Recruitment tools for transgender and gender diverse veterans in health care research.

Transgender and gender diverse (TGD) veterans in the Veterans Health Administration experience health and health care disparities, and research with this population is needed to improve gender-affirming care in Veterans Health Administration. However, TGD veterans may experience hesitancy to participate in research. We must address barriers to participation through feasible and acceptable methods. Opt-out letters are an effective tool used to recruit veterans in mental health research. The present study examined the feasibility and acceptability of opt-out letters modified for TGD veterans. Opt-out letters were sent to 54 potential TGD participants at three sites. The letters stated the research team would begin contacting veterans by phone in 2 weeks if they did not opt out of being contacted. Feasibility was measured through response rate. Acceptability was assessed through qualitative template analysis of interview data. Of the 54 potential participants, two opted out, three letters were undeliverable, and eight veterans called to opt in. Veterans reported that they found the letters to be clear and useful. The responses to the opt-out letters resulted in completing recruitment for two of the three sites. The research team then called the veterans who received the letter at the third site (three veterans) and recruited one additional veteran, for a total of nine TGD veterans. Opt-out letters may be a helpful tool to recruit TGD veterans to participate in research. Although these letters were designed to opt out, 89% of participants called the research team to opt in. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cost comparison of in-person and telehealth modalities for a suicide safety planning group intervention: interim results from the "Project Life Force" randomized clinical trial.

Suicide prevention is a clinical priority for the US Veterans Health Administration. Evidence-based interventions, including developing a suicide safety plan, are recommended practices and are becoming more widespread. Adaptations to further augment safety planning include a manualized group intervention (Project Life Force, PLF) that combines safety planning with the teaching of skills to maximize use of the plan. A multi-year randomized controlled trial to test efficacy of PLF compared to treatment as usual is currently in progress. However, approximately a year into the study, in-person groups were converted to telehealth groups due to the COVID-19 pandemic. This study compares the per-veteran cost of PLF when delivered in-person versus by telehealth using preliminary trial data from the first 2.5 years of the trial. Cost to deliver PLF was obtained from the Veterans Health Administration's Managerial Cost Accounting data, which relies on activity-based costing. We found no significant differences in the average number of sessions or average group size between in-person and telehealth. However, the cost per group session was lower for the telehealth modality and this led to significant overall per-veteran savings. While efficacy data comparing from the two arms is still underway and we await the ongoing RCT results, our interim cost analysis highlights potential savings with the telehealth modality.

Increasing consumer engagement: tools to engage service users in quality improvement or implementation efforts.

Introduction: Engaging service users or consumers in quality improvement or implementing a new service is important across settings and may reduce health inequities. Implementation strategies leveraging consumer engagement are neither commonly used nor robustly operationalized in implementation science. Implementers (e.g., middle managers, facilitators) want to involve consumers in implementation activities, but do not always feel confident in how to proceed. We developed a compendium of tools called Consumer Voice to guide others how to engage consumers in design/delivery of implementation strategies. Although generalizable to other settings, we developed Consumer Voice within the context of implementing suicide prevention treatments in healthcare to reach rural U.S. military veterans, as there are suicide inequities for people in rural areas. Methods: We developed Consumer Voice using a multistep process and human-centered design methods. In between steps, a design team met to generate insights from data, and decide which prototypes to create/refine. In preliminary work, we conducted a scan of examples in healthcare of patient engagement in implementation activities and interviewed two implementation experts about preferred learning styles. In Step 1, we interviewed 26 participants with experience in community engagement, implementation, or lived experience as a rural U.S. veteran with suicidal thoughts/behavior. In Step 2, 11 implementers beta tested prototypes then share feedback in focus groups. In Step 3, we reconvened participants from prior steps to review tools and, using nominal group technique, prioritized remaining recommendations. Results: Consumer Voice is online, modular, and nonlinear for self-guided learning tailored to beginner, intermediate, or advanced experience with consumer engagement. Tools consist of slides, audiovisual content with written text, and templates. Findings indicated there is not one "right" way to engage consumers in implementation activities, rather that implementers wanted tools showcasing core principles for consumer engagement and practical ideas. Discussion: Consumer Voice can be used by implementers to reflect and decide on how to apply consumer engagement implementation strategies to improve equitable dissemination and uptake of evidence-based practices. Most insights generated by user data were explicitly to build trust between consumers and professionals representing institutions, which may be one component to reducing healthcare inequities.

Evaluation of a Model to Target High-risk Psychiatric Inpatients for an Intensive Postdischarge Suicide Prevention Intervention.

Importance: The months after psychiatric hospital discharge are a time of high risk for suicide. Intensive postdischarge case management, although potentially effective in suicide prevention, is likely to be cost-effective only if targeted at high-risk patients. A previously developed machine learning (ML) model showed that postdischarge suicides can be predicted from electronic health records and geospatial data, but it is unknown if prediction could be improved by adding additional information. Objective: To determine whether model prediction could be improved by adding information extracted from clinical notes and public records. Design, Setting, and Participants: Models were trained to predict suicides in the 12 months after Veterans Health Administration (VHA) short-term (less than 365 days) psychiatric hospitalizations between the beginning of 2010 and September 1, 2012 (299 050 hospitalizations, with 916 hospitalizations followed within 12 months by suicides) and tested in the hospitalizations from September 2, 2012, to December 31, 2013 (149 738 hospitalizations, with 393 hospitalizations followed within 12 months by suicides). Validation focused on net benefit across a range of plausible decision thresholds. Predictor importance was assessed with Shapley additive explanations (SHAP) values. Data were analyzed from January to August 2022. Main Outcomes and Measures: Suicides were defined by the National Death Index. Base model predictors included VHA electronic health records and patient residential data. The expanded predictors came from natural language processing (NLP) of clinical notes and a social determinants of health (SDOH) public records database. Results: The model included 448 788 unique hospitalizations. Net benefit over risk horizons between 3 and 12 months was generally highest for the model that included both NLP and SDOH predictors (area under the receiver operating characteristic curve range, 0.747-0.780; area under the precision recall curve relative to the suicide rate range, 3.87-5.75). NLP and SDOH predictors also had the highest predictor class-level SHAP values (proportional SHAP = 64.0% and 49.3%, respectively), although the single highest positive variable-level SHAP value was for a count of medications classified by the US Food and Drug Administration as increasing suicide risk prescribed the year before hospitalization (proportional SHAP = 15.0%). Conclusions and Relevance: In this study, clinical notes and public records were found to improve ML model prediction of suicide after psychiatric hospitalization. The model had positive net benefit over 3-month to 12-month risk horizons for plausible decision thresholds. Although caution is needed in inferring causality based on predictor importance, several key predictors have potential intervention implications that should be investigated in future studies.

Implementation of LGBTQ+ affirming care policies in the Veterans Health Administration: preliminary findings on barriers and facilitators in the southern United States.

Background: In the United States Department of Veterans Affairs (VA), veterans who are lesbian, gay, bisexual, transgender, queer, and similar gender and sexual minoritized people (LGBTQ+) experience health disparities compared to cisgender, heterosexual veterans. VA's LGBTQ+ Health Program created two healthcare policies on providing LGBTQ+ affirming care (healthcare that is inclusive, validating, and understanding of the LGBTQ+ population). The current project examines providers' barriers and facilitators to providing LGBTQ+ affirming care and LGBTQ+ veterans' barriers and facilitators to receiving LGBTQ+ affirming care. Methods: Data collection and analysis were informed by the Consolidated Framework for Implementation Research, which was adapted to include three health equity domains. Data collection involved telephone interviews conducted with 11 VA providers and 12 LGBTQ+ veterans at one rural and one urban VA medical center, and one rural VA community clinic. Qualitative data were rapidly analyzed using template analysis, a data reduction technique. Results: Providers described limited education, limited time, lack of experience with the population, and a lack of awareness of resources as barriers. Providers discussed comfort with consulting trusted peers, interest in learning more about providing LGBTQ+ affirming care, and openness and acceptance of the LGBTQ+ community as facilitators. LGBTQ+ veterans described a lack of provider awareness of their needs, concerns related to safety and discrimination, and structural discrimination as barriers. LGBTQ+ veterans described positive relationships with providers, knowledge of their own healthcare needs, and ability to advocate for their healthcare needs as facilitators. Although VA's LGBTQ+ affirming care policies are in place, providers and veterans noted a lack of awareness regarding specific healthcare processes. Conclusion: Allowing more time and capacity for education and engaging LGBTQ+ veterans in determining how to improve their healthcare may be the path forward to increase adherence to LGBTQ+ affirming care policies. Engaging patients, especially those from marginalized backgrounds, in strategies focused on the uptake of policy may be a path to improve policy implementation. It is possible that creating truly collaborative structures in which patients, staff, providers, leadership, and policymakers can work together towards policy implementation may be a useful strategy. In turn, improved policy implementation would result in increased physical and mental health for LGBTQ+ veterans.

Determining feasibility of incorporating consumer engagement into implementation activities: study protocol of a hybrid effectiveness-implementation type II pilot.

INTRODUCTION: Implementation researchers could draw from participatory research to engage patients (consumers of healthcare) in implementation processes and possibly reduce healthcare disparities. There is a little consumer involvement in healthcare implementation, partially because no formal guidance exists. We will create and pilot a toolkit of methods to engage consumers from the US' Veterans Health Administration (VHA) in selecting and tailoring implementation strategies. This toolkit, Consumer Voice, will provide guidance on what, when, where, how and why an implementer might engage consumers in implementing treatments. We will pilot the toolkit by implementing Safety Planning Intervention for suicide prevention with rural veterans, a population with suicide disparities. Safety Planning Intervention is effective for reducing suicidal behaviours. METHODS AND ANALYSIS: In Aim 1, we will use participatory approaches and user-centred design to develop Consumer Voice and its methods. In Aim 2, we will pilot Consumer Voice by implementing the Safety Planning Intervention in two clinics serving rural VHA patients. One site will receive a current implementation strategy (Implementation Facilitation) only; the second will receive Implementation Facilitation plus Consumer Voice. We will use mixed methods to assess feasibility and acceptability of Consumer Voice. We will compare sites on preliminary implementation (reach, adoption, fidelity) and clinical outcomes (depression severity, suicidal ideation, suicidal behaviour). In Aim 3, we will evaluate Aim 2 outcomes at 20 months to assess sustained impact. We will gather qualitative data on sustainability of the Safety Planning Intervention. ETHICS AND DISSEMINATION: These studies are overseen by the Institutional Review Board at the Central Arkansas Veterans Healthcare System. We plan to use traditional academic modalities of dissemination (eg, conferences, publications). We plan to disseminate findings through meetings with other trainers in implementation practice so they may adopt Consumer Voice. We plan to share results with local community boards.

Evaluation of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration.

Importance: The Veterans Health Administration (VHA) implemented a national clinical program using a suicide risk prediction algorithm, Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET), in which clinicians facilitate care enhancements for individuals identified in local top 0.1% suicide risk tiers. Evaluation studies are needed. Objective: To determine associations with treatment engagement, health care utilization, suicide attempts, safety plan documentation, and 6-month mortality. Design, Setting, and Participants: This cohort study used triple differences analyses comparing 6-month changes in outcomes after vs before program entry for individuals entering the REACH VET program (March 2017-December 2018) vs a similarly identified top 0.1% suicide risk tier cohort from prior to program initiation (March 2014-December 2015), adjusting for trends across subthreshold cohorts. Subcohort analyses (including individuals from March 2017-June 2018) evaluated difference-in-differences for cause-specific mortality using death certificate data. The subthreshold cohorts included individuals in the top 0.3% to 0.1% suicide risk tier, below the threshold for REACH VET eligibility, from the concurrent REACH VET period and from the pre-REACH VET period. Data were analyzed from December 2019 through September 2021. Exposures: REACH VET-designated clinicians treatment reevaluation and outreach for care enhancements, including safety planning, increased monitoring, and interventions to enhance coping. Main Outcomes and Measures: Process outcomes included VHA scheduled, completed, and missed appointments; mental health visits; and safety plan documentation and documentation within 6 months for individuals without plans within the prior 2 years. Clinical outcomes included mental health admissions, emergency department visits, nonfatal suicide attempts, and all-cause, suicide, and nonsuicide external-cause mortality. Results: A total of 173 313 individuals (mean [SD] age, 51.0 [14.7] years; 161 264 [93.1%] men and 12 049 [7.0%] women) were included in analyses, including 40 816 individuals eligible for REACH VET care and 36 604 individuals from the pre-REACH VET period in the top 0.1% of suicide risk. The REACH VET intervention was associated with significant increases in completed outpatient appointments (adjusted triple difference [ATD], 0.31; 95% CI, 0.06 to 0.55) and proportion of individuals with new safety plans (ATD, 0.08; 95% CI, 0.06 to 0.10) and reductions in mental health admissions (ATD, -0.08; 95% CI, -0.10 to -0.05), emergency department visits (ADT, -0.03; 95% CI, -0.06 to -0.01), and suicide attempts (ADT, -0.05; 95% CI, -0.06 to -0.03). Subcohort analyses did not identify differences in suicide or all-cause mortality (eg, age-and-sex-adjusted difference-in-difference for suicide mortality, 0.0007; 95% CI, -0.0006 to 0.0019). Conclusions and Relevance: These findings suggest that REACH VET implementation was associated with greater treatment engagement and new safety plan documentation and fewer mental health admissions, emergency department visits, and suicide attempts. Clinical programs using risk modeling may be effective tools to support care enhancements and risk reduction.

Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System.

There is a very high suicide rate in the year after psychiatric hospital discharge. Intensive postdischarge case management programs can address this problem but are not cost-effective for all patients. This issue can be addressed by developing a risk model to predict which inpatients might need such a program. We developed such a model for the 391,018 short-term psychiatric hospital admissions of US veterans in Veterans Health Administration (VHA) hospitals 2010-2013. Records were linked with the National Death Index to determine suicide within 12 months of hospital discharge (n=771). The Super Learner ensemble machine learning method was used to predict these suicides for time horizon between 1 week and 12 months after discharge in a 70% training sample. Accuracy was validated in the remaining 30% holdout sample. Predictors included VHA administrative variables and small area geocode data linked to patient home addresses. The models had AUC=.79-.82 for time horizons between 1 week and 6 months and AUC=.74 for 12 months. An analysis of operating characteristics showed that 22.4%-32.2% of patients who died by suicide would have been reached if intensive case management was provided to the 5% of patients with highest predicted suicide risk. Positive predictive value (PPV) at this higher threshold ranged from 1.2% over 12 months to 3.8% per case manager year over 1 week. Focusing on the low end of the risk spectrum, the 40% of patients classified as having lowest risk account for 0%-9.7% of suicides across time horizons. Variable importance analysis shows that 51.1% of model performance is due to psychopathological risk factors accounted, 26.2% to social determinants of health, 14.8% to prior history of suicidal behaviors, and 6.6% to physical disorders. The paper closes with a discussion of next steps in refining the model and prospects for developing a parallel precision treatment model.

Intentional research design in implementation science: implications for the use of nomothetic and idiographic assessment.

The advancement of implementation science is dependent on identifying assessment strategies that can address implementation and clinical outcome variables in ways that are valid, relevant to stakeholders, and scalable. This paper presents a measurement agenda for implementation science that integrates the previously disparate assessment traditions of idiographic and nomothetic approaches. Although idiographic and nomothetic approaches are both used in implementation science, a review of the literature on this topic suggests that their selection can be indiscriminate, driven by convenience, and not explicitly tied to research study design. As a result, they are not typically combined deliberately or effectively. Thoughtful integration may simultaneously enhance both the rigor and relevance of assessments across multiple levels within health service systems. Background on nomothetic and idiographic assessment is provided as well as their potential to support research in implementation science. Drawing from an existing framework, seven structures (of various sequencing and weighting options) and five functions (Convergence, Complementarity, Expansion, Development, Sampling) for integrating conceptually distinct research methods are articulated as they apply to the deliberate, design-driven integration of nomothetic and idiographic assessment approaches. Specific examples and practical guidance are provided to inform research consistent with this framework. Selection and integration of idiographic and nomothetic assessments for implementation science research designs can be improved. The current paper argues for the deliberate application of a clear framework to improve the rigor and relevance of contemporary assessment strategies.

A methodology for enhancing implementation science proposals: comparison of face-to-face versus virtual workshops.

BACKGROUND: With the current funding climate and need for advancements in implementation science, there is a growing demand for grantsmanship workshops to increase the quality and rigor of proposals. A group-based implementation science-focused grantsmanship workshop, the Implementation Development Workshop (IDW), is one methodology to address this need. This manuscript provides an overview of the IDW structure, format, and findings regarding its utility. RESULTS: The IDW methodology allows researchers to vet projects in the proposal stage in a structured format with a facilitator and two types of expert participants: presenters and attendees. The presenter uses a one-page handout and verbal presentation to present their proposal and questions. The facilitator elicits feedback from attendees using a format designed to maximize the number of unique points made. After each IDW, participants completed an anonymous survey assessing perceptions of the IDW. Presenters completed a funding survey measuring grant submission and funding success. Qualitative interviews were conducted with a subset of participants who participated in both delivery formats. Mixed method analyses were performed to evaluate the effectiveness and acceptability of the IDW and compare the delivery formats. Of those who participated in an IDW (N = 72), 40 participated in face-to-face only, 16 in virtual only, and 16 in both formats. Thirty-eight (face-to-face n = 12, 35 % response rate; virtual n = 26, 66.7 % response rate) responded to the surveys and seven (15.3 % response rate), who had attended both formats, completed an interview. Of 36 total presenters, 17 (face-to-face n = 12, 42.9 % response rate; virtual n = 5, 62.9 % response rate) responded to the funding survey. Mixed method analyses indicated that the IDW was effective for collaboration and growth, effective for enhancing success in obtaining grants, and acceptable. A third (35.3 %) of presenters ultimately received funding for their proposal, and more than 80 % of those who presented indicated they would present again in the future. The IDW structure and facilitation process were found to be acceptable, with both formats rated as equally strong. CONCLUSIONS: The IDW presents an acceptable and successful methodology for increasing competitiveness of implementation science grant proposals.

It Takes a Village: A Mixed Method Analysis of Inner Setting Variables and Dialectical Behavior Therapy Implementation.

Guided by the Consolidated Framework for Implementation Research, this mixed method study explored the relationship between inner setting variables and dialectical behavior therapy (DBT) implementation. Intensively trained DBT clinicians completed an online quantitative survey (n = 79) and a subset were sequentially interviewed using qualitative methods (n = 20) to identify relationships between inner setting variables and DBT implementation. Four interpersonal variables-team cohesion, team communication, team climate, and supervision-were correlated with the quantity of DBT elements implemented. Qualitative themes corroborated these findings. Additional variables were connected to implementation by either quantitative or qualitative findings, but not both.

Veterans' service utilization and associated costs following participation in dialectical behavior therapy: a preliminary investigation.

CONTEXT: Dialectical Behavior Therapy (DBT) is an evidence-based therapy developed for the treatment of suicidal behaviors and disorders characterized by emotional and behavioral dyscontrol that is effective in veteran populations. The impact of DBT on veterans' Veterans Affairs (VA) service utilization and cost is unknown. EVIDENCE ACQUISITION: This study evaluated the impact of DBT in a VA outpatient mental health setting on VA service utilization and cost of services. Veterans treated for symptoms of Borderline Personality Disorder, who had completed at least 6 months of the DBT program were sampled (N = 41). Use of physical and mental health services during the years prior and following DBT was assessed using medical record information. RESULTS: There was a significant decrease in mental health service utilization. Psychiatric hospitalization dropped in half, and for those with a hospitalization, length of stay decreased significantly. Direct costs associated with all health care were significantly reduced. CONCLUSION: Changes in service utilization resulted in a significant reduction in direct costs of providing care to veterans with symptoms of Borderline Personality Disorder. Additional research is needed to compare the reduction in overall costs to the cost of implementing DBT and to compare these changes to a control group.

Collaborative assessment and management of suicidality (CAMS): feasibility trial for next-day appointment services.

BACKGROUND: Despite the ubiquity of suicidality in behavioral health settings, empirically supported interventions for suicidality are surprisingly rare. Given the importance of resolving suicidality and therapists' anxieties about treating suicidal patients, there is a clear need for innovative services and clinical approaches. The purpose of the current study was an attempt to address some of these needs by examining the feasibility and use of a new intervention called the "Collaborative Assessment and Management of Suicidality" (CAMS) within a "Next-Day Appointment" (NDA) outpatient treatment setting. METHODS: As part of a larger feasibility study, n = 32 suicidal patients were randomly assigned to CAMS care versus Enhanced Care as Usual (E-CAU) in an outpatient crisis intervention setting attached to a safety net hospital. Intent to treat suicidal patients were seen and assessed before, during, and after treatment (with follow-up assessments conducted at 2, 4, 6, and 12 months). RESULTS: The feasibility of using CAMS in the NDA setting was clear; both groups appeared to initially benefit from their respective treatments in terms of decreased suicidal ideation and overall symptom distress. Although patients rated both treatments favorably, the CAMS group had significantly higher satisfaction and better treatment retention than E-CAU. At 12 months post-treatment, CAMS patients showed significantly better and sustained reductions in suicidal ideation, overall symptom distress, and increased hope in comparison to E-CAU patients. CONCLUSIONS: CAMS was both feasible in this NDA setting and effective in treating suicidal ideation, distress, and hopelessness (particularly at 12 months followup).