Jonathan Neufeld

Background: The COVID-19 pandemic triggered widespread adjustments across the US health care system. Telehealth use showed a substantial increase in mental health conditions and services due to acute public health emergency (PHE) behavioral health needs on top of long-standing gaps in access to behavioral health services. How health systems that were already providing behavioral telehealth services adjusted services and staffing during this period has not been well documented, particularly in rural areas with chronic shortages of behavioral health providers and services. Objective: This study investigates patient and treatment characteristic changes from before the COVID-19 PHE to during the PHE within both telehealth and in-person behavioral health services provided in 95 rural communities across the United States. Methods: We used a nonrandomized, prospective, multisite research design involving 2 active treatment groups. The telehealth cohort included all patients who initiated telehealth treatment regimens during the data collection period. A comparison group included a cohort of patients who initiated in-person treatment regimen. Patient enrollment occurred on a rolling basis, and data collection was extended for 3 months after treatment initiation for each patient. Chi-square tests compared changes from pre-PHE to PHE time periods within telehealth and in-person treatment cohorts. The dependent measures included patient diagnosis, clinicians providing treatment services, and type of treatment services provided at each encounter. The 4780 patients in the telehealth cohort and the 6457 patients in the in-person cohort had an average of 3.5 encounters during the 3-month follow-up period. Results: The encounters involving anxiety, dissociative, and stress-related disorders in the telehealth cohort increased from 30% (698/2352) in the pre-PHE period to 35% (4632/12,853) in the PHE period (P<.001), and encounters involving substance use disorders in the in-person cohort increased from 11% (468/4249) in the pre-PHE period to 18% (3048/17,047) in the PHE period (P<.001). The encounters involving treatment service codes for alcohol, drug, and medication-assisted therapy in the telehealth cohort increased from 1% (22/2352) in the pre-PHE period to 11% (1470/13,387) in the PHE period (P<.001); likewise, encounters for this type of service in the in-person cohort increased from 0% (0/4249) in the pre-PHE period to 16% (2687/17,047) in the PHE period (P<.001). From the pre-PHE to the PHE period, encounters involving 60-minute psychotherapy in the telehealth cohort increased from 8% (190/2352) to 14% (1802/13,387; P<.001), while encounters involving group therapy in the in-person cohort decreased from 12% (502/4249) to 4% (739/17,047; P<.001). Conclusions: The COVID-19 pandemic challenged health service providers, and they adjusted the way both telehealth and in-person behavioral therapy services were delivered. Looking forward, future research is needed to explicate the interaction of patient, provider, setting, and intervention factors that influenced the patterns observed as a result of the COVID-19 pandemic.

Introduction: A number of reports are available exploring how telehealth use grew during the COVID-19 pandemic and public health emergency. Some have reported variations in telehealth uptake by specialty, but few have explored growth in telehealth utilization by both specialty and state, arguably the most salient combination of regulatory domains. Methods: We extracted telehealth claims from Medicare public use data files in 2019 and 2020. We calculated utilization by state both as raw encounters and as encounters per 10,000 Medicare beneficiaries in each state. We categorized providers into four major groups (primary care, specialty care, nurse practitioners and physician assistants, and behavioral health) to further explore variations in uptake among these groups. We generated tables and maps to display the variations found. Results: Growth in raw telehealth encounter volume was dominated by large states. Growth in telehealth volume per 10,000 beneficiaries was dominated by states in the Northeast and showed four- to fivefold variation between the least and greatest. Growth by state and provider group varied by even wider margins, with some states showing large amounts of growth among some provider groups, but relatively little growth in others. No states showed relatively robust growth in telehealth across all provider groups. Discussion: Growth in telehealth during the public health emergency was generally robust, but varied considerably across states and provider types. Recognizing this variation is important, and further exploring potential sources of variation is an important task for future research.

Background and Objectives: There is little published evidence for the effectiveness of telehealth in the treatment of substance use disorders. Methods: We analyzed Drug Use Disorders Identification Test - Consumption (DUDIT-C) scores from 360 patients who completed the measure as part of outpatient behavioral health treatment at rural clinic sites. Some patients received in-person care, while others received telehealth. Results were analyzed using multiple regression. Results: Mean DUDIT-C scores improved with treatment in both cohorts. Changes on the DUDIT-C were related to initial scores. Treatment modality (telehealth vs in-person) had no distinguishable association with outcomes. Discussion and Conclusions: Results showed no discernible difference in outcomes between telehealth and in-person cohorts. Telehealth was as effective as in-person care in the treatment of substance use disorders, and appears to be equivalent to in-person care in rural outpatient settings.

BACKGROUND The COVID-19 pandemic triggered widespread adjustments across the US health care system. Telehealth use showed a substantial increase in mental health conditions and services due to acute public health emergency (PHE) behavioral health needs on top of long-standing gaps in access to behavioral health services. How health systems that were already providing behavioral telehealth services adjusted services and staffing during this period has not been well documented, particularly in rural areas with chronic shortages of behavioral health providers and services. OBJECTIVE This study investigates patient and treatment characteristic changes from before the COVID-19 PHE to during the PHE within both telehealth and in-person behavioral health services provided in 95 rural communities across the United States. METHODS We used a nonrandomized, prospective, multisite research design involving 2 active treatment groups. The telehealth cohort included all patients who initiated telehealth treatment regimens during the data collection period. A comparison group included a cohort of patients who initiated in-person treatment regimen. Patient enrollment occurred on a rolling basis, and data collection was extended for 3 months after treatment initiation for each patient. Chi-square tests compared changes from pre-PHE to PHE time periods within telehealth and in-person treatment cohorts. The dependent measures included patient diagnosis, clinicians providing treatment services, and type of treatment services provided at each encounter. The 4780 patients in the telehealth cohort and the 6457 patients in the in-person cohort had an average of 3.5 encounters during the 3-month follow-up period. RESULTS The encounters involving anxiety, dissociative, and stress-related disorders in the telehealth cohort increased from 30% (698/2352) in the pre-PHE period to 35% (4632/12,853) in the PHE period (P<.001), and encounters involving substance use disorders in the in-person cohort increased from 11% (468/4249) in the pre-PHE period to 18% (3048/17,047) in the PHE period (P<.001). The encounters involving treatment service codes for alcohol, drug, and medication-assisted therapy in the telehealth cohort increased from 1% (22/2352) in the pre-PHE period to 11% (1470/13,387) in the PHE period (P<.001); likewise, encounters for this type of service in the in-person cohort increased from 0% (0/4249) in the pre-PHE period to 16% (2687/17,047) in the PHE period (P<.001). From the pre-PHE to the PHE period, encounters involving 60-minute psychotherapy in the telehealth cohort increased from 8% (190/2352) to 14% (1802/13,387; P<.001), while encounters involving group therapy in the in-person cohort decreased from 12% (502/4249) to 4% (739/17,047; P<.001). CONCLUSIONS The COVID-19 pandemic challenged health service providers, and they adjusted the way both telehealth and in-person behavioral therapy services were delivered. Looking forward, future research is needed to explicate the interaction of patient, provider, setting, and intervention factors that influenced the patterns observed as a result of the COVID-19 pandemic. CLINICALTRIAL

Introduction: Telemedicine has demonstrated potential to improve access and quality of mental health services in underserved areas. Use of telemedicine to deliver health services may enable a range of synergistic innovations in care practices, but such innovations will require rigorous evaluation. Materials and Methods: We evaluated a telemental health program designed to increase access by eliminating clinician travel time in a multisite rural community mental health center. The program included both traditionally scheduled and “open scheduled” clinics provided via telemedicine. An initial 13-month evaluation showed better access, quality, and sustainability compared with similar services delivered using traditional methods available elsewhere within the organization. A 24-month follow-up analysis was undertaken to determine if initial findings remained consistent. Results: Telemedicine clinics continued to show remarkably consistent advantages in both access and quality compared with traditional services. Cost-efficiency gains were also robust, maintaining a 20-percentage-point advantage in conversion of scheduled time to billable time over traditional clinics. Much of this advantage was attributable to the 20% of clinic volume that was open-scheduled or “walk-in” in nature. Conclusions: This study confirms earlier findings that telemedicine technology can support synergistic innovations in service format (such as “open scheduling”) and maintain measurable advantages in access and quality along with cost-efficiencies past the initial implementation period.