Introduction Mentorship is an active workplace relationship between a mentor and a mentee, aimed at mutual career advancement, which is vital for both employee growth and organizational success. To improve their mentorship structures and processes, organizations must first assess their current practices. Thus, we developed and conducted a cross-sectional survey to evaluate mentorship among employees at a two-site federally funded health services research center.Methods We surveyed Center investigators and other employees (henceforth "staff"), gathering data on mentors, mentees, mentoring relationships, and satisfaction with the Center's mentoring infrastructure. We used social network analysis to examine both formal and informal mentoring relationships and assessed the association of employee connectedness in these networks with reported satisfaction.Results There were 120 respondents (62.2% response rate). A greater percentage of investigators, compared to staff, had at least one formal mentor (55.8% vs. 25.0%) and one formal mentee (57.7% vs. 10.3%), and investigators had more informal mentors within the Center than staff (4.94 vs. 3.59, p = 0.0485). Investigators reported higher satisfaction with mentorship compared to staff (6.63 vs. 5.25, p = 0.002) and had more formal mentoring relationships with other investigators than staff had with other staff (0.06 vs. 0.01 degree centrality, p < 0.0001). Combining formal and informal mentorship across both investigators and staff, compared to formal mentorship alone, showed fewer degrees of separation (1.32 vs. 3.41 mean distance, p < 0.0001). For the combined formal and informal mentorship network across both investigators and staff, satisfaction with mentoring was associated with having more connections with network members who were connected with each other (r = 0.998, p < 0.0001).Discussion To foster connections among employees, research organizations may create opportunities for open communication and collaborative problem-solving. Our survey and findings are timely given the growing emphasis on mentorship's importance for successful careers, motivated employees, and workplace productivity.

OBJECTIVE:To examine site-level differences in telemental health use within the Department of Veterans Affairs (VA). Findings aim to identify barriers to telemental health use to improve access to care. STUDY SETTING AND DESIGN:122 VA facilities were classified into three groups: sites with higher levels of in-person (n = 55), video (n = 40), and phone mental health (MH) care (n = 27). We used Pearson's chi-squared and F-tests to assess for group differences on organizational characteristics and patient population variables. DATA SOURCES AND ANALYTIC SAMPLE:This was an observational study using VA administrative data from July 2021 to October 2022; analyses were conducted from June 2024 to March 2025. PRINCIPAL FINDINGS:Sites in the video group tended to be larger, high-complexity, urban facilities that served more women, younger patients, and patients with greater broadband access. Sites in the in-person group served more patients of lower socioeconomic status and treated the highest percentage of rural patients. The phone group served the next highest percentage of rural patients, followed by the video group. CONCLUSIONS:Larger, higher-complexity sites may have stronger telehealth infrastructures, and urban areas have stronger broadband connectivity to support video visits. Smaller, rural sites may benefit from targeted support to increase video use.

The Age-Friendly Health System (AFHS) movement has spread widely in recent years, with nearly 5000 healthcare organizations across the country recognized as Age-Friendly. Despite this broad recognition, there is little focus on how AFHS are implemented and the impact of implementation. The objectives of this study were to describe the strategies employed to support AFHS implementation in outpatient settings and to identify the measures used to evaluate implementation and effectiveness. We conducted a systematic review of literature from multiple databases spanning 2015 to March 2024, identified eligible studies using predefined inclusion/exclusion criteria, and extracted key data (eg, study design, study population, implementation strategies, outcomes/measures). We identified ten eligible studies from primary care clinics (N = 8), convenient care clinics (N = 1) and a cancer center (N = 1). The studies employed over 65 implementation strategies and 98 outcomes or measures. The vast majority of measures mapped to components of the 4Ms (Mobility, Mentation, Medication, What Matters), with up to ten measures per M category. Five of ten studies had reporting discrepancies and four did not fully define outcomes. The ten included studies serve as clear examples for the need for more evidence to support AFHS implementation in outpatient settings. Existing research lacks strategy specification and standardization of measures. We present gaps and opportunities to advance from AFHS "recognition" to impact.

The Hospital at Home model, called Hospital-in-Home (HIH) in the Department of Veterans Affairs, delivers coordinated, high-value care aligned with older adult and caregiver preferences. Documenting implementation barriers and corresponding strategies to overcome them can address challenges to widespread adoption. To evaluate HIH implementation barriers and identify strategies to address them, we conducted interviews with 8 HIH staff at 4 hospitals between 2010 and 2013. We utilized qualitative directed content analysis guided by the Consolidated Framework for Implementation Research (CFIR) and mapped identified barriers to possible strategies using the CFIR-Expert Recommendations for Implementing Change (ERIC) Matching Tool. We identified 11 barriers spanning 5 CFIR domains. Three implementation strategies - identifying and preparing champions, conducting educational meetings, and capturing and sharing local knowledge - achieved high expert endorsement for each barrier. A mix of strategies targeting resources, organizational readiness and fit, and leadership engagement should be considered to support the sustainability and spread of HIH.

Background Sustaining evidence-based practices (EBPs) is crucial to ensuring care quality and addressing health disparities. Approaches to identifying factors related to sustainability are critically needed. One such approach is Matrixed Multiple Case Study (MMCS), which identifies factors and their combinations that influence implementation. We applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM) at nine Department of Veterans Affairs (VA) outpatient mental health clinics, 3–4 years after implementation support had concluded. Methods We conducted a directed content analysis of 30 provider interviews, using 6 CCM elements and 4 Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) domains as codes. Based on CCM code summaries, we designated each site as high/medium/low sustainability. We used i-PARIHS code summaries to identify relevant factors for each site, the extent of their presence, and the type of influence they had on sustainability (enabling/neutral/hindering/unclear). We organized these data into a sortable matrix and assessed sustainability-related cross-site trends. Results CCM sustainability status was distributed among the sites, with three sites each being high, medium, and low. Twenty-five factors were identified from the i-PARIHS code summaries, of which 3 exhibited strong trends by sustainability status (relevant i-PARIHS domain in square brackets): “Collaborativeness/Teamwork [Recipients],” “Staff/Leadership turnover [Recipients],” and “Having a consistent/strong internal facilitator [Facilitation]” during and after active implementation. At most high-sustainability sites only, (i) “Having a knowledgeable/helpful external facilitator [Facilitation]” was variably present and enabled sustainability when present, while (ii) “Clarity about what CCM comprises [Innovation],” “Interdisciplinary coordination [Recipients],” and “Adequate clinic space for CCM team members [Context]” were somewhat or less present with mixed influences on sustainability. Conclusions MMCS revealed that CCM sustainability in VA outpatient mental health clinics may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators. These findings have informed a subsequent CCM implementation trial that prospectively examines whether enhancing the above-mentioned factors within implementation facilitation improves sustainability. MMCS is a systematic approach to multi-site examination that can be used to investigate sustainability-related factors applicable to other EBPs and across multiple contexts.

BACKGROUND:The iPRISM webtool is an interactive tool designed to aid the process of applying the Practical, Robust Implementation and Sustainability Model (PRISM) for the assessment of and fit with context. A learning community (LC) is a multidisciplinary group of partners addressing a complex problem. Our LC coproduced the Physical TheraPy frEqueNcy Clinical decIsion support tooL (PT-PENCIL) to guide the use of physical therapist services in acute care hospitals. OBJECTIVE:To describe our LC's activities to co-produce the PT-PENCIL, use of the iPRISM webtool to assess its preimplementation context and fit, and develop a multicomponent implementation strategy for the PT-PENCIL. DESIGN:A descriptive research design. SETTING:Three tertiary care hospitals. PARTICIPANTS:Thirteen LC partners: six clinical physical therapists, three rehabilitation managers, three researchers, and a bioinformaticist. INTERVENTIONS:Not applicable. OUTCOME MEASURES:Using the iPRISM webtool, expected fit of the PT-PENCIL was rated 1 (not aligned) to 6 (well aligned) for each PRISM domain and expected reach, effectiveness, adoption, implementation, and maintenance were rated 1 (not likely at all) to 6 (very likely). Discrete implementation strategies were identified from the Expert Recommendations for Implementing Change. RESULTS:The process spanned 18 meetings over 8 months. Ten LC partners completed the iPRISM webtool. PRISM domains with the lowest expected alignment were the "implementation and sustainability infrastructure" (mean = 4.7 out of 6; range = 3-6) and the "external environment" (mean = 4.9 of 6; range = 4-6). Adoption was the outcome with the lowest expected likelihood (mean = 4.5 out of 6; range = 1-6). Six discrete implementation strategies were identified and combined into a multicomponent strategy. CONCLUSIONS:Within a LC, we used existing implementation science resources to co-produce a novel clinical decision support tool for acute care physical therapists and develop a strategy for its implementation. Our methodology can be replicated for similar projects given the public availability of each resource used.

Abstract Pessimism about aging is ubiquitous and impacts emotional well-being and willingness to implement healthcare strategies with older adults. Individuals experiencing increased stress may be motivated to differentiate themselves from an older, more vulnerable group, which may further intensify pessimistic beliefs. This is particularly important to consider in skilled nursing facilities (SNFs) due to vulnerabilities residents experience. Healthcare environments/approaches can contribute to re-engagement with trauma symptoms, and pessimism about aging are related to trauma symptom endorsement. To explore how expectations about aging may impact staff perceptions of trauma-informed care (TIC), we assessed staff across disciplines (n = 78; nursing, rehabilitation, psychosocial, medical) in a sample of VA SNFs. Staff completed Expectations Regarding Aging (e.g., cognition, physical) and Attitudes Related to Trauma-Informed Care (e.g., beliefs about behavior) questionnaires. Higher total and subscale scores indicate positive expectations of aging and greater TIC endorsement. Expectations of aging differed significantly by discipline (F(3, 65) = 6.79, p <.001, ƞ2 =.24); nurses had lower expectations compared to other disciplines – and a significant difference compared to rehabilitation staff (p =.001; Bonferroni correction). Expectations about aging were not significantly related to overall perceptions of TIC (p =.09). However, staff expectations about cognitive functioning, were positively correlated with TIC attitudes about underlying causes of behavior (r =.25, p =.037), suggesting accurate knowledge about cognitive aging relates to more accurate understanding of resident behavior. This preliminary work suggests beliefs about aging may be related to some but not all aspects of TIC attitudes.

Background Sustaining healthcare interventions once they have been implemented is a pivotal public health endeavor. Achieving sustainability requires context-sensitive adaptations to evidence-based practices (EBPs) or the implementation strategies used to ensure their adoption. For replicability of adaptations beyond the specific setting in question, the underlying logic needs to be clearly described, and adaptations themselves need to be plainly documented. The goal of this project was to describe the process by which implementation facilitation was adapted to improve the uptake of clinical care practices that are consistent with the collaborative chronic care model (CCM). Method Quantitative and qualitative data from a prior implementation trial found that CCM-consistent care practices were not fully sustained within outpatient general mental health teams that had received 1 year of implementation facilitation to support uptake. We undertook a multistep consensus process to identify adaptations to implementation facilitation based on these results, with the goal of enhancing the sustainability of CCM-based care in a subsequent trial. The logic for these adaptations, and the resulting adaptations themselves, were documented using two adaptation-oriented implementation frameworks (the iterative decision-making for evaluation of adaptations [IDEA] and the framework for reporting adaptations and modifications to evidence-based implementation strategies [FRAME-IS], respectively). Results Three adaptations emerged from this process and were documented using the FRAME-IS: (a) increasing the scope of implementation facilitation within the medical center, (b) having the internal facilitator take a greater role in the implementation process, and (c) shortening the implementation timeframe from 12 to 8 months, while increasing the intensity of facilitation support during that time. Conclusions EBP sustainability may require careful adaptation of EBPs or the implementation strategies used to get them into routine practice. Recently developed frameworks such as the IDEA and FRAME-IS may be used to guide decision-making and document resulting adaptations themselves. An ongoing funded study is investigating the utility of the resulting adaptations for improving healthcare.

Background: Patient safety culture (PSC) fosters an environment of trust where people are encouraged to share information to promote psychological safety. To measure PSC, the Veteran's Health Administration (VHA) developed a PSC survey consisting of 20 items administered to all VHA employees. The survey comprises four scales: (1) risk identification engagement. Our objective was to compare the PSC survey data to qualitative data regarding high reliability organization (HRO) implementation from four purposively selected VHA hospitals to assess how it manifests and converges. Methods: Qualitative data focused on understanding HRO implementation efforts were collected from key informants between 2019 and 2020 at 4 of the 18 VHA HRO implementation hospitals. To explore the extent and manifestation of each of the PSC scales among the 4 sites, we combined the qualitative data with the PSC survey data from each hospital using a joint display. Results: Survey responses were significantly different between the 4 hospitals for all 4 PSC scales. Of the 20 PSC survey items, 12 (60.0%) significantly differed across the 4 hospitals. For example, we saw cross-hospital differences in the following sur vey items: "We are given feedback about changes put into place based on event reports" and "We take the time to identify and assess risks to patient safety." Qualitative data supported manifestations for 80.0% (16/20) of PSC individual survey items among hospitals. Conclusion: The authors found that the qualitative data manifestations were well aligned with the VHA PSC scales, but relationships were not always consistent between data sources. Further research is necessary to elucidate these relationships.

Background: As care shifts from institutional to community settings, family caregivers are providing increasing support to older adults, including complex medical/nursing care. In the mid-late pandemic, technology advancements such as use of online patient portals present opportunities for communication and care delivery. This study aims to assess the association between caregiver medical/nursing tasks or patient portal use with contact, communication, and training of caregivers by healthcare providers.Methods: We conducted a cross-sectional analysis of caregiver data from the 2021 National Study of Caregiving (NSOC), linked to the National Health and Aging Trends Study (NHATS). NHATS is nationally-representative, annual survey of Medicare enrollees; NSOC surveys family/unpaid caregivers of NHATS participants. Logistic regression tested association between whether the caregiver does medical/nursing tasks or uses an online patient portal to contact the medical team (independent variables), and communication with or training by the medical team (dependent variables).Results: Participants were 1590 caregivers of living, community-dwelling older adults. More than half (54%) reported no contact with the care recipient's medical team in the past year. Caregivers who did medical/nursing tasks (OR = 3.10; 95% CI: 2.16, 4.46) or who used patient portals (OR = 3.28; 95% CI: 1.96, 5.51) had higher odds of contacting the older adult's medical team. Thirty percent of caregivers stated communication was either not at all or just a little helpful. Sixty-seven percent reported that providers rarely asked if they needed help managing the older adult's treatments. Just 6% of caregivers reported receiving any caregiver training in the last year.Conclusions: Both medical/nursing tasks and online patient portal use were independently associated with contact with health providers. Overall contact, communication, and training were limited or of variable value. Despite recent policy changes and technology advancement, there is still a need for improved integration of caregivers into health teams with ongoing assessment of their needs.

ImportanceClinical outcomes after acute coronary syndromes (ACS) or percutaneous coronary interventions (PCIs) in people living with HIV have not been characterized in sufficient detail, and extant data have not been synthesized adequately.ObjectiveTo better characterize clinical outcomes and postdischarge treatment of patients living with HIV after ACS or PCIs compared with patients in an HIV-negative control group.Data SourcesOvid MEDLINE, Embase, and Web of Science were searched for all available longitudinal studies of patients living with HIV after ACS or PCIs from inception until August 2023.Study SelectionIncluded studies met the following criteria: patients living with HIV and HIV-negative comparator group included, patients presenting with ACS or undergoing PCI included, and longitudinal follow-up data collected after the initial event.Data Extraction and SynthesisData extraction was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Clinical outcome data were pooled using a random-effects model meta-analysis.Main Outcome and MeasuresThe following clinical outcomes were studied: all-cause mortality, major adverse cardiovascular events, cardiovascular death, recurrent ACS, stroke, new heart failure, total lesion revascularization, and total vessel revascularization. The maximally adjusted relative risk (RR) of clinical outcomes on follow-up comparing patients living with HIV with patients in control groups was taken as the main outcome measure.ResultsA total of 15 studies including 9499 patients living with HIV (pooled proportion [range], 76.4% [64.3%-100%] male; pooled mean [range] age, 56.2 [47.0-63.0] years) and 1 531 117 patients without HIV in a control group (pooled proportion [range], 61.7% [59.7%-100%] male; pooled mean [range] age, 67.7 [42.0-69.4] years) were included; both populations were predominantly male, but patients living with HIV were younger by approximately 11 years. Patients living with HIV were also significantly more likely to be current smokers (pooled proportion [range], 59.1% [24.0%-75.0%] smokers vs 42.8% [26.0%-64.1%] smokers) and engage in illicit drug use (pooled proportion [range], 31.2% [2.0%-33.7%] drug use vs 6.8% [0%-11.5%] drug use) and had higher triglyceride (pooled mean [range], 233 [167-268] vs 171 [148-220] mg/dL) and lower high-density lipoprotein-cholesterol (pooled mean [range], 40 [26-43] vs 46 [29-46] mg/dL) levels. Populations with and without HIV were followed up for a pooled mean (range) of 16.2 (3.0-60.8) months and 11.9 (3.0-60.8) months, respectively. On postdischarge follow-up, patients living with HIV had lower prevalence of statin (pooled proportion [range], 53.3% [45.8%-96.1%] vs 59.9% [58.4%-99.0%]) and β-blocker (pooled proportion [range], 54.0% [51.3%-90.0%] vs 60.6% [59.6%-93.6%]) prescriptions compared with those in the control group, but these differences were not statistically significant. There was a significantly increased risk among patients living with HIV vs those without HIV for all-cause mortality (RR, 1.64; 95% CI, 1.32-2.04), major adverse cardiovascular events (RR, 1.11; 95% CI, 1.01-1.22), recurrent ACS (RR, 1.83; 95% CI, 1.12-2.97), and admissions for new heart failure (RR, 3.39; 95% CI, 1.73-6.62).Conclusions and RelevanceThese findings suggest the need for attention toward secondary prevention strategies to address poor outcomes of cardiovascular disease among patients living with HIV.

ObjectiveTo evaluate nationwide implementation of a Guidebook designed to standardize safety practices across VA-delivered and VA-purchased care (i.e., Community Care) and identify lessons learned and strategies to improve them.Data Sources and Study SettingQualitative data collected from key informants at 18 geographically diverse VA facilities across 17 Veterans Integrated Services Networks (VISNs).Study DesignWe conducted semi-structured interviews from 2019 to 2022 with VISN Patient Safety Officers (PSOs) and VA facility patient safety and quality managers (PSMs and QMs) and VA Facility Community Care (CC) staff to assess lessons learned by examining organizational contextual factors affecting Guidebook implementation based on the Consolidated Framework for Implementation Research (CFIR).Data Collection/Extraction MethodsInterviews were conducted virtually with 45 facility staff and 10 VISN PSOs. Using directed content analysis, we identified CFIR factors affecting implementation. These factors were mapped to the Expert Recommendations for Implementing Change (ERIC) strategy compilation to identify lessons learned that could be useful to our operational partners in improving implementation processes. We met frequently with our partners to discuss findings and plan next steps.Principal FindingsSix CFIR constructs were identified as both facilitators and barriers to Guidebook implementation: (1) planning for implementation; (2) engaging key knowledge holders; (3) available resources; (4) networks and communications; (5) culture; and (6) external policies. The two CFIR constructs that were only barriers included: (1) cosmopolitanism and (2) executing implementation.ConclusionsOur findings suggest several important lessons: (1) engage all collaborators involved in implementation; (2) ensure end-users have opportunities to provide feedback; (3) describe collaborators' purpose and roles/responsibilities clearly at the start; (4) communicate information widely and repeatedly; and (5) identify how multiple high priorities can be synergistic. This evaluation will help our partners and key VA leadership to determine next steps and future strategies for improving Guidebook implementation through collaboration with VA staff.

Cognitive impairment due to Alzheimer's disease and related disorders (ADRD) threatens self-management ability when co-occurring with heart failure. ADRD also increases the incremental cost of heart failure care in managed Medicare organizations.1 ICD codes facilitate the identification of persons with ADRD for population health management and observational research. However, multiple ICD-based approaches have developed, and the differences are poorly understood. This study aims to determine the inter-rater reliability between the VA Dementia ICD Code List2 and the Chronic Conditions Warehouse (CCW) ADRD algorithm3 when applied to a cohort of Veterans hospitalized with heart failure. This cross-sectional study used secondary data on a sample of 373,897 Veterans hospitalized in VA medical centers between October 1, 2011, and September 30, 2020, with a primary admission diagnosis of heart failure (see Supplemental Methods). We randomly selected one index admission in Veterans with more than one eligible admission to allow sampling across the clinical course of heart failure. The Median (IQR) number of heart failure admissions per eligible Veteran was 2 (1–3). All study procedures were approved by the IRB at the VA Providence Healthcare System. We applied the VA and CCW algorithms using the same 3-year reference period (see Supplemental Methods). We computed Cohen's kappa coefficient with a 95% confidence interval according to methods previously described.4 We used Pearson's chi-square test to assess independence between algorithm and race. Overall, the cohort included 373 97 Veterans, of whom 364,341 (97%) were male and 74,478 (20%) were Black (Table 1). The CCW code list classified 107,690 (29%) as having ADRD and 266,207 (71%) as not. The VA code list classified 61,796 (17%) as having ADRD and 312,101 (84%) as not. The VA algorithm did not classify any Veterans as having ADRD who were not so classified by the CCW code list. The number of Veterans classified as having ADRD by both the CCW and VA code lists was 61,796 (17%); CCW but not VA, 45894 (12%); neither CCW nor VA, 266207 (71%). The raw percent agreement was 88%. Cohen's kappa coefficient (95% CI) for interrater reliability between the CCW and VA code lists was 0.66 (0.65–0.66), indicating substantial agreement.5 For race, the chi-square test produced a p-value of <0.001, inconsistent with the null hypothesis that algorithm performance is independent of race. The VA algorithm identified a higher proportion of Black Veterans than the CCW algorithm (Table S1). In this study of Veterans with heart failure, ICD-based algorithms estimated ADRD prevalences of 17% and 29%, consistent with the pooled results of 32 prior studies finding a percentage (95% CI) of 20% (13%–28%).6 The inter-rater reliability between the CCW and VA-developed ADRD algorithms was substantially greater than would be expected by random chance. However, the two algorithms classified nearly 1 in 8 Veterans differently. The difference in classification was completely unidirectional: the VA-developed algorithm identified solely Veterans that CCW also identified, whereas CCW classified 74% more Veterans as having ADRD. The composition of these algorithms accounts for their differing patterns of classification. The CCW algorithm differs from the VA algorithm by including several non-specific codes with loose equivalence or association to ADRD (Table 2). VA-only codes, while specific to a narrowly interpreted concept of ADRD, did not measurably alter the algorithm's performance in this sample of Veterans because there were no Veterans with claims containing these codes. The race data demonstrate a small but significant difference in the racial composition between the Veterans identified with the VA and CCW algorithms compared to the CCW algorithm alone, a finding that merits further investigation. This work has several important limitations. We did not compare the coding algorithms to other sources of diagnostic information; therefore, this work does not address the potential problem of underdiagnosis or misdiagnosis of ADRD. This work also does not address the diagnosis of mild cognitive impairment. Our cohort contained only Veterans hospitalized for heart failure, so our observations may not be generalizable to other populations. In Veterans with heart failure, the CCW ADRD algorithm identifies more cases than the VA algorithm due to its inclusion of nonspecific codes with loose equivalence to the ADRD concept. Investigators and health systems desiring tight adherence to the ADRD concept should consider using the VA algorithm. Investigators and health systems who wish to obtain a larger sample inclusive of ADRD and several loosely associated diagnoses should consider using the CCW algorithm. Thomas A. Bayer co-designed the study concept and led the manuscript's production. Lan Jiang performed data management and contributed to the study design. Zachary J. Kunicki co-designed the study and contributed to the production of the manuscript. McKenzie Quinn, Alyssa N. De Vito, and Jennifer L. Sullivan contributed to interpretation of the study results and manuscript production. Catherine M. Kelso and James L. Rudolph contributed to study design, interpretation of results, and manuscript production. The views and opinions expressed do not represent the official policies and protocols of the VA or the United States Government. The authors declare no conflicts of interest. The sponsors had no role in the design of the study or the interpretation of the results. Drs Bayer, Kunicki, Rudolph, and Sullivan and Ms. Jiang are employees of the US Department of Veterans Affairs. Dr. Rudolph, Dr. Sullivan, and Ms. Jiang are funded by the VA Health Services Research and Development Center of Innovation in Long-Term Services and Supports (CIN-13-419), and Dr. Rudolph is funded by the Providence Evidence Synthesis Program (ESP-22-116). Supplemental Text S1. Supplemental methods and results. Table S1. Frequency and percentage of race categories for Veterans with Heart Failure with Alzheimer's Disease or Related Dementia on the Veterans Affairs (VA) and Chronic Conditions Warehouse (CCW) algorithms vs CCW-only. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

BACKGROUND AND OBJECTIVES:Evidence-based practices to manage distress behaviors in dementia (DBD) are not consistently implemented despite demonstrated effectiveness. The Veterans Health Administration (VA) trained teams to implement Staff Training in Assisted Living Residences (STAR)-VA, an intervention to manage DBD in VA nursing home settings, or Community Living Centers (CLCs). This paper summarizes multiyear formative evaluation results including challenges, adaptations, and lessons learned to support sustained integration into usual care across CLCs nationwide. RESEARCH DESIGN AND METHODS:STAR was selected as an evidence-based practice for DBD, adapted for and piloted in VA (STAR-VA), and implemented through a train-the-trainer program from 2013 to 2018. Training and consultation were provided to 92 CLC teams. Evaluation before and after training and consultation included descriptive statistics of measures of clinical impact and survey feedback from site teams regarding self-confidence, engagement, resource quality, and content analysis of implementation facilitators and challenges. RESULTS:STAR-VA training and consultation increased staff confidence and resulted in significant decreases in DBD, depression, anxiety, and agitation for Veterans engaged in the intervention. Implementation outcomes demonstrated feasibility and identified facilitators and barriers. Key findings were interpreted using implementation frameworks and informed subsequent modifications to sustain implementation. DISCUSSION AND IMPLICATIONS:STAR-VA successfully prepared teams to manage DBD and resulted in improved outcomes. Lessons learned include importance of behavioral health-nursing partnerships, continuous engagement, iterative feedback and adaptations, and sustainment planning. Evaluation of sustainment factors has informed selection of implementation strategies to address sustainment barriers. Lessons learned have implications for integrating team-based practices into system-level practice.

Previous studies have shown Relational Coordination improves team functioning in healthcare settings. The aim of this study was to examine the relational factors needed to support team functioning in outpatient mental health care teams with low staffing ratios. We interviewed interdisciplinary mental health teams that had achieved high team functioning despite low staffing ratios in U.S. Department of Veterans Affairs medical centers. We conducted qualitative interviews with 21 interdisciplinary team members across three teams within two medical centers. We used directed content analysis to code the transcripts with a priori codes based on the Relational Coordination dimensions, while also being attentive to emergent themes. We found that all seven dimensions of Relational Coordination were relevant to improved team functioning: frequent communication, timely communication, accurate communication, problem-solving communication, shared goals, shared knowledge, and mutual respect. Participants also described these dimensions as reciprocal processes that influenced each other. In conclusion, relational Coordination dimensions can play pivotal roles in improving team functioning both individually and in combination. Communication dimensions were a catalyst for developing relationship dimensions; once relationships were developed, there was a mutually reinforcing cycle between communication and relationship dimensions. Our results suggest that establishing high-functioning mental health care teams, even in low-staffed settings, requires encouraging frequent communication within teams. Moreover, attention should be given to ensuring appropriate representation of disciplines among leadership and defining roles of team members when teams are formed.

ObjectivesPrevious research has identified the critical role of primary care for suicide prevention. Although several suicide prevention resources for primary care already exist, it is unclear how many have been created specifically for older veterans. This environmental scan sought to assemble a compendium of suicide prevention resources to be utilized in primary care.MethodsWe searched four academic databases, Google Scholar, and Google to identify available suicide prevention resources. Data from 64 resources was extracted and summarized; 15 were general resources and did not meet inclusion criteria.ResultsOur scan identified 49 resources with three resources specifically developed for older veterans in primary care. Identified resources shared overlapping content, including implementing a safety plan and lethal means reduction.ConclusionAlthough only 10 of the identified resources were exclusively primary care focused, many of the resources had content applicable to suicide prevention in primary care.Clinical ImplicationsPrimary care providers can use this compendium of resources to strengthen suicide prevention work within their clinics including: safety planning, lethal means reduction, assessing for risk factors that place older veteran at increased risk of suicide, and mitigating risk factors through referral to programs designed to support older adult health and well-being.