Showing Up Is Half the Battle: The Impact of Telehealth on Psychiatric Appointment Attendance for Hospital-Based Intensive Outpatient Services During COVID-19


Introduction

The COVID-19 pandemic prompted a broadband acceleration in telehealth adoption to deliver psychiatric services across the United States,1 and indeed across the globe.2 This was necessitated, in large part, due to stay-home orders and physical distancing precautions that were implemented to slow the spread of infection.3 To mitigate risk for negative outcomes for individuals at increased risk of psychiatric hospitalization, continuation of services was critical. With the support of key policy and regulation changes, telehealth has been a key player in timely provision and continuation of these services.4–6

Telehealth for psychiatric services has a strong basis of empirical support,7,8 and recently published observations have reported increased odds of attending a telepsychiatry visit compared with an in-person visit for routine adult outpatient treatment services9 and early support for feasibility and acceptability of these rapidly deployed virtual outpatient psychiatry services.2,10,11 However, the impact of widespread and rapid deployment of intensive outpatient virtual services, including structured group psychotherapy, for higher acuity populations during the pandemic needs further evaluation.12–14 In addition, concerns have been documented regarding amplification of preexisting15 health care disparities and inequities in access to care in the wake of these large-scale shifts to telehealth for vulnerable populations, including racial and ethnic minorities, rural populations, socially and economically disadvantaged individuals, and older individuals.16–19

Over and above insurance coverages for telehealth services, disparities in access to technology (including stable internet services, and devices) and familiarity with technology are two key factors identified as potentially linked to a potentially widening digital divide.18 Monitoring patterns of attendance to virtual psychiatric treatment in the pandemic has important implications for highlighting the potential gaps in availability of intensive treatment services for vulnerable populations as well as supporting advocacy for the continued protection of access to telehealth services.

To examine whether rapidly deployed telehealth services have maintained availability and impacted use of available intensive outpatient (IOP) services for psychiatrically high-risk individuals, the current study examined appointment attendance rates for IOP services provided via telehealth versus in-person among two high-risk psychiatric populations: Adults (aged 18 and older) and Adolescents (aged 12–17) in a large hospital-based setting. Additional analyses were conducted to examine rates of appointment attendance according to age, race, insurance, and type of diagnostic treatment program.

Methods

This project and these data were part of a systematic, data-guided effort to improve clinical care and monitor the impact of rapid telehealth adoption within the setting. This study was designated as linked to this overarching quality improvement effort and did not require additional Institutional Review Board approval or oversight.

The Setting

Yale New Haven Psychiatric Hospital (YNHPH) offers comprehensive IOP psychiatric services for adolescents and adults in a large metropolitan hospital-based setting. IOP services are group-based treatments designed for individuals in need of intensive therapeutic services following a psychiatric hospitalization or to prevent a hospitalization. The programs are structured, supportive, and use a variety of group therapy interventions to help increase coping skills to manage symptoms, improve interpersonal and problem-solving skills, and to prevent relapse. In addition to group psychotherapy, the IOPs include targeted individual psychotherapy and crisis management, family involvement, psychiatric medication management and consultation, recreation or art therapy, care management services to support community and school/occupational functioning, and aftercare resource coordination.

The IOPs for both Adults and Adolescents provide 3 h of group-based treatment 3–4 days a week for a period of up to 6 weeks. Each treatment program has between one and four tracks, and each track within the program has the capacity to serve up to 12 individuals each. Descriptions of the specialized treatment programs, including the evidence-based psychotherapies as well as target diagnostic treatment populations, are given in Table 1. Patients are assigned to a treatment program based on an initial diagnostic clinical interview and comprehensive assessment of clinical need.

Table 1. Treatment Tracks and Services Offered According to Population

POPULATION TREATMENT PROGRAM DESCRIPTION OF POPULATION EVIDENCE-BASED PRACTICES USED
Adult
  Mood disorders
• Single track offered
IOP for individuals with difficult-to-treat depression Cognitive behavior therapy
Transitional aged youth
• Single track offered
IOP for young adults aged 18–25 with general mental health concerns; primarily depression, anxiety, and emotion dysregulation Cognitive behavior therapy; dialectical behavior therapy
Dual diagnosis
• Two identical tracks offered
IOP for individuals with co-occurring mental health and substance abuse concerns Motivational enhancement therapy; cognitive behavior therapy
Dialectical behavior therapy
• General track
• Substance use disorder track
IOP for individuals diagnosed with borderline personality disorder and/or with chronic suicidal ideation and/or self-injurious behaviors; substance use disorder track treats individuals with co-occurring substance abuse Dialectical behavior therapy
General mental health adult
• Three identical tracks offered
IOP for individuals with general mental health concerns, including anxiety, depression, trauma, and stressor-related disorders Cognitive behavior therapy
Adolescent
  General adolescent
• Four identical tracks offered
IOP for youth with transdiagnostic mental health concerns, including anxiety, depression, trauma, suicidality and/or self-injurious behaviors, and emotion dysregulation Cognitive behavior therapy; dialectical behavior therapy; acceptance and commitment therapy

Within the larger services setting, preexisting telehealth solutions to deliver individual-level psychiatric services were used in combination with emergently designed and rapidly deployed virtual group-based services to preserve IOP programming structure.13 For a detailed description of the service setting as well as immediate responses during the COVID-19 pandemic, readers are referred to a recent article by the authors,14 which documents the rapid development and deployment of virtual group-based psychotherapy services.

On March 17, 2020, YNHPH suspended a substantive proportion of in-person ambulatory services, including all group psychotherapy services. YNHPH began immediate provision of telephonic telehealth sessions on March 23, 2020, and deployed a comprehensive telehealth strategy to include virtual IOP psychotherapy groups beginning on April 6, 2020. YNHPH began a partial reopening of a limited number of in-person IOP services for adults beginning July 13, 2020.

Data and Analyses

Observational data were queried from the hospital system electronic medical record (EMR) from October 1, 2019, to July 31, 2020, to document patterns in appointment attendance, including appointment method (telehealth vs. in-person), insurance, treatment program, and demographics. Demographics for each population are summarized in Table 2. For any given treatment day, each service a patient was scheduled to receive is classified as a unique appointment in the EMR. At the IOP level of care, patients are scheduled for a minimum of 3 h of structured clinical services, or appointments per treatment day (e.g., three psychotherapy groups; two psychotherapy groups; and one medication management session). This study examined rates of attending these scheduled appointments. That is, whether the patients presented to their appointment during the scheduled time.

Table 2. Demographics for Adult and Adolescent Intensive Outpatient Program Patients Treated Between October 1, 2019, and July 31, 2020

  ADULT POPULATION ADOLESCENT POPULATION TOTAL POPULATION
Overall, n (unique individuals) 775 233 1,008
Age, M (SD) 37.5 (15.4) 15.1 (1.5) 32.3 (16.4)
Gender, n (%)
 Female 449 (57.9) 172 (73.82) 621 (61.6)
 Male 326 (42.1) 61 (26.18) 387 (38.39)
Race/ethnicity, n (%)
 Hispanic 88 (11.4) 40 (17.2) 128 (12.7)
 Non-Hispanic, Black 151 (19.5) 34 (14.6) 185 (18.4)
 Non-Hispanic, Other 34 (4.4) 9 (3.9) 43 (4.3)
 Non-Hispanic, White 493 (63.6) 139 (59.7) 632 (62.7)
 Unknown/not listed 9 (1.2) 11 (4.7) 20 (2.0)
Insurance status, n (%)
 Medicaid 322 (41.6) 104 (44.6) 426 (42.3)
 Medicare 73 (9.4) 0 (0.0) 73 (7.2)
 Managed care 211 (27.2) 60 (25.8) 271 (26.9)
 BC/BS 138 (17.8) 57 (24.5) 195 (19.4)
 Commercial 21 (2.7) 8 (3.4) 29 (2.88)
 Other 10 (1.3) 4 (1.7) 14 (1.4)

Within the study, telehealth refers to a live, synchronous communication with a patient and provider. Telehealth types included telephonic/audio only, individual video-based services, and group-level video-based telehealth services. Table 3 summarizes the appointments for IOP patients according to treatment modality (in-person, telephone telehealth, televideo telehealth) and according to the population group (i.e., adult or adolescent) between October 1, 2019, and July 31, 2020. Finally, Table 4 summarizes the unique IOP patient count by mode of IOP service delivery (in person, telehealth, and combined for patients who received some in-person services and some telehealth services during the system transition to telehealth at the start of the pandemic) between October 1, 2019, and July 31, 2020.

Table 3. Unique Intensive Outpatient Program Patient Count, by Mode of Intensive Outpatient Program Service Delivery Between October 1, 2019, and July 31, 2020

  IN-PERSON ONLY TELEHEALTH ONLY BOTH MODES TOTAL UNIQUE PATIENTS
N % N % N % N %
Adolescent 133 65.5 56 27.6 14 6.9 203 23.4
Adult 485 72.8 118 17.7 63 9.5 666 76.6
Total 485 71.1 174 20.0 77 8.9 869 100.0

Table 4. Appointments for Intensive Outpatient Program Patients by Treatment Modality Between October 1, 2019, and July 31, 2020

TREATMENT MODALITY
  IN-PERSON APPOINTMENTS TELEPHONE APPOINTMENTS TELEVIDEO APPOINTMENTS TOTAL COMBINED APPOINTMENTS
N % OF TOTAL APPTS N % OF TOTAL APPTS N % OF TOTAL APPTS N % OF TOTAL APPTS
Adolescent 2,693 72.9 6 0.2 997 27.0 3,696 23.9
Adult 8,283 70.5 92 0.8 3,371 28.7 11,746 76.1
Total population 10,976 71.1 98 0.6 4,368 28.3 15,442 100.0

Chi-squared analyses were utilized to evaluate whether there were differences in proportion of attended appointments for in-person versus telehealth IOP appointments from October 1, 2019, to July 31, 2020, for adults and adolescents. Next, chi-squared analyses were used to examine differences in appointment attendance for scheduled IOP services by race, insurance, and according to treatment program type (e.g., dual diagnosis track, mood disorders) for adults and adolescents.

Results

Adult Population

Volume data for scheduled IOP appointments in total, by insurer, race, and for group-only services by treatment program for adults are summarized in Table 5. When examining all scheduled appointments between October 1, 2019, and July 31, 2020, analyses revealed a statistically significantly higher proportion of attended appointments for telehealth IOP services of all types (individual, family, medication management, group-based contacts) compared with in-person IOP services of all types for adults (Table 5). Further analyses revealed statistically higher proportions of attended appointments for telehealth compared with in-person appointments for commercially, Medicaid-, and Medicare-insured adults (Table 5).

Table 5. Pearson Chi-Square Comparison of Proportion of Attended Appointments Between Telehealth and In-Person Services, by Population, Race, Payer, and Treatment Program

POPULATION IN-PERSON TELEHEALTH χ2 P-VALUE DF % DIFFERENCE
N, ATTENDED APPOINTMENTS N, SCHEDULED APPOINTMENTS %, ATTENDED N, ATTENDED APPOINTMENTS N, SCHEDULED APPOINTMENTS %, ATTENDED
Adult
 All IOP services 20,711 33,647 61.55 8,534 11,815 72.23 434.37 0.000 1 10.68
 Payer: Commercial 9,769 14,278 68.42 4,496 5,966 75.36 97.39 0.000 1 6.94
 Payer: Medicaid 7,586 13,772 55.08 2,618 3,932 66.58 165.65 0.000 1 11.50
 Payer: Medicare 3,242 5,326 60.87 1,420 1,902 74.66 116.34 0.000 1 13.79
 Race: Hispanic/Latinx 3,497 1,851 52.93 1,088 669 61.49 24.55 0.000 1 8.56
 Race: Non-Hispanic, black 6,259 3,393 54.21 1,466 886 60.44 18.64 0.000 1 6.23
 Race: Non-Hispanic, white 21,793 14,061 64.52 8,749 6,586 75.07 316.99 0.000 1 10.55
 Race: Non-Hispanic, other 809 572 70.70 288 249 86.46 27.99 0.000 1 15.76
 Race: Unknown 1,297 841 64.84 232 169 72.84 5.26 0.018 1 8.00
 IOP groups: Mood disorders 2,316 3,520 65.80 841 1,132 74.29 28.36 0.000 1 8.49
 IOP groups: Transitional aged youth 3,089 5,208 59.31 1,616 2,412 67.00 41.23 0.000 1 7.69
 IOP groups: Dual diagnosis (2) 3,784 8,039 47.07 737 1,313 56.13 37.10 0.000 1 9.06
 IOP groups: Dialectical behavior therapy, general 1,004 1,343 74.76 826 1,003 82.35 19.30 0.000 1 7.59
 IOP groups: Dialectical behavior therapy, substance use disorder 818 1,382 59.19 588 840 70.00 26.28 0.000 1 10.81
 IOP groups: General mental health adult (3) 4,013 6,458 62.14 2,296 2,942 78.04 231.59 0.000 1 15.90
Adolescent
 All IOP services 7,146 10,091 70.82 2,433 3,219 75.58 27.49 0.000 1 4.77
 Payer: Commercial 3,473 4,817 72.10 1,718 2,169 79.21 39.58 0.000 1 7.11
 Payer: Medicaid 3,496 5,072 68.93 714 1,031 69.25 0.04 0.837 1 0.33
 Race: Hispanic/Latinx 1,907 1,395 73.15 295 176 59.66 22.74 0.000 1 -13.49
 Race: Non-Hispanic, black 1,856 1,274 68.64 313 210 67.09 0.30 0.585 1 -1.55
 Race: Non-Hispanic, white 5,470 3,840 70.20 2,250 1,768 78.58 56.29 0.000 1 8.38
 Race: Non-Hispanic, other 342 235 68.71 173 137 79.19 6.288 0.012 1 10.48
 Race: Unknown 514 402 78.21 191 145 75.92 0.42 0.516 1 -2.29
 IOP groups: General adolescent (four tracks) 6,437 9,070 70.97 2,131 2,777 76.74 35.327 0.000 1 5.77

With respect to race, there was a statistically significantly higher proportion of attended appointments for telehealth compared with in-person appointments across all race/ethnicity groups, particularly among non-Hispanic white adults who showed in excess a 10% increase (Table 5). Lastly, when examining IOP group-based attendance by treatment program, analyses indicated a statistically significantly higher proportion of attendance for telehealth IOP group-based appointments compared with in-person IOP group-based appointments for all five treatment programs (Table 5).

Adolescent Population

Volume data for all scheduled IOP appointments in total, by insurer, race, and for group-only services for adolescents are summarized in Table 5. When examining all scheduled appointments between October 1, 2019, and July 31, 2020, analyses revealed a statistically significantly higher proportion of attended appointments for telehealth IOP services of all types (individual, family, medication management, group-based contacts) compared with in-person IOP services of all types for adolescents (Table 5). Further analyses revealed statistically higher proportions of attended appointments for telehealth compared with in-person IOP appointments for commercially insured adolescents. However, no statistically significant difference in appointment attendance for Medicaid enrollees was found (Table 5).

With respect to race, non-Hispanic white identified youth demonstrated statistically higher proportions of attended appointments for telehealth compared with in-person IOP appointments, whereas Hispanic/Latinx identified youth demonstrated a significant decrease in the proportion of attended appointments (Table 5). There were no statistically significant differences in attendance for non-Hispanic black identified youth. Finally, when evaluating IOP group-based psychotherapy attendance in adolescents, analyses again indicated a statistically significantly higher proportion of attendance for telehealth IOP group appointments compared with in-person IOP group appointments (Table 5).

Discussion

The current study found that IOP appointment attendance rates were significantly higher for telehealth services compared with in-person services for both adult and adolescent subpopulations. These overall findings are consistent with observations that have been reported in general outpatient psychiatry settings with lower patient contact frequency.20 There were mixed findings among the adolescent subpopulation with respect to insurance and race/ethnicity. Of note, telehealth services were not previously offered in YNHPH until mid-March 2020, and thus, the overall visit volume for telehealth services was lower compared with in-person services. A discussion of results, including implications, follows.

Adults were more likely to attend telehealth appointments regardless of insurer, with a nearly 14% increase in IOP attendance for adults with Medicare insurance and a nearly 12% increase in attendance for those with Medicaid insurance. Over 50% of the adult population accessed services via Medicaid (41.6%) or Medicare (9.4%) insurance. Increased attendance for telehealth services in these vulnerable and high-risk populations underscores the importance of maintaining key regulatory, policy, and payment provisions for telehealth made by the Centers for Medicare and Medicaid Services (CMS) for supporting vulnerable populations.

For example, CMS expanded telehealth benefits to lift certain reimbursement limitations, including allowing for reimbursement for telehealth services for mental health outside of rural settings as well as allowing for patients to receive services outside of traditional provider settings, such as hospitals, clinics, or other medical facilities, and instead receive their service elsewhere (e.g., the patient’s home, place of work)4 Patients were also not required to report to a facility for the purposes of establishing a prior relationship with providers before initiating telehealth services, allowing for initiation of services and continued care without requiring patients to travel and risk exposure. Rightly, systems and providers are concerned that critical regulatory and reimbursement changes may not outlast the pandemic, leading to a widespread reduction of virtual services and by extension access and availability of care.10,21

Furthermore, the trend for increased rates of attending appointments for telehealth compared with in-person services was demonstrated across racial and ethnic groups for all IOP service contacts among adults. Further investigation is warranted to evaluate the implications for telehealth’s role in maintaining access to intensive psychiatric services among vulnerable populations, including publicly insured racial and ethnic minority adults, although these initial findings are promising.

Impressively, telehealth was linked to increased attendance rates for group-based IOP psychotherapy services for adults regardless of clinical program type. Indeed, there was a nearly 16% increase in attendance among adults in the transdiagnostic IOP group services. Furthermore, telehealth attendance outperformed in-person attendance for individuals dually diagnosed with substance use disorders and mental health problems, suggesting that telehealth may be an important mechanism in increasing treatment attendance. Treatment attendance for individuals being treated for co-occurring mental health and substance use disorders is particularly important given the implications for poorer outcomes and increased emergency services usage.22,23

Future studies to evaluate whether increased attendance has links to changes in treatment adherence, engagement, and/or outcomes in this difficult-to-treat population are needed. Given the broad range of presenting concerns treated within the intensive outpatient setting, these findings document important preliminary support for the value of telehealth in both sustaining access for intensive services and increasing use of available resources among adults.

For adolescents, the overall population demonstrated increased attendance for telehealth services compared with in-person services. When examining demographic factors, higher rates of attendance for telehealth were observed for commercially insured youth although not for Medicaid-insured youth. In the pre-COVID context, youth receiving outpatient mental health services are vulnerable to staggering rates of treatment drop-out.24 Thus, understanding what methods might reduce this vulnerability and within which population subgroups is critical and telehealth may be an especially important player among commercially insured youth.

According to the 2018 U.S. Census Bureau Report,25 nearly 36% of children had Medicaid or Children’s Health Insurance Program (CHIP) in 2018. Both Medicaid and CHIP target low-income children, making it imperative to continue to monitor trends in access to services, including appointment attendance, among Medicaid-insured psychiatrically vulnerable youth.

Mixed results were also observed with respect to race, such that higher rates of attendance to telehealth were observed among non-Hispanic white youth, although no differences were found for non-Hispanic black youth. Furthermore, Hispanic/Latinx youth were observed to have decreased rates of attendance for telehealth compared with in-person during the rapid deployment period. These findings, while limited to this sample, highlight the need to investigate the potential for special challenges or vulnerabilities (e.g., psychosocial, familial, systemic, and structural barriers) that are not able to be overcome among racial/ethnic minority youth. Special advocacy to ensure that these youth are able to receive virtual services and continue care may be warranted for racial and ethnic minority psychiatrically high-risk youth in particular as waves of the pandemic shift and in-person services are suspended or significantly reduced for periods of time.

In addition, trends for racial and ethnic minority youth will also warrant further investigation as agencies and institutions providing care seek to maintain and expand telehealth offerings as a part of a long-term care delivery strategy beyond the pandemic to ensure that disparities are not exacerbated in the virtual space. Qualitative approaches, including interviews to better understand factors influencing treatment for these youth, may also be helpful in monitoring patterns of telehealth usage.

Despite these important contributions, the current study is not without limitations. Although we observed variations in appointment attendance by age, race, insurance, and clinical program for rapidly deployed virtual group-based services, we did not examine other markers of acceptability or outcomes. Attending scheduled appointments is an important foundation for understanding treatment, although it is only one piece of a larger puzzle that must include treatment completion rates and clinical outcomes.

Furthermore, an exploration of barriers to attendance would provide further rationale for the changes in rates of appointment attendance. Although these data were unavailable for the current study, this work is a natural future direction to better understand the potential contributors to increased attendance among telehealth appointments, as well as potential barriers to attendance, such as challenges with technology or access to private space.

Within the health system, current quality improvement efforts are underway to better understand patient experience with telehealth more broadly, including understanding domains that may support better attendance for telehealth appointments (e.g., time savings; convenience; structural barriers such as transportation and broadband internet access; and access to private spaces). Furthermore, clinical outcome measurement data are being collected to shed light on the quality and efficacy of IOP telehealth compared with in-person services. Finally, future studies will necessarily need to examine potential interactions of race, insurance, and diagnosis to further understand the impact of telehealth services for these populations.

Appreciating the implications of telehealth on attendance of intensive psychiatric services within the context of the pandemic and beyond is essential for health systems, policy makers, and providers as they navigate the future of telehealth in their service settings. The current data indicated that telehealth increased appointment attendance (i.e., use of available services) for a high-risk psychiatric population in a large hospital-based system. In addition, these findings provide continued support for the feasibility of intensive outpatient psychiatric telehealth services as an important tool to maintaining availability to needed care during the COVID 19 pandemic. Importantly, these offerings were made possible by key regulatory adjustments. Advocacy efforts should continue to pursue support for maintaining these regulatory changes, to ensure that access to critical services delivered in a format that improves attendance continues.

Acknowledgments

The authors thank Carol Cestaro, LCSW, for her leadership of the ambulatory teams at YNHPH, who collectively have a significant role in making these services possible.

Disclosure Statement

No competing financial interests exist.

Funding Information

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References

  • 1. Hollander JE, Carr BG. Virtually perfect? Telemedicine for Covid-19. N Engl J Med 2020;382:1679–1681. Crossref, MedlineGoogle Scholar
  • 2. Gilbert AW, Billany JCT, Adam R, et al. Rapid implementation of virtual clinics due to COVID-19: Report and early evaluation of a quality improvement initiative. BMJ Open Qual 2020;9:e000985. Crossref, MedlineGoogle Scholar
  • 3. Jernigan DB. Update: Public health response to the Coronavirus disease 2019 outbreak—United States, February 24, 2020. MMWR Morb Mortal Wkly Rep 2020;69:216–219. Crossref, MedlineGoogle Scholar
  • 4. Centers for Medicare & Medicaid Services. Medicare and Medicaid programs; policy and regulatory revisions in response to the COVID-19 public health emergency. 2020. Available at https://www.cms.gov/Medicare/ (last accessed July 12, 2020). Google Scholar
  • 5. Cowan KE, McKean AJ, Gentry MT, Hilty DM. Barriers to use of telepsychiatry: Clinicians as gatekeepers. Mayo Clin Proc 2019;94:2510–2523. Crossref, MedlineGoogle Scholar
  • 6. Keesara S, Jonas, Schulman K. Covid-19 and health care’s digital revolution. N Engl J Med 2020;382:e82. Crossref, MedlineGoogle Scholar
  • 7. Bashshur RL, Shannon GW, Bashshur N, Yellowlees PM. The empirical evidence for telemedicine interventions in mental disorders. Telemed J E Health 2016;22:87–113. LinkGoogle Scholar
  • 8. Bashshur RL, Shannon G, Krupinski EA, Grigsby J. Sustaining and realizing the promise of telemedicine. Telemed J E Health 2013;19:339–345. LinkGoogle Scholar
  • 9. Avalone L, Barron C, King C, et al. Rapid telepsychiatry implementation during COVID-19: Increased attendance at the largest health system in the United States. Psychiatr Serv 2021 [Epub ahead of print]; DOI: 10.1176/appi.ps.202000574. Crossref, MedlineGoogle Scholar
  • 10. Chen JA, Chung W-J, Young SK, et al. COVID-19 and telepsychiatry: Early Outpatient Experiences and implications for the future. Gen Hosp Psychiatry 2020;66:89–95. Crossref, MedlineGoogle Scholar
  • 11. Tse J, LaStella D, Chow E, et al. Telehealth acceptability and feasibility among people served in a community behavioral health system during the COVID-19 pandemic. Psychiatr Serv 2021; [Epub ahead of print]; DOI: 10.1176/appi.ps.202000623. CrossrefGoogle Scholar
  • 12. Hom MA, Weiss RB, Millman ZB, Christensen K, Lewis EJ, Cho S, et al. Development of a virtual partial hospital program for an acute psychiatric population: Lessons learned and future directions for telepsychotherapy. J Psychother Integr 2020;30:366–382. CrossrefGoogle Scholar
  • 13. Childs AW, Unger A, Li L. Rapid design and deployment of intensive outpatient group-based psychiatric care using telehealth during COVID-19. J Am Med Inform Assoc 2020;27:1420–1424. Crossref, MedlineGoogle Scholar
  • 14. Childs AW, Klingensmith K, Bacon SM, Li L. Emergency conversion to telehealth in hospital-based psychiatric outpatient services: Strategy and early observations. Psychiatry Res 2020;293:113425. Crossref, MedlineGoogle Scholar
  • 15. Cook BL, Zuvekas SE, Carson N, Wayne GF, Vesper A, McGuire TG. Assessing racial/ethnic disparities in treatment across episodes of mental health care. Health Serv Res 2014;49:206–229. Crossref, MedlineGoogle Scholar
  • 16. Sullivan SR, Bell K-A, Spears AP, et al. No community left behind: A call for action during the COVID-19 pandemic. Psychiatr Serv 2021;72:89–90. Crossref, MedlineGoogle Scholar
  • 17. Jaffe DH, Lee L, Huynh S, Haskell TP. Health inequalities in the use of telehealth in the United States in the lens of COVID-19. Popul Health Manag 2020;23:368–377. LinkGoogle Scholar
  • 18. Weber E, Miller SJ, Astha VA, Janevic T, et al. Characteristics of telehealth users in NYC for COVID-related care during the Coronavirus pandemic. J Am Inform Assoc 2020;27:1949–1954. Crossref, MedlineGoogle Scholar
  • 19. Velasquez D, Mehrotra A. Ensuring the growth of telehealth during COVID-19 does not exacerbate disparities in care. Health Affairs Blog, 2020; [Epub ahead of print]; DOI: 10.1377/hblog20200505.591306 CrossrefGoogle Scholar
  • 20. Yang J, Landrum MB, Zhou L, Busch AB. Disparities in outpatient visits for mental health and/or substance use disorders during the COVID surge and partial reopening in Massachusetts. Gen Hosp Psychiatry 2020;67:100–106. Crossref, MedlineGoogle Scholar
  • 21. American Hospital Association. Fact sheet: The future of telehealth—protecting patient access to care. Available at https://www.aha.org/fact-sheets/2020-07-30-fact-sheet-future-telehealth-protecting-patient-access-care (last accessed October 22, 2020). Google Scholar
  • 22. Watkins KE, Hunter SB, Wenzel SL, Tu W, et al. Prevalence and characteristics of clients with co-occurring disorders in outpatient substance abuse treatment. Am J Drug Alcohol Abuse 2004;30:749–764. Crossref, MedlineGoogle Scholar
  • 23. Urbanoski K, Cheng J, Rehm J, Kurdyak P. Frequent use of emergency departments for mental and substance use disorders. Emerg Med J 2018;35:220–225. Crossref, MedlineGoogle Scholar
  • 24. De Haan AM, Boon AE, De Jong JTVM, et al. A meta-analytic review on treatment dropout in child and adolescent outpatient mental health care. Clin Psychol Rev 2013;33:698–711. Crossref, MedlineGoogle Scholar
  • 25. Berchick ER, Barnett JC, Rachel D. Upton Current Population Reports, P60-267(RV), Health Insurance Coverage in the United States: 2018. U.S. Government Printing Office, Washington, DC, 2019. Google Scholar





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