In many mental health and some somatic disorders, efficacy of therapist-guided remote CBT and in-person CBT does not differ.

SOURCE CITATION: Zandieh S, Abdollahzadeh SM, Sadeghirad B, et al. Therapist-guided remote versus in-person cognitive behavioural therapy: a systematic review and meta-analysis of randomized controlled trials. CMAJ. 2024;196:E327-E340. 38499303.

Characteristics of Veterans Experiencing Homelessness using Telehealth for Primary Care Before and After COVID-19 Pandemic Onset.

BACKGROUND: The COVID-19 pandemic expanded telehealth use across healthcare systems, including the Veterans Health Administration (VA). Little is known about how large-scale telehealth rollout affected access to primary care for patients experiencing homelessness. OBJECTIVE: To examine the extent to which homeless-experienced veterans used telehealth services in primary care and to characterize users before and after the onset of the COVID-19 pandemic. DESIGN: Retrospective cohort study, 3/16/2019-3/15/2022. PARTICIPANTS: 394,731 veterans with homelessness diagnoses nationally using 4,068,109 primary care visits. MAIN MEASURES: The outcomes were use of 1 + telehealth visits (video, phone, secure messaging) for primary care during each year. Through multivariable regression models, we examined associations between telehealth use, patient characteristics (e.g., age, sex, race-ethnicity, comorbidity), and VA homeless services use (e.g., homeless-tailored primary care (HPACT), permanent supportive housing). KEY RESULTS: Compared to pre-pandemic, telehealth in primary care among homeless-experienced veterans increased substantially 2 years post-pandemic (video: 1.37% versus 20.56%, phone: 60.74% versus 76.58%). Secure messaging was low over time (1.57-2.63%). In adjusted models, video users were more likely to be young (65 + years: OR = 0.43, CI: 0.42-0.44), women (OR = 1.74, CI: 1.70-1.78), Black (OR = 1.14, CI: 1.12-1.16), Hispanic (OR = 1.34, CI: 1.30-1.38), and with more comorbidities (2 + on the Charlson Comorbidity Index; OR = 1.16, CI: 1.14-1.19), compared to video non-users. HPACT patients were less likely to use video (OR = 0.68, CI: 0.66-0.71) than other primary care patients. This was not observed among users of other VA homeless services. CONCLUSIONS: Despite decreased access to health information technology and low pre-pandemic telehealth use, veterans experiencing homelessness still sustained high use of telehealth in primary care post-pandemic. Women and racial-ethnic minorities had higher video uptake proportionately, suggesting that telehealth may address access disparities among these homeless-experienced patient groups. Identifying and targeting organizational characteristics (e.g., HPACT users) that predict telehealth use for improvement may be key to increasing adoption among VA primary care patients experiencing homelessness.

Disparities in Video-Based Primary Care Use Among Veterans with Cardiovascular Disease.

BACKGROUND: Cardiovascular disease (CVD) is prevalent among Veterans, and video care enhances access to CVD care. However, it is unknown which patients with CVD conditions receive video care in primary care clinics, where a large proportion of CVD services is delivered. OBJECTIVE: Characterize use of VA video primary care for Veterans with two common CVDs, heart failure and hypertension. DESIGN: Retrospective cohort study. PATIENTS: Veterans seen in VA primary care with diagnoses of heart failure and/or hypertension in the year prior to the COVID-19 pandemic and for the first two pandemic-years. MAIN MEASURES: The primary outcome was use of any video-based primary care visits. Using multilevel regressions, we examined the association between video care use and patient sociodemographic and clinical characteristics, controlling for time and adjusting for patient- and site-level clustering. KEY RESULTS: Of 3.8M Veterans with 51.9M primary care visits, 456,901 Veterans had heart failure and hypertension, 50,753 had heart failure only, and 3,300,166 had hypertension only. Veterans with heart failure and hypertension had an average age of 71.6 years. 2.9% were female, and 34.8% lived in rural settings. Patients who were male, aged 75 or older, or rural-dwelling had lower odds of using video care than female patients, 18-44-year-olds, and urban-dwellers, respectively (male patients' adjusted odds ratio [AOR] 0.73, 95% confidence interval [CI] 0.72-0.74; 75 years or older, AOR 0.38, 95% CI 0.37-0.38; rural-dwellers, AOR 0.71, 95% CI 0.70-0.71). Veterans with heart failure had higher odds of video care use than those with hypertension only (AOR 1.05, 95% CI 1.04-1.06). CONCLUSIONS: Given lower odds of video primary care use among some patient groups, continued expansion of video care could make CVD services increasingly inequitable. These insights can inform equitable triage of patients, for example by identifying patients who may benefit from additional support to use virtual care.

Understanding How Contingency Staffing Programs Can Support Mental Health Services in the Veterans Health Administration.

Introduction: Beginning in 2019, the Department of Veterans Affairs (VA) prioritized improving access to care nationally to deliver virtual care and implemented 18 regionally based Clinical Resource Hubs (CRHs) to meet this priority. This observational study describes the quantity and types of care delivered by CRH Mental Health teams, and the professions of those hired to deliver it. Methods: A retrospective cohort study, based on national VA CRH mental health care utilization data and CRH staffing data for CRH's first 3 years, was conducted. Results: CRH Mental Health teams primarily used Telemental Health (TMH) to provide care (98.1% of all CRH MH encounters). The most common disorders treated included depression, post-traumatic stress disorder, and anxiety disorders. The amount of care delivered overtime steadily increased as did the racial and ethnic diversity of Veterans served. Psychologists accounted for the largest share of CRH staffing, followed by psychiatrists. Conclusions: CRH TMH delivered from a regional hub appears to be a feasible and acceptable visit modality, based on the continuously increasing CRH TMH visit rates. Our results showed that CRH TMH was predominantly used to address common mental health diagnoses, rather than serious mental illnesses. Traditionally marginalized patient populations increased over the 3-year window, suggesting that CRH TMH resources were accessible to many of these patients. Future research should assess barriers and facilitators for accessing CRH TMH, especially for difficult-to-service patient populations, and should consider whether similar results to ours occur when regional TMH is delivered to non-VA patient populations.

Associations Between Primary Care Providers and Staff-Reported Access Management Challenges and Patient Perceptions of Access.

BACKGROUND/OBJECTIVE: Optimizing patients' access to primary care is critically important but challenging. In a national survey, we asked primary care providers and staff to rate specific care processes as access management challenges and assessed whether clinics with more of these challenges had worse access outcomes. METHODS: Study design: Cross sectional. National Primary Care Personnel Survey (NPCPS) (2018) participants included 6210 primary care providers (PCPs) and staff in 813 clinics (19% response rate) and 158,645 of their patients. We linked PCP and staff ratings of access management challenges to veterans' perceived access from 2018-2019 Survey of Healthcare Experiences of Patients-Patient Centered Medical Home (SHEP-PCMH) surveys (35.6% response rate). MAIN MEASURES: The NPCPS queried PCPs and staff about access management challenges. The mean overall access challenge score was 28.6, SD 6.0. The SHEP-PCMH access composite asked how often veterans reported always obtaining urgent appointments same/next day; routine appointments when desired and having medical questions answered during office hours. ANALYTIC APPROACH: We aggregated PCP and staff responses to clinic level, and use multi-level, multivariate logistic regressions to assess associations between clinic-level access management challenges and patient perceptions of access. We controlled for veteran-, facility-, and area-level characteristics. KEY RESULTS: Veterans at clinics with more access management challenges (> 75th percentile) had a lower likelihood of reporting always receiving timely urgent care appointments (AOR: .86, 95% CI: .78-.95); always receiving routine appointments (AOR: .74, 95% CI: .67-.82); and always reporting same- or next-day answers to telephone questions (AOR: .79, 95% CI: .70-.90) compared to veterans receiving care at clinics with fewer (< 25th percentile) challenges. DISCUSSION/CONCLUSION: Findings show a strong relationship between higher levels of access management challenges and worse patient perceptions of access. Addressing access management challenges, particularly those associated with call center communication, may be an actionable path for improved patient experience.

Quality of Depression Care for Veterans Affairs Primary Care Patients with Experiences of Homelessness.

BACKGROUND: Persons who experience homelessness (PEH) have high rates of depression and incur challenges accessing high-quality health care. Some Veterans Affairs (VA) facilities offer homeless-tailored primary care clinics, although such tailoring is not required, within or outside VA. Whether services tailoring enhances care for depression is unstudied. OBJECTIVE: To determine whether PEH in homeless-tailored primary care settings receive higher quality of depression care, compared to PEH in usual VA primary care. DESIGN: Retrospective cohort study of depression treatment among a regional cohort of VA primary care patients (2016-2019). PARTICIPANTS: PEH diagnosed or treated for a depressive disorder. MAIN MEASURES: The quality measures were timely follow-up care (3 + completed visits with a primary care or mental health specialist provider, or 3 + psychotherapy sessions) within 84 days of a positive PHQ-2 screen result, timely follow-up care within 180 days, and minimally appropriate treatment (4 + mental health visits, 3 + psychotherapy visits, 60 + days antidepressant) within 365 days. We applied multivariable mixed-effect logistic regressions to model differences in care quality for PEH in homeless-tailored versus usual primary care settings. KEY RESULTS: Thirteen percent of PEH with depressive disorders received homeless-tailored primary care (n = 374), compared to usual VA primary care (n = 2469). Tailored clinics served more PEH who were Black, who were non-married, and who had low income, serious mental illness, and substance use disorders. Among all PEH, 48% received timely follow-up care within 84 days of depression screening, 67% within 180 days, and 83% received minimally appropriate treatment. Quality metric attainment was higher for PEH in homeless-tailored clinics, compared to PEH in usual VA primary care: follow-up within 84 days (63% versus 46%; adjusted odds ratio [AOR] = 1.61, p = .001), follow-up within 180 days (78% versus 66%; AOR = 1.51, p = .003), and minimally appropriate treatment (89% versus 82%; AOR = 1.58, p = .004). CONCLUSIONS: Homeless-tailored primary care approaches may improve depression care for PEH.

Development of a model to predict psychotherapy response for depression among Veterans.

BACKGROUND: Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. METHODS: This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018-2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. RESULTS: 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. CONCLUSIONS: Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

Development of a model to predict antidepressant treatment response for depression among Veterans.

BACKGROUND: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. RESULTS: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. CONCLUSIONS: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Association of Team-Based Care and Continuity of Care with Hospitalizations for Veterans with Comorbid Mental and Physical Health Conditions.

BACKGROUND: Integrating mental health in primary care settings is associated with improved screening and detection of mental illness. In 2010, the Veterans Health Administration launched a patient-centered medical home (PCMH) model nationally across all clinical sites that integrated mental health into primary care-the Patient Aligned Care Team (PACT) initiative. Team-based delivery of continuous primary and mental health care, as found in effective collaborative care models, is thought to be crucial to managing veterans with mental health disorders. The association between clinic implementation of specific aspects of PACT and clinical outcomes of veterans with mental health disorders remains unknown. OBJECTIVE: To examine the association between clinic implementation of team-based care and continuity of care and subsequent hospitalizations among veterans with mental health disorders. DESIGN: Retrospective cohort study. PATIENTS: A total of 1,444,942 veterans with comorbid mental health disorders and physical health conditions receiving primary care in 831 VA PACT clinics in fiscal year (FY) 2015. MAIN MEASURES: We examined the clinic-level implementation of team-based care and continuity of care in the clinic where veterans received their primary care. Our primary outcome was any hospitalization in the VA or fee-based service in FY2016. We examined the impact of clinic-level implementation of team-based care and continuity of care on having a hospitalization, adjusting for patient demographic, clinical characteristics, and facility characteristics. KEY RESULTS: Veterans receiving care in clinics with the greatest versus lowest quartile of implementation of team-based care had lower rates of hospitalization (8.8% vs. 12.3%; adjusted OR = 0.92, 95% CI 0.85-0.99, p < 0.035). There was not a statistically significant association between clinic-level implementation of continuity of care and hospitalization. CONCLUSIONS: Veterans receiving care in clinics with greater implementation of team-based care had statistically significant lower rates of hospitalization.

Association of Integrated Mental Health Services with Physical Health Quality Among VA Primary Care Patients.

BACKGROUND: Integrated care for comorbid depression and chronic medical disease improved physical and mental health outcomes in randomized controlled trials. The Veterans Health Administration (VA) implemented Primary Care-Mental Health Integration (PC-MHI) across all primary care clinics nationally to increase access to mental/behavioral health treatment, alongside physical health management. OBJECTIVE: To examine whether widespread, pragmatic PC-MHI implementation was associated with improved care quality for chronic medical diseases. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included 828,050 primary care patients with at least one quality metric among 396 VA clinics providing PC-MHI services between October 2013 and September 2016. MAIN MEASURE(S): For outcome measures, chart abstractors rated whether diabetes and cardiovascular quality metrics were met for patients at each clinic as part of VA's established quality reporting program. The explanatory variable was the proportion of primary care patients seen by integrated mental health specialists in each clinic annually. Multilevel logistic regression models examined associations between clinic PC-MHI proportion and patient-level quality metrics, adjusting for regional, patient, and time-level effects and clinic and patient characteristics. KEY RESULTS: Median proportion of patients seen in PC-MHI per clinic was 6.4% (IQR=4.7-8.7%). Nineteen percent of patients with diabetes had poor glycemic control (hemoglobin A1c >9%). Five percent had severely elevated blood pressure (>160/100 mmHg). Each two-fold increase in clinic PC-MHI proportion was associated with 2% lower adjusted odds of poor glycemic control (95% CI=0.96-0.99; p=0.046) in diabetes. While there was no association with quality for patients diagnosed with hypertension, patients without diagnosed hypertension had 5% (CI=0.92-0.99; p=0.046) lower adjusted odds of having elevated blood pressures. CONCLUSIONS AND RELEVANCE: Primary care clinics where integrated mental health care reached a greater proportion of patients achieved modest albeit statistically significant gains in key chronic care quality metrics, providing optimism about the expected effects of large-scale PC-MHI implementation on physical health.

Are Veterans Getting Their Preferred Depression Treatment? A National Observational Study in the Veterans Health Administration.

BACKGROUND: Physician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes. OBJECTIVE: To examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment. DESIGN: Patient self-report surveys at treatment initiation linked to medical records. SETTING: Veterans Health Administration (VA) clinics nationally, 2018-2020. PARTICIPANTS: A total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) MAIN MEASURES: Patient self-reported preferences for medication and psychotherapy on 0-10 self-anchoring visual analog scales (0="completely unwilling"; 10="completely willing"). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables. KEY RESULTS: More patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p<0.001). A total of 32.1% of patients who preferred (7-10/10) medication and 21.8% who preferred psychotherapy did not receive these treatments. Patients who strongly preferred medication were substantially more likely to receive medication than those who had strong negative preferences (odds ratios [OR]=17.5; 95% confidence interval [CI]=12.5-24.5). Compared with patients who had strong negative psychotherapy preferences, those with strong psychotherapy preferences were about twice as likely to receive psychotherapy (OR=1.9; 95% CI=1.0-3.5). Patients who strongly preferred psychotherapy were more likely to adhere to psychotherapy than those with strong negative preferences (OR=3.3; 95% CI=1.4-7.4). Treatment preferences were not associated with medication or combined treatment adherence. Patients in primary care settings had lower odds of receiving (but not adhering to) psychotherapy than patients in specialty mental health settings. Depression severity was not associated with treatment receipt or adherence. CONCLUSIONS: Mismatches between treatment preferences and treatment type received were common and associated with worse treatment adherence for psychotherapy. Future research could examine ways to decrease mismatch between patient preferences and treatments received and potential effects on patient outcomes.

Integrating Mental Health in Safety-net Primary Care: A Five-year Observational Study on Visits in a County Health System.

BACKGROUND: Beginning in 2010, Los Angeles County Departments of Health Services and Mental Health collaborated to increase access to effective mental health care. The Mental Health Integration Program (MHIP) embedded behavioral health specialists in primary care clinics to deliver brief, problem-focused treatments, and psychiatric consultation support for primary care-prescribed psychotropic medications. OBJECTIVE: The aim was to compare primary care visits associated with psychiatric diagnoses before and after MHIP implementation. METHODS: This retrospective cohort study (2009-2014) examined 62,945 patients from 8 safety-net clinics that implemented MHIP in a staggered manner in Los Angeles. Patients' primary care visits (n=695,354) were either associated or not with a previously identified or "new" (defined as having no diagnosis within the prior year) psychiatric diagnosis. Multilevel regression models used MHIP implementation to predict odds of visits being associated with psychiatric diagnoses, controlling for time, clinic, and patient characteristics. RESULTS: 9.4% of visits were associated with psychiatric diagnoses (6.4% depression, 3.1% anxiety, <1% alcohol, and substance use disorders). Odds of visits being associated with psychiatric diagnoses were 9% higher [95% confidence interval (CI)=1.05-1.13; P<0.0001], and 10% higher for diagnoses that were new (CI=1.04-1.16; P=0.002), after MHIP implementation than before. This appeared to be fueled by increased visits for depression post-MHIP (odds ratio=1.11; CI=1.06-1.15; P<0.0001). CONCLUSIONS: MHIP implementation was associated with more psychiatric diagnoses coded in safety-net primary care visits. Scaling up this effort will require greater attention to the notable differences across patient populations and languages, as well as the markedly low coding of alcohol and substance use services in primary care.

Use of the Veterans' Choice Program and Attrition From Veterans Health Administration Primary Care.

BACKGROUND: Concerns over timely access and waiting times for appointments in the Veterans Health Administration (VHA) spurred the push towards greater privatization. In 2014, VHA increased the provision of care from community providers through the Veterans' Choice Program (Choice). OBJECTIVES: We examined the characteristics of patients and practices more likely to use Choice care and whether using Choice care affected patients' attrition from VHA primary care. STUDY DESIGN: We conducted a longitudinal study of VHA primary care users in the fiscal year 2015 and their attrition 2 years later. In the multivariate analysis, we examined whether attrition from VHA primary care was related to prior use of Choice care. SUBJECTS: A total of 1.4 million nonelderly patients diagnosed with chronic conditions. MEASURES: Choice outpatient care utilization was measured in the baseline year. Attrition was measured as not receiving any VHA primary care in 2 subsequent years. RESULTS: In our cohort, 93,710 (7%) patients used some Choice outpatient care, and these patients were more likely to be female, White or Hispanic, to have more primary care utilization at baseline, and to have long driving distances to VHA care. Practices which sent more patients out for Choice care had lower mean scores for patient-centered medical home implementation and longer mean waiting times for appointments. In the adjusted analysis, the probability of attrition was significantly lower (-0.009) among patients who used Choice outpatient care (0.036) versus patients who did not (0.044) (P<0.001). CONCLUSION: The use of community outpatient providers in the Choice program was associated with less attrition from VHA primary care.

Surviving and Thriving as Physicians in General Internal Medicine Fellowship in the Twenty-First Century.

General internal medicine (GIM) fellowships play an important role in the development of physician scientists and clinical educators, as well as leaders in academic medicine. Nevertheless, the challenges of developing another novel aspect to one's career, along with balancing coursework, research productivity, clinical duties, and personal life during fellowship, can be overwhelming. Similarly, successfully securing a job at the end of fellowship can be a daunting process. In this article, we discuss the foundational tenets and themes of the GIM fellowship. These themes include (1) finding your purpose and passion, with a focus on selecting research coursework and developing an area of study; (2) the role and importance of mentorship, including the various kinds of mentorship that fellows require (traditional and peer mentorship, sponsors, and coaches), as well as how to be an effective mentee; (3) securing research funding; (4) landing a job; (5) and protecting time to meet personal goals. There is an increased need for a vibrant, diverse, and successful generation of general internal medicine researchers to advance our understanding of complex issues in clinical medicine and healthcare delivery and to inform health policy. It is our hope that this piece helps to support that mission.

Does Mental Health Care Integration Affect Primary Care Clinician Burnout? Results from a Longitudinal Veterans Affairs Survey.

BACKGROUND: Burnout among primary care clinicians (PCPs) is associated with negative health and productivity consequences. The Veterans Health Administration (VA) embedded mental health specialists and care managers in primary care to manage common psychiatric diseases. While challenging to implement, mental health integration is a team-based care model thought to improve clinician well-being. OBJECTIVE: To examine the relationships between PCP-reported burnout (and secondarily, job satisfaction) and mental health integration at provider and clinic levels DESIGN: Analysis of 286 cross-sectional surveys in 2012 (n = 171) and 2013 (n = 115) PARTICIPANTS: 210 PCPs in one VA region MAIN MEASURES: Outcomes were PCP-reported burnout (Maslach Burnout Inventory emotional exhaustion subscale), and secondarily, job satisfaction. Two independent variables represented mental health integration: (1) PCP-specialty communication rating and (2) proportion of clinic patients who saw integrated specialists. Using multilevel regression models, we examined PCP-reported burnout (and job satisfaction) and mental health integration, adjusting for PCP characteristics (e.g., gender), PCP ratings of team functioning (communication, knowledge/skills, satisfaction), and organizational factors. KEY RESULTS: On average, PCPs reported high burnout (29, range = 9-54) across all VA healthcare systems. In total, 46% of PCPs reported "very easy" communication with mental health; 9% of primary clinic patients had seen integrated specialists. Burnout was not significantly associated with mental health communication ratings (ß coefficient = - 0.96, standard error [SE] = 1.29, p = 0.46), nor with proportion of clinic patients who saw integrated specialists (ß = 0.02, SE = 0.11, p = 0.88). No associations were observed with job satisfaction either. Among study participants, PCPs with poor team functioning, as exhibited by low team communication ratings, reported high burnout (ß = - 1.28, SE = 0.22, p < 0.001) and low job satisfaction (ß = 0.12, SE = 0.02, p < 0.001). CONCLUSIONS: As currently implemented, primary care and mental health integration did not appear to impact PCP-reported burnout, nor job satisfaction. More research is needed to explore care model variation among clinics in order to optimize implementation to enhance PCP well-being.

Do Collaborative Care Managers and Technology Enhance Primary Care Satisfaction with Care from Embedded Mental Health Providers?

BACKGROUND: To improve mental health care access, the Veterans Health Administration (VA) implemented Primary Care-Mental Health Integration (PC-MHI) in clinics nationally. Primary care clinical leader satisfaction can inform model implementation and may be facilitated by collaborative care managers and technology supporting cross-specialty collaboration. OBJECTIVE: (1) To determine primary care clinical leaders' overall satisfaction with care from embedded mental health providers for a range of conditions and (2) to examine the association between overall satisfaction and two program features (care managers, technology). DESIGN: Cross-sectional organizational survey in one VA region (Southern California, Arizona, and New Mexico), 2018. PARTICIPANTS: Sixty-nine physicians or other designated clinical leaders in each VA primary care clinic (94% response rate). MAIN MEASURES: We assessed primary care clinical leader satisfaction with embedded mental health care on four groups of conditions: target, non-target mental health, behavioral health, suicide risk management. They additionally responded about the availability of mental health care managers and the sufficiency of information technology (telemental health, e-consult, instant messaging). We examined relationships between satisfaction and the two program features using χ2 tests and multivariable regressions. KEY RESULTS: Most primary care clinical leaders were "very satisfied" with care for targeted anxiety (71%) and depression (69%), but not for other common conditions (37% alcohol misuse, 19% pain). Care manager availability was significantly associated with "very satisfied" responses for depression (p = .02) and anxiety care by embedded mental health providers (p = .02). Highly rated sufficiency of communication technology (only 19%) was associated with "very satisfied" responses to suicide risk management (p = .002). CONCLUSIONS: Care from embedded mental health providers for depression and anxiety was highly satisfactory, which may guide improvement among less satisfactory conditions (alcohol misuse, pain). Observed associations between overall satisfaction and collaborative care features may inform clinics on how to optimize staffing and technology based on priority conditions.

High Quality of Care Persists With Shifting Depression Services From VA Specialty to Integrated Primary Care.

BACKGROUND/OBJECTIVE: Offering depression collaborative care services in primary care (PC) settings can reduce use of nonintegrated mental health care resources and improve mental health care access, particularly for vulnerable PC patients. Tests of effects on depression care quality, however, are needed. We examined overall quality of depression care and tested whether increasing clinic engagement in Veterans Affairs (VA)'s Primary Care-Mental Health Integration (PC-MHI) services was associated with differences in depression care quality over time. METHODS: We conducted a retrospective longitudinal cohort study of 80,136 Veterans seen in 26 Southern California VA PC clinics (October 1, 2008-September 30, 2013). Using multilevel regression models adjusting for year, clinic, and patient characteristics, we predicted effects of clinic PC-MHI engagement (ie, percent of PC patients receiving PC-MHI services) on 3 VA-developed longitudinal electronic population-based depression quality measures among Veterans newly diagnosed with depression (n=12,533). RESULTS: Clinic PC-MHI engagement rates were not associated with significant depression care quality differences. Across all clinics, average rates of follow-up within 84 or 180 days were, 66.4% and 74.5%, respectively. Receipt of minimally appropriate treatment was 80.5%. Treatment probabilities were significantly higher for vulnerable PC patients (homeless: 4.5%, P=0.03; serious mental illness: 15.2%, P<0.001), than for otherwise similar patients without these characteristics. CONCLUSIONS/POLICY IMPLICATIONS: Study patients treated in PC clinics with greater PC-MHI engagement received similarly high quality depression care, and even higher quality for vulnerable patients. Findings support increasing use of PC-MHI models to the extent that they confer some advantage over existing services (eg, access, patient satisfaction) other than quality of care.

Interprofessional training and team function in patient-centred medical home: Findings from a mixed method study of interdisciplinary provider perspectives.

Transitioning from profession-specific to interprofessional (IP) models of care requires major change. The Veterans Assessment and Improvement Laboratory (VAIL), is an initiative based in the United States that supports and evaluates the Veterans Health Administration's (VAs) transition of its primary care practices to an IP team based patient-centred medical home (PCMH) care model. We postulated that modifiable primary care practice organizational climate factors impact PCMH implementation. VAIL administered a survey to 322 IP team members in primary care practices in one VA administrative region during early implementation of the PCMH and interviewed 79 representative team members. We used convergent mixed methods to study modifiable organizational climate factors in relationship to IP team functioning. We found that leadership support and job satisfaction were significantly positively associated with team functioning. We saw no association between team functioning and either role readiness or team training. Qualitative interview data confirmed survey findings and explained why the association with IP team training might be absent. In conclusion, our findings demonstrate the importance of leadership support and individual job satisfaction in producing highly functioning PCMH teams. Based on qualitative findings, we hypothesize interprofessional training is important, however, inconsistencies in IP training delivery compromise its potential benefit. Future implementation efforts should improve standardization of training process and train team members together. Interprofessional leadership coordination of interprofessional training is warranted.