from PCPs.⁴² Such preferences represent important opportunities for health centers to integrate behavioral health services with primary care and continue to provide increased access to mental health care through integrated care models that appropriately leverage virtual care modalities.

Our findings that telehealth was associated with care continuity are also supported by existing evidence, such that health center telehealth users were more likely to remain in psychotherapy within six months following initiation²¹ and that telehealth improved care continuity for those with serious mental illness.⁴³ In addition to providing virtual care, health centers’ holistic approach to primary care delivery, including care coordination and provision of enabling services that facilitate patient access, may reduce attrition in counseling services. These services combined with virtual counseling services may reinforce care continuity for health center patients.

Our study also found significant associations between patient characteristics and mental health utilization. We found that female patients were less likely to visit a PCP for mental health care but more likely to remain in counseling services. Our findings reflect that female patients are more likely to actively seek a specialist for their mental health needs (compared with men who are more likely to be connected to mental health care via medical care) and to continue treatment after the initial visit.^44,45

While previous research found most racial/ethnic minority health center patients were more likely to use mental health care during COVID-19,⁴⁴ our study highlights possible racial/ethnic disparities in utilization and continuity of mental health care. Contrary to the literature showing lower rates of mental health diagnoses among Asian and NHOPI patients,⁴⁶ the greater likelihood of NHOPI patients receiving mental health care from PCPs may reflect the increased demand for mental health care among Asian and NHOPI patients during the COVID-19 PHE.^46,47 However, this result should be interpreted with caution given the small sample size of this group. Our finding that H/NH AIAN patients were less likely to receive all counseling at a health center may reflect documented disparities in mental health care access among AIAN individuals, who have faced complex, historic barriers to mental health care.⁴⁸ Developing culturally centered virtual mental health care services and tailoring strategies to support patients with access barriers, such as through the provision of enabling services like care coordination, may help improve these disparities.⁴⁹

Our finding that patients with overall poorer health were less likely to access all counseling services at a health center generally mirrors national trends of lower likelihood of mental health treatment among those with worse overall health.⁵⁰ However, the greater odds of counseling retention among uninsured patients are contrary to national findings that uninsured patients are less likely to receive mental health treatment.⁵⁰ This finding may be a result of health centers serving all patients regardless of their ability to pay and their comprehensive approach to primary care delivery.

The positive association between total mental health diagnoses and accessing mental health care from PCPs likely reflects the higher need for care and care coordination for patients with multiple mental health conditions. With 77% of health centers achieving Patient-Centered Medical Home recognition,⁵¹ they are uniquely positioned to provide care coordination and team-based delivery models that support the needs of patients with multiple mental health conditions.

While our study did not directly explore the influence of telehealth policies, research has shown that state-level telehealth policy changes during the COVID-19 PHE were influential in increasing virtual mental health care provision.⁵² Several policies affecting telehealth at health centers have become permanent under Medicare, including allowing health centers to serve as distant site providers for behavioral health services, removing originating site restrictions, and permitting the use of audio-only platforms for behavioral health services.⁵³ State Medicaid telehealth policies affecting health centers vary.⁵⁴ While policies may facilitate health center patient access to virtual behavioral health services, health center practice may require adaptation as policies evolve.

LIMITATIONS

Our study is subject to limitations. Due to HCPS’ cross-sectional design, we can only explore associations and cannot make causal inferences. Our findings are potentially influenced by acquiescence and recall bias. We also could not identify which services were accessed via telehealth but only if a patient used telehealth for any service. Furthermore, we could not distinguish telehealth service modalities (e.g., live-video, audio-only). Sample sizes limited our ability to explore the differential influence of only-telehealth versus hybrid service use. While HCPS asked if patients received mental health care from a specialist, we did not use this variable due to low response rates within our study population. Small sample sizes within some categorical variables may have limited ability to detect statistical differences or led to wider confidence intervals on some point estimates. Finally, HCPS’ sampling design did not allow for controlling unmeasured state-level differences, like telehealth policy. Despite these limitations, this study has the unique strength of providing a nationally representative view on the associations between telehealth and mental health care utilization and continuity at health centers.

Conclusions

Our study provides a novel contribution to telehealth’s role in enabling mental health care utilization through integrated care models at health centers. As care continuity is critical for managing mental health conditions, telehealth is an important tool for care management and may reduce costlier care for health center patients with multiple mental health needs. While additional research is needed to further understand disparities in mental health care, our research suggests that health centers have leveraged telehealth to support the utilization and continuity of mental health care for historically and medically underserved patients.

Footnotes

Authors’ Contributions

B.P.: Conceptualization (lead), formal analysis (lead), methodology (lead), writing—original draft (lead), and writing—reviewing and editing (equal). H.Y.-L.: Conceptualization (supporting), formal analysis (supporting), and writing—reviewing and editing (equal). C.B.: Conceptualization (supporting), writing—reviewing, and editing (supporting). M.W.: Conceptualization (supporting), writing—reviewing and editing (supporting), and supervision (supporting). A.S.: Supervision (lead).

Disclaimer

The views expressed in this publication are solely the opinions of the authors and do not necessarily reflect the official policies of the U.S. DHHS or the HRSA, nor does mention of the department or agency names imply endorsement by the U.S. government.

Disclosure Statement

The authors report no conflicts of interest.

Funding Information

No funding was received for this article.

Supplementary Material

Supplementary Table S1

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Supplementary Material

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Telehealth-Facilitated Mental Health Care Access and Continuity for Patients Served at the Health Resources and Services Administration–Funded Health Centers

Abstract

Objective:

Methods:

Results:

Conclusions:

Introduction

Methods

DATA SOURCE AND SAMPLE

VARIABLES

Dependent variables

Independent variable

Covariates

STATISTICAL ANALYSIS

Results

Discussion

LIMITATIONS

Conclusions

Footnotes

Authors’ Contributions

Disclaimer

Disclosure Statement

Funding Information

Supplementary Material

References

Supplementary Material