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The Impact of a Primary Care Telepsychiatry Program on Outcomes of Managed Care Older Adults

Published:November 07, 2022DOI:https://doi.org/10.1016/j.jamda.2022.10.004

      Abstract

      Objective

      The goal of this study was to assess the outcomes of a primary-based telepsychiatry intervention program for older managed care enrollees with depression/anxiety and with limited access to in-person psychiatric care.

      Design

      A pre-post design was used to examine service use (n = 218) and severity of depression (n = 204). Enrollment, claims, and depression and anxiety score data were obtained from the medical group. The implementation process and self-reported outcomes were examined.

      Setting and Participants

      The program was funded by the Senior Care Action Network (SCAN) group and implemented by a large medical group serving older adults who were identified as needing outpatient psychiatric care, including those with psychiatric hospitalizations, depression/anxiety disorders, comorbid substance use disorders, or other multiple comorbidities.

      Methods

      Poisson regressions were used to examine changes in predicted rates of outpatient services, emergency department visits, and hospitalizations up to 24 months prior and 24 months following the first telepsychiatry visit. Changes in predicted severity of depression up to 2 quarters prior and 3 quarters following the first telepsychiatry visit were examined.

      Results

      The number of outpatient services declined significantly by 0.24 per patient per 6-month time frame following the first telepsychiatry visit. The number of emergency department visits and hospitalizations also declined after the first visit (0.07 and 0.03 per patient per 6-month time frame, respectively). Depression severity scores also declined in the quarters following the first visit (1.52). The medical group reported improvements in both wait time for appointments and no-show rates with the integration of telepsychiatry in primary care.

      Conclusions and Implications

      The telepsychiatry program lowered service use, depression severity, and increased better access to psychiatry care. The findings highlight the potential benefits of sustaining and expanding the telepsychiatry program by SCAN and other plans facing a limited supply of psychiatrists.

      Keywords

      Existing evidence indicates a shortage of psychiatrists in many areas of the country.
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      Telepsychiatry and e-mental health services: potential for improving access to mental health care.
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      Telehealth benefits offered by Medicare Advantage plans in 2020.
      These developments highlight the importance of identifying effective models of telepsychiatry for aging adults. This is particularly important because aging adults can experience barriers related to physical and cognitive impairment. They can also experience barriers related to Internet connectivity and technological challenges, such as lower ownership of smartphones, tablets, and computers, than younger adults.
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      We evaluated a telepsychiatry program in an underserved, mostly lower population density Southern California location. The population of interest was aging adults with co-occurring physical and mental health conditions and the intervention was designed to address many of the challenges described previously. Our first research question was, to what extent did aging enrollees achieve better outcomes of care following receipt of any telepsychiatry services? The outcomes included use of outpatient and acute care services following their first visit. Our second question was, to what extent did patients with depression experience a reduction in their Patient Health Questionaire-9 (PHQ-9) scores 3 to 6 months following their first telepsychiatry visit? PHQ-9 is a self-administered questionnaire used to identify the presence and severity of depression.
      • Kroenke K.
      • Spitzer R.L.
      • Williams J.B.
      The PHQ-9: validity of a brief depression severity measure.
      These questions focus on 2 outcomes of the program that investigators could assess using rigorous quantitative methods.

      Methods

      Intervention

      The telepsychiatry program was implemented by the Senior Care Action Network (SCAN) Group and was designed to be implemented for 18 months from February 28, 2019, to August 31, 2020. The program was intended to address challenges of limited access to psychiatric care for aging enrollees assigned to a medical group in a mostly lower population density area of Southern California. The medical group had a limited number of psychiatrists and one social worker in its provider network, both prior and during program implementation. The SCAN Group contracted with a telepsychiatry group to provide services in a centrally located large primary care clinic that was further colocated with other specialists.
      The program was primarily intended to identify patients with untreated depression and anxiety diagnoses among aging adults, reduce stigma associated with psychiatric care use, reduce wait time for psychiatric appointment, reduce language barriers to use of psychiatric care, improve follow-through with referrals, reduce the use of acute services and readmissions, and improve mental health and quality-of-life outcomes.
      The medical group contracted with Array Behavioral Care (Array) to deliver integrated telepsychiatry services in English and Spanish.
      • Care A.B.
      Array behavioral care.
      Array is a large national provider of telepsychiatry services in all settings, including hospitals and at home for more than 20 years. One bilingual Array clinician provided care for 8 or 12 hours on alternate weeks and was later joined by a second clinician who provided a total of 8 hours of care. Both psychiatrists were generalists but had extensive experience working with older populations. Array used a secure and HIPAA-compliant virtual care platform remotely operated within the medical group’s primary care clinic site. Array clinicians had remote access to the medical group’s electronic medical records (EMR) and operated similarly to other on-site providers and within the clinic’s workflow. The workflow included setting an appointment for the referred patients at their primary care clinic site, completion of the PHQ-9 administered by a medical assistant, and meeting with the psychiatrist virtually in an examination room similar to any other visit. Visits were scheduled for 45 to 50 minutes for initial evaluation and psychotherapy and 15 to 20 minutes for follow-up visits and medication management. The psychiatrists had the ability to communicate with primary care providers (PCPs) through the EMR and were available for online consultation. PCPs were required to administer the PHQ-9 approximately every 3 months for the duration of the program, either at the next visit or by phone. PCPs were not required to, but they also measured the Generalized Anxiety Disorder (GAD-7) score as needed. GAD-7 measures the presence and severity of anxiety.
      • Spitzer R.L.
      • Kroenke K.
      • Williams J.B.
      • Löwe B.
      A brief measure for assessing generalized anxiety disorder: the GAD-7.
      At the start of the program, an initial examination of enrollees’ medical records by the medical group was conducted to identify patients in need of outpatient psychiatric care including those with psychiatric hospitalizations, depression and anxiety disorders, comorbid substance use disorders, or other multiple comorbidities. These enrollees’ records were then referred to their PCPs for review and potential referral to telepsychiatry (Figure 1). PCPs also referred patients directly to telepsychiatry. Patients who did not decline or miss appointments received a telepsychiatry visit and either received further treatment or were referred back to their PCPs.
      Figure thumbnail gr1
      Fig. 1The SCAN telepsychiatry program referral and work flow.
      The medical group monitored program implementation with the goals of increasing the number of behavioral health referrals, increasing the average number of appointments scheduled per half day, reducing time from referral to appointment, increasing the number of initial and follow-up/return visits, decreasing the no-show rate, and increasing patient satisfaction scores. The medical group also promoted integration of psychiatrists as members of the multidisciplinary clinical team and continuity of care for patients.

      Data

      We interviewed SCAN, the medical group, and one of the Array psychiatrists to gain a better understanding of program implementation. We obtained demographic and health and mental health services claims data from the medical group for patients who received any telepsychiatry services during the implementation period, which began on February 28, 2019, and ended on August 31, 2020. Enrollees with at least 1 telepsychiatry visit during this period were identified. We used the date of first visit to determine the post-period and obtained claims data up to February 28, 2021, to increase the likelihood of having 6 months of observation following the receipt of telepsychiatry services. We also obtained claims data for 2 years before date of first visit, which was from February 27, 2017, to February 27, 2019. Evaluation activities of this project did not meet the definition of human subject research as defined by federal regulations for human subject protections. As such, neither certification or exemption from institutional review board (IRB) review nor IRB approval was required.
      Of the total sample, 60 enrollees younger than 55 years were excluded because they were not the primary population of focus for SCAN. We further excluded 25 individuals who had at least 1 in-person psychiatry visit before their telepsychiatry visit to more clearly assess the likely impact of the program on outcomes. Our final sample for analyses of utilization of services included 218 enrollees with no prior psychiatric care in the pre-period (see Supplementary Figure 1).
      To examine the potential impact of telepsychiatry on patients with depression, we excluded another 14 enrollees because they did not have any PHQ-9 scores or lacked a depression diagnosis before or on the first date of their telepsychiatry visit. Our final sample for analyses of change in depression outcomes was 204 enrollees (Supplementary Figure 1).

      Variables

      The dependent variables included the overall number of outpatient care services, primary care services, specialty care services, all-cause emergency department (ED) visits, and all-cause hospitalizations. These were measured for 6-month periods before and after the program. Another dependent variable was the PHQ-9 average score per quarter. The last variable was the severity of GAD-7, categorized at the recommended severity levels of minimal (0–4), mild (5–9), moderate (10–14), and severe (15–21).
      Time was the main independent variable of interest for assessing changes in service use, PHQ-9, and GAD-7 dependent variables. For the utilization indicators, there were 4 pre-period time indicators (24 to 19 months, 18 to 13, 12 to 7, and 6 to 1) before the date of first visit and 4 post-period indicators (0 to 5 months, 6 to 11, 12 to 17, and 18 to 24) following the date of first visit. For PHQ-9 scores, there were 2 pre-period time indicators (180 to 90 days and 90 days to 7 days) before the first visit and 2 post-period time indicators (8 to 97 days and 98 to 187 days) after the first visit. GAD-7 scores were not consistently available before the first visit, so the time indicators were in relation to the first visit (7 days prior or 7 days after) and the quarter following that visit. We allowed more time for assessment of the pre-PHQ-9 and first GAD-7 scores because many patients had completed these tests either before attending their first visit or shortly after rather than on the day of that visit. A second independent variable of interest used for assessing changes in PHQ-9 scores was diagnosis of depression at the first telepsychiatry visit (vs not).
      The control variables included demographic information such as age on the date of first visit (65–74 and 75 and older vs 55–64), female (vs male), race and ethnicity (Hispanic/Latino and other vs White), preferred language for communication was English (vs other), and marital status (not married and unknown vs married). Health status was measured by the International Classification of Diseases, 10th Revision (ICD-10) diagnosis codes from claims data during the pre-period. We searched the claims for ICD-10 codes in the Chronic Condition Warehouse
      Centers for Mediare and Medicaid Services
      Chronic Conditions Data Warehouse.
      (CCW) and constructed a categorical variable for the number of physical health conditions (3–4, 5–6, and 7 or more vs 0–2) based on the most common conditions in the data [hypertension, arthritis, hyperlipidemia, asthma, chronic obstructive pulmonary disease (COPD), diabetes, chronic kidney disease, heart failure, atrial fibrillation, stroke, Alzheimer’s disease, osteoporosis, cancer]. The number of mental health diagnoses were counted and a variable created with 2 or more (vs 1) mental health diagnoses. Another variable was created to indicate the presence of alcohol or drug use disorders (vs none). We further controlled for whether enrollees had used any primary care or specialty care services during the quarter before the first telepsychiatry visit and which telepsychiatry provider they had visited. When examining PHQ-9 scores, we further controlled for the number of telepsychiatry visits and average number of months observed during the program period.

      Analyses Methods

      Service use

      We developed a random effect Poisson regression model for each dependent variable measuring service use. We used random effects to account for repeated observations for each patient. We standardized the dependent variables by using the number of months observed in each semi-annual period as the exposure variable in the regression models. Using the margins command in Stata 16.1, we estimated the predicted rates of utilization at each time period and compared the semi-annual change in trends between the pre- and post-periods.

      PHQ-9 and GAD-7

      We further developed a similar random effects linear regression model for measuring change in PHQ-9 scores using a slightly different mix of the independent and control variables (see Supplementary Tables 1 and 2). We added an interaction term between time and depression diagnosis at first visit when measuring change in PHQ-9 scores to see whether patterns of change differed for those with depression vs not. We estimated the predicted PHQ-9 score using the margins command and compared the change from the quarter before the first visit to the quarters after that visit. We tested the difference in average GAD-7 scores and severity levels at first visit with the following quarter using t-test and χ2 tests, respectively.

      Results

      The sample characteristics for the utilization and PHQ analyses are displayed in Table 1 and Supplementary Table 3, respectively. Data showed that the telepsychiatry patients were most frequently ages 65 to 74 (50%), female (64%), White (52%), spoke English (82%), and were married (46%). Most had 3 to 4 physical health comorbidities (35%), most had depression (81%), 50% had 2 or more mental health comorbidities, and 38% had alcohol or drug use disorders. During the 2 years before the first telepsychiatry visit, patients had used 24 outpatient services on average including 9 primary care and 9 specialty care services. They also had 0.9 ED visits followed by discharge and 0.4 hospitalizations. Within the sample for PHQ-9 analysis, more patients had moderately severe to severe PHQ-9 scores (43%), with an average score of 13.0. Furthermore, 94% had a primary care and 85% had a specialty care visit in the prior quarter, and 60% saw telepsychiatry provider 1 vs 2 (Supplementary Table 3). The average number of telepsychiatry visits was 6, and patients were observed for 6 months during the intervention period.
      Table 1Characteristics of the Sample of Adults Ages 55 and Older Who Received Telepsychiatry
      Utilization Sample
      Sample size218
      Demographics
       Age, y
      55 to 6425%
      65 to 7450%
      75 and older24%
       Female64%
       Race and ethnicity
      White (reference group)52%
      Hispanic/Latino28%
      Black/African American8%
      Other/Unknown11%
       Preferred language is English (vs other)82%
       Marital status
      Married (reference group)46%
      Not Married34%
      Unknown19%
      Health status before first telepsychiatry visit
       Number of physical health comorbidities
      0 to 222%
      3 or 435%
      5 or 622%
      7 or more21%
       Depression (vs not)81%
       2 or more mental health conditions (vs 0–1)50%
       Alcohol or drug use disorders (vs none)38%
      Average annual utilization during the 2 years before first telepsychiatry visit
       Number of overall outpatient services24
       Number of primary care services9
       Number of specialty care services9
       Number of ED visits0.9
       Number of hospitalizations0.4
       Number of months observed before the intervention20
       Visits Telepsychiatry provider 1 (vs 2)62%
      Notes: Mental health conditions include diagnosis of depression, anxiety, schizophrenia, and bipolar disorders. Physical health comorbidities include hypertension, arthritis, hyperlipidemia, asthma, COPD, diabetes, chronic kidney disease, heart failure, atrial fibrillation, stroke, Alzheimer’s disease, osteoporosis, cancer, autism, and HIV.
      Table 2 displays the findings from the utilization regression models. Data showed that the number of outpatient services declined significantly (−0.24 or from 2.24 to 1.53 services per patient per 6 months) in the 2 years following the first telepsychiatry visit. However, there were no statistically significant changes in these rates before the first telepsychiatry visit (from 2.01 to 2.22). A closer examination of prior primary and specialty care specific sub-categories of outpatient service use showed a similar lack of change for the number of primary and specialty services. Both types of services declined significantly following the first telepsychiatry visit (by −0.11 and −0.13 services, respectively).
      Table 2Changes in Predicted Rates of Service Use From 24 Months Prior to 24 Months After the First Telepsychiatry Visit
      Pre-Period, Before First VisitPost-Period, After First VisitDifference in Patterns of Semi-annual Change
      24–19 mo18–13 mo12–7 mo6–1 moAverage Semi-annual Change0–5 mo6–11 mo12–17 mo18–24 moAverage Semi-annual Change
      Number of outpatient services2.011.891.912.220.072.241.831.731.53−0.24∗∗∗−0.57∗∗∗
      Number of primary care services0.760.720.710.840.030.820.540.600.51−0.11∗∗∗−0.41∗∗∗
      Number of specialty care services0.710.720.770.800.030.900.750.620.53−0.13∗∗∗−0.17∗
      Number of ED visits followed by discharge0.060.060.070.120.02∗∗∗0.080.060.07−0.07∗
      Number of hospitalizations0.030.020.020.040.020.030.020.02−0.03∗
      — indicates sample is too small. Utilization is measured per patient per 6 months.
      Bold values indicate statistically significant.
      P < .05.
      ∗∗∗P < .001.
      Examining the changes in number of ED visits followed by discharge showed a significant increase semi-annually in the 2 years prior (0.02) and subsequent decline (−0.07) during the following 1.5 years. Hospitalizations also declined (−0.03) in the 1.5 years after the first telepsychiatry visit following no change in the prior 2 years. The shorter timeline for these 2 outcomes was because the rates for the last 6 months of the program were unreliable. Further examination of these trends for all 5 outcomes indicated they were significantly different.
      Further analyses of utilization in the shorter-term showed significant declines in total outpatient, primary, and specialty care services from the year before to the year after the first telepsychiatry visit (Supplementary Table 4). The patterns for ED visits were similar to the longer-term analyses. There was a significant increase in number of hospitalizations during the year before the first telepsychiatry visit (0.02), however, which remained unchanged in the year following the first telepsychiatry visit.
      Examining the changes in the PHQ-9 score among patients diagnosed with depression before or on the first telepsychiatry visit showed an increase before the first visit (from 10.0 to 11.8), an increase to 13.8 during and up to 3 months following the first visit, and a significant decline in the third quarter following the first visit (−1.5 from 13.8 to 12.3; Table 3). There were no significant differences in the PHQ-9 score for the population diagnosed with mental health conditions other than depression.
      Table 3Changes in Predicted PHQ-9 Scores From 2 Quarters Before First Telepsychiatry Visit to 3 Quarters After the Visit
      Pre-Period, Before First VisitAverage Quarterly ChangePost-Period, After First VisitAverage Quarterly ChangeDifference in Patterns of Quarterly Change
      2 Quarters1 Quarter1 Quarter After2 Quarters After3 Quarters After
      Depression diagnosis by date of first visit10.011.8−2.113.813.012.3−0.8−1.52
      P < .05.
      No depression diagnosis by date of first visit7.59.3−1.811.08.88.80.1−2.2
      P < .05.
      Our descriptive assessment of GAD-7 scores showed a significant decline in the average score (from 13. 8 to 8.4) as well as a decline in the percentage who had severe (52% to 19%) or moderate anxiety (26% to 22%; Table 4).
      Table 4GAD-7 Average Scores and Severity Levels From First Telepsychiatry Visit to 3 Months After the Visit Among Those With GAD-7 Scores at Both Times
      At or Within 2 wk of First Visit3 mo After the First VisitDifference (P Value)
      Average score13.88.4.000
      Severity level, %
       Minimal (0–4)426.000
       Mild (5–9)1933
       Moderate (10–14)2622
       Severe (15–21)5219
      In addition to these findings, the medical group reported that during the program period, 45% of those referred were not seen. These findings are in line with other research that show that less than 50% of individuals needing mental health services ever receive those services.
      National Institute of Mental Health
      Figure 2. Mental Health Services Received in Past Year Among U.S. Adults with Any Mental Illness (2020). National Institute of Mental Health. Mental Health Information: Statistics Web site.
      Efforts to ensure that patients were seen by telepsychiatry included walking patients to the telepsychiatry clinic to schedule the telepsychiatry appointment on the day they were referred to promote a warm handoff, giving patients a copy of their appointment date and time, and calling patients by phone the day before their appointment as a reminder. Among those seen, the average number of days to appointment was 6 and 5 days, reduced by 69 days for new patients and 25 days for returning patients. In comparison, in-person psychiatrist wait times were 75 days for new patients and 30 days for returning patients. The medical group also reported a decrease in the no-show rate by 56% for new patients and 40% for returning patients.

      Discussion

      Our analyses showed that most patients in the SCAN telepsychiatry program had moderately severe to severe depression. Before receiving their first telepsychiatry visit, patients had increasing rates of outpatient service use, including primary care and specialty care service use. This service use declined following the telepsychiatry visit and reached a level lower than the period before receipt of telepsychiatry. In addition, the analyses showed a similar decline in ED visits and hospitalization. The analyses of average PHQ-9 scores showed improvements 2 quarters after the first telepsychiatry visit for those with a depression diagnosis by the date of their first visit.
      The level of decline in utilization of outpatient services in our findings are consistent with other research that indicate overutilization of such services when patients with mental health disorders are undiagnosed or do not have timely access to needed psychiatric care.
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      It is likely that these patients have more primary care visits to treat previously undiagnosed mild and moderate depression or anxiety or they need more primary and specialty care because they cannot manage their physical health conditions effectively.
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      Our descriptive assessment of patients with conditions such as hypertension, diabetes, and asthma/COPD were consistent with these assertions.
      Our findings of reductions in all-cause ED visits and hospitalization are also consistent with other research. These findings likely indicate that telepsychiatry reduced the need for these services by improving patients’ mental health and consequently improving their ability to manage their physical health conditions. These types of improvements are shown to help patients avoid acute episodes, particularly for ambulatory care–sensitive conditions that depend more heavily on self-management.
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      The statistically significant decline in the average PHQ-9 score indicates the likely impact of telepsychiatry on patients with depression who received this care and is consistent with other research supporting the efficacy of this modality of treatment compared with in-person psychiatry. These findings are also consistent with the findings of lower utilization of outpatient and acute services in this study. The decline may not have occurred among patients with depression and co-occurring anxiety or substance use disorders, or among those who may have treatment-resistant depression.
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      Our data had caveats. The number of enrollees receiving telepsychiatry was small and we could not detect smaller differences in utilization of PHQ-9 scores. This also reduced our ability to conduct more stratified or targeted analyses by age or mental health conditions of enrollees to better assess the program’s impact. Despite considerable effort by the medical group, PHQ-9 score measurement frequency was irregular. We did not have access to socioeconomic data, such as income, which may have played a role in decisions to use services or hamper the improvement in mental and physical health of enrollees. Despite our best efforts, we were not able to construct a reliable control group because of sparse PHQ-9 scores and self-selection of enrollees into in-person or telepsychiatry. We also could not assess concurrent use of behavioral health therapy provided by non-psychiatrists due to sparseness of such data. We lacked adequate data to measure changes in GAD-7 before the first telepsychiatry visit. Our data may not be generalizable to other health plans or enrollees in other geographic areas. Nevertheless, our data provide extensive information on the likely impact of a telepsychiatry program designed to improve access to psychiatric care to aging adults and are instructive for other health plans, as well as health systems, attempting to address similar problems.

      Conclusions and Implications

      Our findings have implications for provision of telepsychiatry as an alternative modality of providing psychiatric care, particularly best practices in promoting behavioral health integration and access to care highlighted by the specific approach used by the SCAN telepsychiatry program. The virtual integration of psychiatrists within the primary care setting and workflows, who had access to patient medical records, were available for consultation, and communicated directly with PCPs is in accordance with current efforts in integrated and collaborative behavioral and primary health care.
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      An update on telepsychiatry and how it can leverage collaborative, stepped, and integrated services to primary care.
      In addition, availability of bilingual psychiatrists can help address language barriers in areas with a shortage of such providers. Integrated telepsychiatry services can also help to address other barriers to care, such as reducing stigma associated with seeking psychiatric treatment at specialty settings, reducing the need for longer travel, and excessive wait times for first and follow-up visits.
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      • et al.
      Patient satisfaction with geriatric psychiatry services via video teleconference.
      More research is needed to confirm the findings of this study and to test this approach in other areas and with different populations. Specifically, more research is needed to assess the impact of this approach for older patients who present with different mental health and physical conditions, and cognitive and functional status. More research is also need to better understand the perceptions of stigma associated with seeking mental health care, and the reasons why older adults with a behavioral health referral from their PCP do not follow through with the referral and use these services.

      Acknowledgments

      The authors thank Yupeng Chen for assistance in data analyses; and Stephanie Neely and Tawnya Smead for extracting claims and medical record data. The authors acknowledge Dr. Steven Wallace, who was the principal investigator of this evaluation and passed before the analyses in this manuscript started.

      Supplementary Data

      Figure thumbnail fx1
      Supplementary Fig. 1Sample size and inclusion criteria.
      Supplementary Table 1Service Utilization Poisson Regression Results
      Number of Outpatient ServicesNumber of Primary Care ServicesNumber of Specialty Care ServicesNumber of ED Visits Followed by DischargeNumber of Hospitalizations
      Estimate/SEEstimate/SEEstimate/SEEstimate/SEEstimate/SE
      Time (Ref = 24–19 mo prior)
       18–13 mo prior−0.063 (0.056)−0.053 (0.068)0.01 (0.082)−0.062 (0.242)−0.303 (0.322)
       12–7 mo prior−0.054 (0.056)−0.056 (0.067)0.086 (0.079)0.137 (0.232)−0.375 (0.327)
       6–1 mo prior0.1 (0.053)0.107 (0.063)0.117 (0.078)0.691
      P < .001.
      (0.206)
      0.372 (0.277)
       0–5 mo after0.11
      P < .05.
      (0.053)
      0.083 (0.063)0.238
      P < .01.
      (0.076)
      0.344 (0.22)0.073 (0.292)
       6–11 mo after−0.097 (0.058)−0.343
      P < .001.
      (0.073)
      0.057 (0.082)−0.018 (0.247)−0.178 (0.316)
       12–17 mo after−0.15
      P < .05.
      (0.066)
      −0.239
      P < .01.
      (0.081)
      −0.13 (0.096)0.158 (0.263)−0.196 (0.36)
       18–24 mo after−0.274
      P < .01.
      (0.095)
      −0.385
      P < .01.
      (0.117)
      −0.301
      P < .05.
      (0.138)
      −0.047 (0.385)−0.1 (0.494)
      Age (Ref = 55–64)
       65–740.015 (0.086)0 (0.09)−0.107 (0.125)−0.351 (0.228)−0.264 (0.274)
       75+0.063 (0.109)0.034 (0.113)0 (0.157)0.125 (0.27)0.451 (0.311)
      Gender
       Female0.314
      P < .001.
      (0.076)
      0.182
      P < .05.
      (0.081)
      0.373
      P < .001.
      (0.112)
      −0.017 (0.201)−0.461
      P < .05.
      (0.232)
      Race (Ref = White)
       African American−0.04 (0.105)0.074 (0.109)−0.025 (0.151)0.5 (0.309)0.263 (0.335)
       Latino−0.128 (0.112)−0.12 (0.118)−0.325 (0.167)−0.108 (0.286)−0.167 (0.36)
       Other/Unknown0
      P < .001.
      (0)
      0
      P < .001.
      (0)
      0
      P < .001.
      (0)
      −0.267 (0.312)0
      P < .001.
      (0)
      Marital Status (Ref = Married)
       Not Married−0.007 (0.074)0.014 (0.079)−0.13 (0.109)0.351 (0.196)0.376 (0.23)
       Unknown0.057 (0.094)0.07 (0.099)0.013 (0.138)0.31 (0.254)0.14 (0.321)
      Language (Ref = English)
       Non-English−0.002 (0.127)−0.03 (0.131)−0.145 (0.182)0.119 (0.341)−0.24 (0.401)
      Number of physical health comorbidities (Ref = "0–2")
       3 or 40.338
      P < .001.
      (0.095)
      0.265
      P < .01.
      (0.1)
      0.335
      P < .05.
      (0.138)
      0.444 (0.279)0.437 (0.407)
       5 or 60.533
      P < .001.
      (0.111)
      0.375
      P < .01.
      (0.115)
      0.64
      P < .001.
      (0.16)
      0.483 (0.312)0.799 (0.426)
       7 or more0.902
      P < .001.
      (0.113)
      0.64
      P < .001.
      (0.118)
      0.938
      P < .001.
      (0.165)
      1.506
      P < .001.
      (0.304)
      1.818
      P < .001.
      (0.402)
      Depression (Ref = None)
       Yes−0.114 (0.092)−0.082 (0.095)−0.115 (0.13)0.067 (0.243)−0.096 (0.289)
      Other mental health conditions (Ref = "0–1")
       2 or more0.084 (0.072)0.107 (0.075)−0.034 (0.104)0.205 (0.188)0.36 (0.231)
      Alcohol or drug use disorders (Ref = none)
       Yes0.18
      P < .05.
      (0.073)
      0.037 (0.075)0.213
      P < .05.
      (0.106)
      −0.123 (0.186)−0.165 (0.225)
      Provider indicator (Ref = First)
       Second−0.002 (0.074)−0.063 (0.077)−0.041 (0.108)−0.086 (0.191)0 (0.23)
      Intercept−0.797
      P < .001.
      (0.152)
      −0.285 (0.187)−1.166
      P < .001.
      (0.216)
      −3.33
      P < .001.
      (0.437)
      −3.752
      P < .001.
      (0.606)
      Random effect parameters
       log(r)1.984
      P < .001.
      (0.122)
      2.749
      P < .001.
      (0.147)
      1.523
      P < .001.
      (0.124)
      1.383
      P < .001.
      (0.196)
      2.302
      P < .001.
      (0.416)
       log(s)2.582
      P < .001.
      (0.139)
      2.188
      P < .001.
      (0.151)
      1.484
      P < .001.
      (0.138)
      0.642
      P < .001.
      (0.237)
      1.355
      P < .001.
      (0.527)
      P < .05.
      ∗∗ P < .01.
      ∗∗∗ P < .001.
      Supplementary Table 2PHQ-9 Score Ordinary Least Square Regression Results
      Estimate/SE
      Depression diagnosis at initial Telepsych visit (Ref = No)
       Yes2.493 (1.792)
      Time (Ref = 180 to 90 days prior)
       90 days to 7 days after the first visit (time2)1.752 (1.988)
       8 to 97 days after the first visit (time3)3.444
      P < .05.
      (1.564)
       98 to 187 days after the first visit (time4)1.216 (1.931)
       188 to 278 days after the first visit (time5)1.253 (1.78)
      Interaction of depression status with time
       Depression by time2−0.04 (2.344)
       Depression by time30.286 (1.81)
       Depression by time41.727 (2.213)
       Depression by time50.96 (2.049)
      Age (Ref = 55–64)
       65–74−2.911
      P < .01.
      (0.873)
       75+−2.539
      P < .05.
      (1.152)
      Gender
       Female0.262 (0.862)
      Race (Ref = White)
       African American0.74 (1.569)
       Latino−0.732 (1.263)
       Other/Unknown1.974 (1.192)
      Marital Status (Ref = Married)
       Not Married/Unknown0.272 (0.781)
      Language (Ref = English)
       Non-English2.077 (1.368)
      Number of physical health comorbidities (Ref = "0–2")
       3 or 4−0.268 (1.019)
       5 or 6−0.058 (1.163)
       7 or more1.99 (1.241)
      Other mental health conditions (Ref = "0–1")
       2 or more−0.342 (0.801)
      Alcohol or drug use disorders (Ref = none)
       Yes0.528 (0.792)
      Provider indicator (Ref = First)
       Second1.422 (0.901)
      Number of treatment visits0.093 (0.104)
      Duration observed in the program (Ref = more than a year)
       Less than a year1.285 (1.301)
      Had a PCP visit in previous quarter (Ref = No)
       Yes0.515 (0.773)
      Had a specialty visit in previous quarter (Ref = No)
       Yes−0.352 (0.699)
      Intercept6.1
      P < .05.
      (2.626)
      Random Effect Parameters
       Between variance3.949
      P < .001.
      (0)
       Within variance4.357
      P < .001.
      (0)
       Intra-class correlation0.4510
      P < .05.
      ∗∗ P < .01.
      ∗∗∗ P < .001.
      Supplementary Table 3Characteristics of the Sample of Adults Ages 55 and Older Who Received Telepsychiatry and Had a PHQ-9 Score
      PHQ-9 Sample
      Sample size204
      Demographics
       Age, y
      55 to 6429%
      65 to 7448%
      75 and older23%
       Female68%
       Race and ethnicity
      White (reference group)52%
      Hispanic/Latino27%
      Black/African American7%
      Other/Unknown14%
       Preferred language is English (vs other)79%
       Marital status
      Married (reference group)41%
      Not married37%
      Unknown22%
      Health status prior to first telepsychiatry visit
       Number of physical health comorbidities
      0 to 222%
      3 or 434%
      5 or 623%
      7 or more21%
       Depression (vs not)92%
       2 or more mental health conditions (vs 1)56%
       Alcohol or drug use disorders (vs none)46%
       Average PHQ score at first visit13.0
       PHQ-9 severity level at first visit
      0 to 9 (no depression or mild)32%
      10 to 14 (moderate)26%
      15 to 27 (moderately severe or severe)43%
       Having PCP visit during prior quarter94%
       Having specialty visit during prior quarter85%
       Visits telepsychiatry provider 1 (vs 2)60%
       Average number of telepsychiatry visits6
       Average number of months of intervention observed6
      Average annual utilization during the 2 years before first Telepsych visit
       Number of overall outpatient services24
       Number of primary care services9
       Number of specialty care services9
       Number of ED visits0.9
       Number of hospitalizations0.4
       Number of months observed before the intervention20
      Notes: Mental health conditions include diagnosis of depression, anxiety, schizophrenia, and bipolar disorders. Physical health comorbidities include hypertension, arthritis, hyperlipidemia, asthma, COPD, diabetes, chronic kidney disease, heart failure, atrial fibrillation, stroke, Alzheimer’s disease, osteoporosis, cancer, autism, HIV.
      Supplementary Table 4Changes in Predicted Rates of Service Utilization From 12 Months Prior to 12 Months After the First Telepsychiatry Visit
      Pre-Period, Before First VisitPost-Period, After First VisitDifference in Patterns of Semi-Annual Change
      12–7 mo6–1 moAverage Semi-annual Change0–5 mo6–11 moAverage Semi-annual Change
      Number of outpatient services1.912.220.32
      P < .01.
      2.241.83−0.42
      P < .001.
      −0.73
      P < .001.
      Number of primary care services0.710.840.13
      P < .01.
      0.820.54−0.29
      P < .001.
      −0.24
      P < .001.
      Number of specialty care services0.770.800.020.900.75−0.15
      P < .05.
      −0.16
      P < .05.
      Number of ED visits followed by discharge0.070.120.05
      P < .01.
      0.080.06−0.01−0.06
      P < .01.
      Number of hospitalizations0.020.040.02
      P < .05.
      0.030.02−0.01−0.03
      P < .05.
      Bold values indicate statistically significant.
      Notes: Utilization is measured per patient per 6 months.
      P < .05.
      ∗∗ P < .01.
      ∗∗∗ P < .001.

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