Comparison of Treatment Modality Crossovers in Telehealth and In-Person Behavioral Health Treatment in Rural Communities.

Background: Treatment crossovers occur when one mode of treatment is begun and then a different mode of treatment is utilized. Treatment crossovers are frequently examined in randomized controlled trials, but have been rarely noted or quantitatively evaluated in usual care treatment studies. The purpose of this analysis is to examine the extent of modality crossovers during behavioral health treatment. Methods: The nonrandomized, prospective, multisite research design involved two active treatment groups-a telehealth treatment cohort and an in-person treatment cohort. Treatment modality (telehealth or in person) during each encounter was compared overall and across two time periods (pre- and during the COVID-19 pandemic) between the telehealth cohort and the in-person cohort. Results: Overall, modality crossovers were relatively uncommon (6.3%). However, patients in the in-person treatment cohort were more than twice as likely to have an encounter through telehealth (8.5%) than patients in the telehealth treatment cohort were to have an in-person encounter (3.4%) even though they had the same average number of encounters. The occurrence of off-mode encounters was particularly influenced by the onset of the COVID-19 pandemic. Conclusions: In this multisite usual care study comparing telehealth and in-person behavioral health treatment, modality crossovers were more common in the in-person cohort than the telehealth cohort, especially during the COVID-19 pandemic. Because telehealth availability has increased, crossovers are likely to increase in patients receiving multiple encounters for behavioral or chronic conditions and their occurrence should be noted by both researchers and practitioners.

Telehealth and In-Person Behavioral Health Services in Rural Communities Before and During the COVID-19 Pandemic: Multisite Prospective Cohort Study.

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.

Technologically Punctual? A Preliminary Evaluation of Differences between Face-to-Face and Video Check-In Times for Initial Mental Health Services.

Video-based telehealth provides mental health services to underserved populations. As decision makers reevaluate service offerings following COVID-19, it remains prudent to evaluate the utility of ongoing telehealth options among rural healthcare facilities, the primary healthcare source for many rural individuals. As research continues to compare video and face-to-face services, one understudied component is attendance. Although video-based telehealth has demonstrated improved show-rates for mental health services when compared to face-to-face methods, limited work has clarified whether video improves patient punctuality for these appointments, a documented challenge prevalent for patients with mental health-related concerns. A retrospective electronic record review of psychiatry, psychology, and social work initial patient visits between 2018-2022 was conducted (N = 14,088). Face-to-face visits demonstrated a mean check-in time of -10.78 min (SD = 26.77), while video visits demonstrated a mean check-in time of -6.44 (SD = 23.87). Binary logistic regressions suggested that increased video usage was associated with a decreased likelihood of late check-in (B = -0.10, S. E. = 0.05, Exp(B) = 0.91, 95% CI = 0.83 - 1.00). Exploratory binary logistic regressions evaluated age, sex, race, ethnicity, specialty, insurance type, and diagnostic classification influence on video initial visits. Increased video usage was associated with a statistically decreased likelihood of late check-in; however, clinically, both face-to-face and video visits exhibited mean check-in times prior to the initial visit's scheduled time. As such, mental health organizations are encouraged to continue offering both face-to-face and video as options to foster evidence-based practices to the broadest population.

Change in Drug Use Disorders Identification Test - Consumption (DUDIT-C) with Telehealth Treatment Compared to in-Person Treatment.

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.

Comparison of Telehealth and In-Person Behavioral Health Services and Payment in a Large Rural Multisite Usual Care Study.

Background: Telehealth and in-person behavioral health services have previously shown equal effectiveness, but cost studies have largely been limited to travel savings for telehealth cohorts. The purpose of this analysis was to compare telehealth and in-person cohorts, who received behavioral health services in a large multisite study of usual care treatment approaches to examine relative value units (RVUs) and payment. Methods: We used current procedural terminology codes for each encounter to identify RVUs and Medicare payment rates. Mixed linear regression models compared telehealth and in-person cohorts on RVUs, per-encounter payment rates, and total-episode payment rates. Results: We found the behavioral health services provided by telehealth to have modest, but statistically significantly lower RVUs (i.e., less provider work in time spent and case complexity), per-encounter payments, and total episode payments than the in-person cohort. Despite Medicare rates discounting payments for nonphysician providers and the in-person cohort using clinical social workers more frequently, the services provided by the telehealth cohort still had lower payments. Thus, the differences observed are due to the in-person cohort receiving higher payment RVU services than the telehealth cohort, which was more likely to receive briefer therapy sessions and other less expensive services. Conclusions: Behavioral health services provided by telehealth used services with lower RVUs than behavioral health services provided in-person, on average, even after adjusting for patient demographics and diagnosis. Observed differences in Medicare payments resulted from the provider type and services used by the two cohorts; thus, costs and insurance reimbursements may vary for others.

Comparison of in-person vs. telebehavioral health outcomes from rural populations across America.

BACKGROUND: This study investigates outcomes from two federal grant programs: the Evidence-Based Tele-Behavioral Health Network Program (EB THNP) funded from September 2018 to August 2021 and the Substance Abuse Treatment Telehealth Network Grant Program (SAT TNGP) funded from September 2017 to August 2020. As part of the health services implementation program, the aims of this study were to evaluate outcomes in patient symptoms of depression and anxiety across the programs' 17 grantees and 95 associated sites, with each grantee having data from telehealth patients and from an in-person comparison group. METHODS: The research design is a prospective multi-site observational study. Each grantee provided data on a nonrandomized convenience sample of telehealth patients and an in-person comparison group from sites with similar rural characteristics and during the same time period. Patient characteristics were collected at treatment initiation, and clinical outcome measures were collected at baseline and monthly. The validated clinical outcome measure instruments included the Patient Health Questionnaire-9 (PHQ-9) for depression symptoms and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety-related symptoms. Linear mixed models, with grantee as the random effect, were used to determine the association of behavioral health delivery (telehealth versus in-person) on the one-month change in PHQ-9 and GAD-7 while adjusting for covariates. RESULTS: Across a total of 1,514 patients, one-month change scores were improved indicating that PHQ-9 and GAD-7 scores decreased from baseline to the one-month follow-up at similar rates in both the in-person and telehealth groups. Reduction in scores averaged 2.8 for the telehealth treatment group and 2.9 for the in-person treatment group in the PHQ-9 subsample and 2.0 for the telehealth treatment group and 2.4 for the in-person treatment group in the GAD-7 subsample. There was no statistically significant association between the modality of care (telehealth treatment group versus in-person comparison group) and the one-month change scores for either PHQ-9 or GAD-7. Individuals with higher baseline scores demonstrated the greatest decrease in scores for both measures. Upon adjusting for baseline scores and grantee program, patient demographics were not found to be significantly associated with change in anxiety or depression symptoms. CONCLUSION: In our very large pragmatic study comparing behavioral health treatment delivered to a population of patients in rural, underserved communities, we found no clinical or statistical differences in improvements in depression or anxiety symptoms as measured by the PHQ-9 and GAD-7 between patients treated via telehealth or in-person.

An Innovative Approach to Care: Integrating Mental Health Services Through Telemedicine in Rural School-Based Health Centers.

In rural communities, primary care providers continue to provide mental health services, and about 70% of children and adolescents identified to have a psychiatric disorder never receive treatment. A telehealth model for providing integrated mental health services in a school-based health clinic has the potential to increase access to specialized care for the most vulnerable youths. This column provides an overview of the strategies used to implement and integrate such a model in West Virginia. Operationalization, barriers, challenges, and judicious resource use are discussed. Appropriate reimbursement for services and state-specific legislation to ensure consistent revenue to sustain the program are considered.