Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

Cerner Millennium's Care Pathways for Specialty Care Referrals: Provider and Nurse Experiences, Perceptions, and Recommendations for Improvements.

BACKGROUND: Using structured templates to guide providers in communicating key information in electronic referrals is an evidence-based practice for improving care quality. To facilitate referrals in Veterans Health Administration's (VA) Cerner Millennium electronic health record, VA and Cerner have created "Care Pathways"-templated electronic forms, capturing needed information and prompting ordering of appropriate pre-referral tests. OBJECTIVE: To inform their iterative improvement, we sought to elicit experiences, perceptions, and recommendations regarding Care Pathways from frontline clinicians and staff in the first VA site to deploy Cerner Millennium. DESIGN: Qualitative interviews, conducted 12-20 months after Cerner Millennium deployment. PARTICIPANTS: We conducted interviews with primary care providers, primary care registered nurses, and specialty providers requesting and/or receiving referrals. APPROACH: We used rapid qualitative analysis. Two researchers independently summarized interview transcripts with bullet points; summaries were merged by consensus. Constant comparison was used to sort bullet points into themes. A matrix was used to view bullet points by theme and participant. RESULTS: Some interviewees liked aspects of the Care Pathways, expressing appreciation of their premise and logic. However, interviewees commonly expressed frustration with their poor usability across multiple attributes. Care Pathways were reported as being inefficient; lacking simplicity, naturalness, consistency, and effective use of language; imposing an unacceptable cognitive load; and not employing forgiveness and feedback for errors. Specialists reported not receiving the information needed for referral triaging. CONCLUSIONS: Cerner Millennium's Care Pathways, and their associated organizational policies and processes, need substantial revision across several usability attributes. Problems with design and technical limitations are compounding challenges in using standardized templates nationally, across VA sites having diverse organizational and contextual characteristics. VA is actively working to make improvements; however, significant additional investments are needed for Care Pathways to achieve their intended purpose of optimizing specialty care referrals for Veterans.

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.

Veteran Perspectives on Population-Based Suicide Risk Screening in VHA Primary Care: Mixed-Methods Study.

BACKGROUND: In late 2018, VHA implemented a multi-stage suicide risk screening and evaluation initiative, Suicide Risk Identification Strategy, or "Risk ID," in primary care settings. OBJECTIVE: The main objective of this study was to characterize VHA primary care patient perspectives regarding population-based suicide risk screening through the Risk ID program. DESIGN: Mixed methods; survey and qualitative interviews. PARTICIPANTS: Veterans screened for suicide risk using Risk ID in primary care (n = 868) participated in a survey of veteran attitudes about screening (45% response rate); thirty additionally participated in follow-up qualitative interviews. MAIN MEASURES: The quantitative survey consisted of three questions on attitudes about screening for suicidal thoughts in primary care. In qualitative interviews, veterans were asked about their experiences with the Risk ID processes and recommendations for improving Risk ID. KEY RESULTS: Over 90% of veterans reported that it is appropriate for primary care providers or nurses/medical assistants to ask veterans about thoughts of suicide during primary care visits. Approximately half of veterans indicated that veterans should be asked about suicidal thoughts at every visit. Qualitative findings revealed that while most veterans were generally supportive and appreciated VHA screening for suicidal thoughts, they also expressed concern for the potential for inadvertent harm. Participants expressed conflicting preferences for how screening should be handled and delivered. CONCLUSIONS: Findings suggest that most veterans support the integration of standardized suicide risk assessment into routine primary care visits. However, findings also suggest that population-based suicide risk assessment should further consider patient experiences and preferences. Specifically, additional guidance or training for staff conducting suicide risk screening may be warranted to ensure patients feel heard (e.g., eye contact, expressing empathy) and increase patient understanding of the purpose of the screening and potential outcomes. These patient-centered approaches may improve patient experience and facilitate disclosure of suicidal thoughts.

Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans.

BACKGROUND: Although research shows that more depressed patients respond to combined antidepressants (ADM) and psychotherapy than either alone, many patients do not respond even to combined treatment. A reliable prediction model for this could help treatment decision-making. We attempted to create such a model using machine learning methods among patients in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of VHA patients beginning combined depression treatment completed self-report assessments at baseline and 3 months (n = 658). A learning model was developed using baseline self-report, administrative, and geospatial data to predict 3-month treatment response defined by reductions in the Quick Inventory of Depression Symptomatology Self-Report and/or in the Sheehan Disability Scale. The model was developed in a 70 % training sample and tested in the remaining 30 % test sample. RESULTS: 30.0 % of patients responded to treatment. The prediction model had a test sample AUC-ROC of 0.657. A strong gradient was found in probability of treatment response from 52.7 % in the highest predicted quintile to 14.4 % in the lowest predicted quintile. The most important predictors were episode characteristics (symptoms, comorbidities, history), personality/psychological resilience, recent stressors, and treatment characteristics. LIMITATIONS: Restrictions in sample definition, a low recruitment rate, and reliance on patient self-report rather than clinician assessments to determine treatment response limited the generalizability of results. CONCLUSIONS: A machine learning model could help depressed patients and providers predict likely response to combined ADM-psychotherapy. Parallel information about potential harms and costs of alternative treatments would be needed, though, to inform optimal treatment selection.

Primary Care and Mental Health Staff Perspectives on Universal Suicide Risk Screening and Care Coordination.

Little is known about staff or patient perspectives on suicide risk screening programs. The objectives of this study were to characterize Veterans Health Administration (VHA) primary care and mental health staff perspectives regarding the VHA Suicide Risk Identification Strategy screening and assessment program and to describe coordination of suicide prevention-related care following positive screening results. Qualitative interviews were conducted with 40 primary care and mental health staff at 12 VHA facilities. An inductive-deductive hybrid approach was used to conduct a thematic analysis. Several key themes were identified. Primary care and mental health staff participants accepted having a structured process for screening for suicidal ideation and conducting risk assessments, but both groups noted limitations and challenges with initial assessment and care coordination following screening. Mental health staff reported more concerns than primary care staff about negative impacts of the screening and assessment process on treatment. Both groups felt that better training was needed for primary care staff to effectively discuss and evaluate suicide risk. The results suggested that additional modifications of the screening and assessment process are needed for patients already known to have elevated risk of suicide or chronic suicidal ideation.

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.

Does screening for PTSD lead to VA mental health care? Identifying the spectrum of initial VA screening actions.

Despite the active posttraumatic stress disorder (PTSD) screening program in Department of Veterans Affairs (VA) primary care clinics and the availability of empirically supported treatments for PTSD at VA, many veterans for whom screening suggests treatment may be indicated do not gain access to VA-based mental health care. To determine where we may be losing veterans to follow-up, we need to begin by identifying the initial action taken in response to a positive PTSD screen in primary care. Using VA administrative data and chart review, we identified the spectrum of initial actions taken after veterans screened positive for PTSD in VA primary care clinics nationwide between October 2017 and September 2018 (N = 41,570). We collapsed actions into those that could lead to VA-based mental health care (e.g., consult placed to a VA mental health clinic) versus not (e.g., veteran declined care), and then examined the association between these categories of actions and contextual- and individual-level variables. More than 61% of veterans with positive PTSD screens had evidence that an initial action toward VA-based mental health care was taken. Urban-dwelling and female veterans were significantly more likely to have evidence of these initial actions, whereas White and Vietnam-era veterans were significantly less likely to have this evidence. Our findings suggest that most veterans screening positive for PTSD in VA primary care clinics have evidence of initial actions taken toward VA-based mental health care; however, a substantial minority do not, making them unlikely to receive follow-up care. Findings highlight the potential benefit of targeted primary care-based access interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Electronic Population-Based Depression Detection and Management Through Universal Screening in the Veterans Health Administration.

Importance: In 2016, the US Preventive Services Task Force newly recommended universal screening for depression, with the expectation that screening would be associated with appropriate treatment. Few studies have been able to assess the population-based trajectory from screening to receipt of follow-up and treatment for individuals with depression. Objective: To examine adherence to guidelines for follow-up and treatment among primary care patients who newly screened positive for depression in the Veterans Health Administration (VA). Design, Setting, and Participants: This retrospective cohort study used VA electronic data to identify patients who newly screened positive for depression on the 2-item Patient Health Questionnaire at 82 primary care VA clinics in California, Arizona, and New Mexico between October 1, 2015, and September 30, 2019. Data analysis was performed from December 2020 to August 2021. Main Outcomes and Measures: Receipt of guideline-concordant care for screen-positive patients who were determined by clinicians as having depression was assessed. Timely follow-up (within 84 days of screening) was defined as receiving 3 or more mental health specialty visits, 3 or more psychotherapy visits, or 3 or more primary care visits with a depression diagnosis according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Completing at least minimal treatment (within 12 months) was defined as having 60 days or more of antidepressant prescriptions filled, 4 or more mental health specialty visits, or 3 or more psychotherapy visits. Results: The final cohort included 607 730 veterans (mean [SD] age, 59.4 [18.2] years; 546 516 men [89.9%]; 339 811 non-Hispanic White [55.9%]); 8%, or 82 998 of 997 185 person-years, newly screened positive for depression. Clinicians identified fewer than half with depression (15 155 patients), of whom 32% (5034 of 15 650 person-years) met treatment guidelines for timely follow-up and 77% (12 026 of 15 650 person-years) completed at least minimal treatment. Younger age (odds ratio, 0.990; 95% CI, 0.986-0.993; P < .001), Black race (odds ratio, 1.19; 95% CI, CI 1.05-1.34; P = .01), and having comorbid psychiatric diagnoses were significantly associated with timely follow-up. Individual quality metric components (eg, medication or psychotherapy) were associated differently with overall quality results among patient groups, except for age. Conclusions and Relevance: In this cohort study, most patients met the guidelines for completing at least minimal treatment, but only a minority received timely follow-up after screening positive and being identified as having depression. More research is needed to understand whether the discrepancy between patients who screened positive and patients identified as having depression reflects a gap in recognition of needed care.

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.

Veterans Health Administration staff experiences with suicidal ideation screening and risk assessment in the context of COVID-19.

Universal screening for suicidal ideation in primary care and mental health settings has become a key prevention tool in many healthcare systems, including the Veterans Healthcare Administration (VHA). In response to the coronavirus pandemic, healthcare providers faced a number of challenges, including how to quickly adapt screening practices. The objective of this analyses was to learn staff perspectives on how the pandemic impacted suicide risk screening in primary care and mental health settings. Forty semi-structured interviews were conducted with primary care and mental health staff between April-September 2020 across 12 VHA facilities. A multi-disciplinary team employed a qualitative thematic analysis using a hybrid inductive/deductive approach. Staff reported multiple concerns for patients during the crisis, especially regarding vulnerable populations at risk for social isolation. Lack of clear protocols at some sites on how to serve patients screening positive for suicidal ideation created confusion for staff and led some sites to temporarily stop screening. Sites had varying degrees of adaptability to virtual based care, with the biggest challenge being completion of warm hand-offs to mental health specialists. Unanticipated opportunities that emerged during this time included increased ability of patients and staff to conduct virtual care, which is expected to continue benefit post-pandemic.

Comorbid mental disorders, depression symptom severity, and role impairment among Veterans initiating depression treatment through the Veterans Health Administration.

BACKGROUND: Psychiatric comorbidities may complicate depression treatment by being associated with increased role impairments. However, depression symptom severity might account for these associations. Understanding the independent associations of depression severity and comorbidity with impairments could help in treatment planning. This is especially true for depressed Veterans, who have high psychiatric comorbidity rates. METHODS: 2,610 Veterans beginning major depression treatment at the Veterans Health Administration (VHA) were administered a baseline self-report survey that screened for diverse psychiatric comorbidities and assessed depression severity and role impairments. Logistic and generalized linear regression models estimated univariable and multivariable associations of depression severity and comorbidities with impairments. Population attributable risk proportions (PARPs) estimated the relative importance of depression severity and comorbidities in accounting for role impairments. RESULTS: Nearly all patients (97.8%) screened positive for at least one comorbidity and half (49.8%) for 4+ comorbidities. The most common positive screens were for generalized anxiety disorder (80.2%), posttraumatic stress disorder (77.9%), and panic/phobia (77.4%). Depression severity and comorbidities were significantly and additively associated with impairments in multivariable models. Associations were attenuated much less for depression severity than for comorbidities in multivariable versus univariable models. PARPs indicated that 15-60% of role impairments were attributable to depression severity and 5-32% to comorbidities. LIMITATIONS: The screening scales could have over-estimated comorbidity prevalence. The cross-sectional observational design cannot determine either temporal or causal priorities. CONCLUSIONS: Although positive screens for psychiatric comorbidity are pervasive among depressed VHA patients, depression severity accounts for most of the associations of these comorbidities with role impairments.

Treatment Differences in Primary and Specialty Settings in Veterans with Major Depression.

INTRODUCTION: The Veterans Health Administration (VHA) supports the nation's largest primary care-mental health integration (PC-MHI) collaborative care model to increase treatment of mild to moderate common mental disorders in primary care (PC) and refer more severe-complex cases to specialty mental health (SMH) settings. It is unclear how this treatment assignment works in practice. METHODS: Patients (n = 2610) who sought incident episode VHA treatment for depression completed a baseline self-report questionnaire about depression severity-complexity. Administrative data were used to determine settings and types of treatment during the next 30 days. RESULTS: Thirty-four percent (34.2%) of depressed patients received treatment in PC settings, 65.8% in SMH settings. PC patients had less severe and fewer comorbid depressive episodes. Patients with lowest severity and/or complexity were most likely to receive PC antidepressant medication treatment; those with highest severity and/or complexity were most likely to receive combined treatment in SMH settings. Assignment of patients across settings and types of treatment was stronger than found in previous civilian studies but less pronounced than expected (cross-validated AUC = 0.50-0.68). DISCUSSION: By expanding access to evidence-based treatments, VHA's PC-MHI increases consistency of treatment assignment. Reasons for assignment being less pronounced than expected and implications for treatment response will require continued study.

Diagnostic Accuracy and Acceptability of the Primary Care Posttraumatic Stress Disorder Screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) Among US Veterans.

Importance: Posttraumatic stress disorder (PTSD) is a serious mental health disorder that can be effectively treated with empirically based practices. PTSD screening is essential for identifying undetected cases and providing patients with appropriate care. Objective: To determine whether the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PC-PTSD-5) is a diagnostically accurate and acceptable measure for use in Veterans Affairs (VA) primary care clinics. Design, Setting, and Participants: This cross-sectional, diagnostic accuracy study enrolled participants from May 19, 2017, to September 26, 2018. Participants were recruited from primary care clinics across 2 VA Medical Centers. Session 1 was conducted in person, and session 2 was completed within 30 days via telephone. A consecutive sample of 1594 veterans, aged 18 years or older, who were scheduled for a primary care visit was recruited. Data analysis was performed from March 2019 to August 2020. Exposures: In session 1, participants completed a battery of questionnaires. In session 2, a research assistant administered the PC-PTSD-5 to participants, and then a clinician assessor blind to PC-PTSD-5 results conducted a structured diagnostic interview for PTSD. Main Outcomes and Measures: The range of PC-PTSD-5 cut points overall and across gender was assessed, and diagnostic performance was evaluated by calculating weighted κ values. Results: In total, 495 of 1594 veterans (31%) participated, and 396 completed all measures and were included in the analyses. Participants were demographically similar to the VA primary care population (mean [SD] age, 61.4 [15.5] years; age range, 21-93 years) and were predominantly male (333 participants [84.1%]) and White (296 of 394 participants [75.1%]). The PC-PTSD-5 had high levels of diagnostic accuracy for the overall sample (area under the receiver operating characteristic curve [AUC], 0.927; 95% CI, 0.896-0.959), men (AUC, 0.932; 95% CI, 0.894-0.969), and women (AUC, 0.899, 95% CI, 0.824-0.974). A cut point of 4 ideally balanced false negatives and false positives for the overall sample and for men. However, for women, this cut point resulted in high numbers of false negatives (6 veterans [33.3%]). A cut point of 3 fit better for women, despite increasing the number of false positives. Participants rated the PC-PTSD-5 as highly acceptable. Conclusions and Relevance: The PC-PTSD-5 is an accurate and acceptable screening tool for use in VA primary care settings. Because performance parameters will change according to sample, clinicians should consider sample characteristics and screening purposes when selecting a cut point.

Assessment of Rates of Suicide Risk Screening and Prevalence of Positive Screening Results Among US Veterans After Implementation of the Veterans Affairs Suicide Risk Identification Strategy.

Importance: In 2018, the Veterans Health Administration (VHA) implemented the Veterans Affairs (VA) Suicide Risk Identification Strategy to improve the identification and management of suicide risk among veterans receiving VHA care. Objectives: To examine the prevalence of positive suicide screening results among veterans in ambulatory care and emergency departments (EDs) or urgent care clinics (UCCs) and to compare acuity of suicide risk among patients screened in these settings. Design, Setting, and Participants: This cross-sectional study used data from the VA's Corporate Data Warehouse (CDW) to assess veterans with at least 1 ambulatory care visit (n = 4 101 685) or ED or UCC visit (n = 1 044 056) at 140 VHA medical centers from October 1, 2018, through September 30, 2019. Exposures: Standardized suicide risk screening and evaluation tools. Main Outcomes and Measures: One-year rate of suicide risk screening and evaluation, prevalence of positive primary and secondary suicide risk screening results, and levels of acute and chronic risk based on the VHA's Comprehensive Suicide Risk Evaluation. Results: A total of 4 101 685 veterans in ambulatory care settings (mean [SD] age, 62.3 [16.4] years; 3 771 379 [91.9%] male; 2 996 974 [73.1%] White) and 1 044 056 veterans in ED or UCC settings (mean [SD] age, 59.2 [16.2] years; 932 319 [89.3%] male; 688 559 [66.0%] White) received the primary suicide screening. The prevalence of positive suicide screening results was 3.5% for primary screening and 0.4% for secondary screening in ambulatory care and 3.6% for primary screening and 2.1% in secondary screening for ED and UCC settings. Compared with veterans screened in ambulatory care, those screened in the ED or UCC were more likely to endorse suicidal ideation with intent (odds ratio [OR], 4.55; 95% CI, 4.37-4.74; P < .001), specific plan (OR, 3.16; 95% CI, 3.04-3.29; P < .001), and recent suicidal behavior (OR, 1.95; 95% CI, 1.87-2.03; P < .001) during secondary screening. Among the patients who received a Comprehensive Suicide Risk Evaluation, those in ED or UCC settings were more likely than those in ambulatory care settings to be at high acute risk (34.1% vs 8.5%; P < .001). Conclusions and Relevance: In this cross-sectional study, population-based suicide risk screening and evaluation in VHA ambulatory care and ED or UCC settings may help identify risk among patients who may not be receiving mental health treatment. Higher acuity of risk among veterans in ED or UCC settings compared with those in ambulatory care settings highlights the importance of scaling up implementation of brief evidence-based interventions in the ED or UCC to reduce suicidal behavior.

Association of Veterans Affairs Primary Care Mental Health Integration With Care Access Among Men and Women Veterans.

Importance: Women veterans increasingly seek care yet continue to face barriers in the Veterans Health Administration (VA), which predominantly cares for men. Evidence-based collaborative care models can improve patient access to treatment of depression, which is experienced at higher rates by women. While the VA has implemented these care models nationally, it is not known whether access improvements occur equitably across genders in primary care. Objective: To examine whether the VA's national Primary Care-Mental Health Integration (PC-MHI) initiative (beginning 2007) expanded realized access to mental health care similarly for men and women. Design, Setting, and Participants: This cohort study included 5 377 093 million primary care patients assigned to 396 VA clinics that provided integrated mental health services nationally between October 2013 and September 2016. Data analysis occurred between May 2017 and July 2020. Exposures: Clinic PC-MHI penetration, calculated as the proportion of clinic patients who saw an integrated specialist per fiscal year. Main Outcomes and Measures: Estimates of mean VA health care utilization (mental health, primary care, other specialty care, telephone, hospitalizations) and median total costs for men and women. Multilevel models adjusted for year, clinic, patient characteristics, and interactions between patient-defined gender and clinic PC-MHI penetration. Results: This study examined 5 377 093 veterans (448 455 [8.3%] women; 3 744 140 [69.6%] White) with a mean (SD) baseline age 62.0 (16.6) years. Each percentage-point increase in the proportion of clinic patients who saw an integrated specialist was associated with 38% fewer mental health visits per year for women (incidence rate ratio [IRR], 0.62; 95% CI, 0.60-0.65), but 39% more visits for men (IRR, 1.39; 95% CI, 1.34-1.44; P < .001). Both men and women had more primary care visits (men: IRR, 1.40; 95% CI, 1.36-1.45; women: IRR, 1.22; 95% CI, 1.17-1.28; P < .001) and total costs (men: ß [SE], 2.23 [0.10]; women: ß [SE], 1.24 [0.15]; P = .06), but women had 74% fewer hospitalizations than men related to clinics with mental health integration (IRR, 0.26; 95% CI, 0.19-0.36 vs IRR, 1.02; 95% CI, 0.83-1.24; P < .001). Conclusions and Relevance: While greater outpatient service use for men was observed in this study, PC-MHI was associated with a decrease in mental health specialty visits (and hospitalizations) for women veterans, potentially signifying a shift of services to primary care. With increasing patient choice for where veterans receive care, the VA must tailor medical care to the needs of rising numbers of women patients. Differences in health care utilization by gender highlight the importance of anticipating policy impacts on and tailoring services for patients in the numerical minority in the VA and other health systems.

Protocol: examining the effectiveness of an adaptive implementation intervention to improve uptake of the VA suicide risk identification strategy: a sequential multiple assignment randomized trial.

BACKGROUND: In 2018, the Veterans Health Administration (VHA) mandated implementation of a national suicide risk identification strategy (Risk ID). The goal of Risk ID is to improve the detection and management of suicide risk by standardizing suicide risk screening and evaluation enterprise-wide. In order to ensure continuous quality improvement (QI), ongoing evaluation and targeted interventions to improve implementation of Risk ID are needed. Moreover, given that facilities will vary with respect to implementation needs and barriers, the dose and type of intervention needed may vary across facilities. Thus, the objective of this study is to examine the effectiveness of an adaptive implementation strategy to improve the uptake of suicide risk screening and evaluation in VHA ambulatory care settings. In addition, this study will examine specific factors that may impact the uptake of suicide risk screening and evaluation and the adoption of different implementation strategies. This protocol describes the stepped implementation approach and proposed evaluation plan. METHODS: Using a sequential multiple assignment randomized trial (SMART) design, two evidence-based implementation strategies will be evaluated: (1) audit and feedback (A&F); (2) A&F plus external facilitation (A&F + EF). Implementation outcomes of interest include uptake of secondary suicide risk screening and uptake of comprehensive suicide risk evaluation (stages 2 and 3 of Risk ID). Secondary outcomes include rates of other clinical outcomes (i.e., safety planning) and organizational factors that may impact Risk ID implementation (i.e., leadership climate and leadership support). DISCUSSION: This national QI study will use a SMART design to evaluate whether an adaptive implementation strategy is effective in improving uptake of a mandated VHA-wide suicide risk screening and evaluation initiative. If this study finds that the proposed stepped implementation strategy is effective at increasing uptake and maintaining performance improvements, this approach may be used as an overarching QI strategy for other national suicide prevention programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04243330 . Registered 28 January 2020.

Characteristics and Injury Mechanisms of Veteran Primary Care Suicide Decedents with and without Diagnosed Mental Illness.

BACKGROUND: In the United States, suicide rates are increasing among nearly all age groups. Primary care is a critical setting for suicide prevention, where interventions often rely on identifying mental health conditions as indicators of elevated suicide risk. OBJECTIVE: Quantify the proportion of suicide decedents within primary care who had no antecedent mental health or substance use diagnosis. DESIGN: Retrospective cohort study. PARTICIPANTS: Veterans who received Veterans Health Administration (VHA) primary care any time from 2000 to 2014 and died by suicide before 2015 (n = 27,741). MAIN MEASURES: We categorized decedents by whether they had any mental health or substance use diagnosis (yes/no) using ICD-9 codes available from VHA records. We compared sociodemographic, clinical, and suicide mechanism characteristics between groups using chi-square, Student's T, or Wilcoxon tests. RESULTS: Forty-five percent of decedents had no mental health or substance use diagnosis. Decedents without such a diagnosis were older (68 vs. 57 years, p < 0.001), and more likely to be male (98.3% vs. 95.8%, p < 0.001), non-Hispanic White (90.6% vs. 87.9%, p < 0.001), married/partnered (50.4% vs. 36.6%, p < 0.001), and without military service-connected disability benefits (72.6% vs. 56.9%, p < 0.001). They were also more likely to die from firearm injury (78.9% vs. 60.7%, p < 0.001). There were statistically significant differences in physical health between groups, but the magnitudes of those differences were small. Decedents without a mental health or substance use diagnosis had significantly shorter durations of enrollment in VHA healthcare, less healthcare utilization in their last year of life, and had little utilization aside from primary care visits. CONCLUSIONS AND RELEVANCE: From 2000 to 2014, of nearly thirty thousand VHA primary care patients who died by suicide, almost half had no antecedent mental health or substance use diagnosis. Within VHA primary care settings, suicide risk screening for those with and without such a diagnosis is indicated.

Mortality Among Veterans with Major Mental Illnesses Seen in Primary Care: Results of a National Study of Veteran Deaths.

BACKGROUND: Premature mortality observed among the mentally ill is largely attributable to chronic illnesses. Veterans seen within Veterans Affairs (VA) have a higher prevalence of mental illness than the general population but there is limited investigation into the common causes of death of Veterans with mental illnesses. OBJECTIVE: To characterize the life expectancy of mentally ill Veterans seen in VA primary care, and to determine the most death rates of combinations of mental illnesses. DESIGN: Retrospective cohort study of decedents. SETTING/PARTICIPANTS: Veterans seen in VA primary care clinics between 2000 and 2011 were included. Records from the VA Corporate Data Warehouse (CDW) were merged with death information from the National Death Index. MAIN MEASURES: Mental illnesses were determined using ICD9 codes. Direct standardization methods were used to calculate age-adjusted gender and cause-specific death rates per 1000 deaths for patients with and without depression, anxiety, post-traumatic stress disorder (PTSD), substance use disorder (SUD), serious mental illness (SMI), and combinations of those diagnoses. KEY RESULTS: Of the 1,763,982 death records for Veterans with 1 + primary care visit, 556,489 had at least one mental illness. Heart disease and cancer were the two leading causes of death among Veterans with or without a mental illness, accounting for approximately 1 in 4 deaths. Those with SUD (n = 204,950) had the lowest mean age at time of death (64 ± 12 years). Among men, the death rates were as follows: SUD (55.9/1000); anxiety (49.1/1000); depression (45.1/1000); SMI (40.3/1000); and PTSD (26.2/1000). Among women, death rates were as follows: SUD (55.8/1000); anxiety (36.7/1000); depression (45.1/1000); SMI (32.6/1000); and PTSD (23.1/1000 deaths). Compared to men (10.8/1000) and women (8.7/1000) without a mental illness, these rates were multiple-fold higher in men and in women with a mental illness. A greater number of mental illness diagnoses was associated with higher death rates among men and women (p < 0.0001). CONCLUSIONS: Veterans with mental illnesses, particularly those with SUD, and those with multiple diagnoses, had shorter life expectancy than those without a mental illness. Future studies should examine both patient and systemic sources of disparities in providing chronic illness care to Veterans with a mental illness.