"I feel like a caged pig in here": Language, Race, and Ethnic Identity in a Case Study Hmong Nursing Home Resident Quality of Life.

Racial disparities in nursing home (NH) quality of life (QOL) are well established, yet, little is understood about actual experiences shaping QOL for Black, indigenous, and people of color (BIPOC) residents in NHs. This gap extends to BIPOC residents with limited English proficiency (LEP). Drawing on Kane's (2001) and Zubristky's (2013) QOL frameworks, this case study examined QOL experiences for Hmong NH residents, an ethnic and refugee group from Southeast Asia, in a NH with a high proportion of BIPOC residents. Methods include four months of observation, interviews with eight Hmong residents and five NH staff, and one community focus group. Thematic analysis revealed significant challenges in QOL. Exacerbated by language barriers and racism, many residents reported neglect, limited relationships, lack of meaningful activities, and dissatisfaction with food. These experiences fostered a sense of resignation and diminished QOL among Hmong residents, highlighting the need for additional supports for this group.

Health and Health Care Use of American Indian/Alaska Native Women Veterans: A Scoping Review.

BACKGROUND: American Indian/Alaska Native (AI/AN) women serve in the U.S. military, use Veterans Health Administration (VA) health care, and reside in rural areas at the highest rates compared with other women veterans. However, little is known about their unique health care needs, access, and health care use. OBJECTIVE: We assessed the existing literature on the health and health care use of U.S. AI/AN women veterans. METHODS: Online databases were searched to identify studies. Study characteristics extracted included health care topic, study design, overall sample size and number of AI/AN women veterans, and funding source. We screened 1,508 publications for inclusion; 28 publications were ultimately retained. RESULTS: Health care access and use were the most common health care research topics (39%), followed by mental health (36%) and physical health (25%). Few studies considered the impact of rurality. Most studies found significant differences between AI/AN women veterans and other women veterans or AI/AN men veterans. Publication dates ranged from 1998 to 2023, with 71% published after 2010. The majority of studies (75%) were secondary analyses of extant health care data. More than three-quarters of studies (82%) were funded federally (e.g., VA). Many studies were based on VA administrative data, resulting in a gap in knowledge regarding AI/AN women veterans who are not eligible for, or choose not to use, VA health care. CONCLUSION: Research to inform the health and health care of AI/AN women veterans is limited, especially in terms of known AI/AN and women veterans' prevalent health concerns (e.g., diabetes, hypertension), women's health and reproduction, and how AI/AN women veterans access, use, and confront barriers to health care. Moreover, there is scarce research specific to cultural, tribal, and regional factors that likely affect access and use of particular health care systems or that can affect perspectives on illness that impact long-term treatment adherence and patient outcomes.

Home health utilization in the Veterans Health Administration: Are there rural and urban differences?

PURPOSE: Growing numbers of older adults need home health care, yhese services may be more difficult to access for rural Veterans, who represent one-third of Veterans Health Administration (VA) enrollees. Our objective was to examine whether home health use differs within VA based on rurality. METHODS: We examined national VA administrative data for 2019-2021 (January 1, 2019 to December 31, 2021) among Veterans ages ≥65 years. Using descriptive and multivariable analyses, we assessed whether rural versus urban Veterans differed in (1) the likelihood of using any home health and (2) for those who received ≥1 visit, number of visits received. RESULTS: Among home health users (n = 107,229, 33.1% rural), rural and urban Veterans were similar in age (77.0 vs. 77.2 years). Rural Veterans were less likely to be highly frail (38.9% rural vs. 40.4% urban) or diagnosed with dementia (13.5% vs. 17.6%). After adjusting for Veterans' characteristics, rural Veterans were more likely to receive any home health (odds ratio: 1.10; 95% confidence interval [CI]: 1.07, 1.13). Among Veterans who received ≥1 home health visit, rurality was associated with considerably fewer expected visits (incident rate ratio: 0.70; 95% CI: 0.68, 0.72). CONCLUSIONS: Although rural Veterans were more likely than urban Veterans to receive any home health services, they received considerably fewer home health visits. This difference may represent an access issue for rural Veterans. Future research is needed to identify reasons for these differences and develop strategies to ensure rural Veterans' care needs are equitability addressed.

Racial and Ethnic and Rural Variations in Access to Primary Care for Veterans Following the MISSION Act.

Importance: The 2018 Veterans Affairs Maintaining Internal Systems and Strengthening Integrated Outside Networks (VA MISSION) Act was implemented to increase timely access to care by expanding veterans' opportunities to receive Veterans Affairs (VA)-purchased care in the community (community care [CC]). Because health equity is a major VA priority, it is important to know whether Black and Hispanic veterans compared with White veterans experienced equitable access to primary care within the VA MISSION Act. Objective: To examine whether utilization of and wait times for primary care differed between Black and Hispanic veterans compared with White veterans in rural and urban areas after the implementation of the VA MISSION Act. Design, Setting, and Participants: This cross-sectional study used VA and CC outpatient and consult data from the VA's Corporate Data Warehouse for fiscal years 2021 to 2022 (October 1, 2020, to September 30, 2022). Separate fixed-effects multivariable models were run to predict CC utilization and wait times. Each model was run twice, once comparing Black and White veterans and then comparing Hispanic and White veterans. Adjusted risk ratios (ARRs) were calculated for Black and Hispanic veterans compared with White veterans within rurality status for both outcomes. Main Outcomes and Measures: VA and CC primary care utilization as measured by primary care visits (utilization cohort); VA and CC primary care access as measured by mean wait times (access cohort). Results: A total of 5 046 087 veterans (994 517 [19.7%] Black, 390 870 [7.7%] Hispanic, and 3 660 700 [72.6%] White individuals) used primary care from fiscal years 2021 to 2022. Utilization increased for all 3 racial and ethnicity groups, more so in CC than VA primary care. ARRs were significantly less than 1 regardless of rurality status, indicating Black and Hispanic veterans compared with White veterans were less likely to utilize CC for primary care. There were 468 246 primary care consultations during the study period. The overall mean (SD) wait time was 33.3 (32.4) days. Despite decreases in wait times over time, primary care wait times remained longer in CC than in VA. Black veterans compared with White veterans had significantly longer wait times in CC (ARRs >1) but significantly shorter wait times in VA (ARRS <1) regardless of rurality status in VA and CC. CC wait times for Hispanic veterans compared with White veterans were longer in rural areas only and in VA rural and urban areas (ARRs >1). Conclusion and Relevance: The results of this cross-sectional study suggest that additional research should explore the determinants and implications of utilization differences among Black and Hispanic veterans compared with White veterans. Efforts to promote equitable primary care access for all veterans are needed so that policy changes can be more effective in ensuring timely access to care for all veterans.

Care Fragmentation, Social Determinants of Health, and Postoperative Mortality in Older Veterans.

INTRODUCTION: Veterans Affairs Surgical Quality Improvement Program (VASQIP) benchmarking algorithms helped the Veterans Health Administration (VHA) reduce postoperative mortality. Despite calls to consider social risk factors, these algorithms do not adjust for social determinants of health (SDoH) or account for services fragmented between the VHA and the private sector. This investigation examines how the addition of SDoH change model performance and quantifies associations between SDoH and 30-d postoperative mortality. METHODS: VASQIP (2013-2019) cohort study in patients ≥65 y old with 2-30-d inpatient stays. VASQIP was linked to other VHA and Medicare/Medicaid data. 30-d postoperative mortality was examined using multivariable logistic regression models, adjusting first for clinical variables, then adding SDoH. RESULTS: In adjusted analyses of 93,644 inpatient cases (97.7% male, 79.7% non-Hispanic White), higher proportions of non-veterans affairs care (adjusted odds ratio [aOR] = 1.02, 95% CI = 1.01-1.04) and living in highly deprived areas (aOR = 1.15, 95% CI = 1.02-1.29) were associated with increased postoperative mortality. Black race (aOR = 0.77, CI = 0.68-0.88) and rurality (aOR = 0.87, CI = 0.79-0.96) were associated with lower postoperative mortality. Adding SDoH to models with only clinical variables did not improve discrimination (c = 0.836 versus c = 0.835). CONCLUSIONS: Postoperative mortality is worse among Veterans receiving more health care outside the VA and living in highly deprived neighborhoods. However, adjusting for SDoH is unlikely to improve existing mortality-benchmarking models. Reduction efforts for postoperative mortality could focus on alleviating care fragmentation and designing care pathways that consider area deprivation. The adjusted survival advantage for rural and Black Veterans may be of interest to private sector hospitals as they attempt to alleviate enduring health-care disparities.

Social Determinants of Long-Term Opioid Use Following Total Knee Arthroplasty.

Total knee arthroplasty (TKA) risks persistent pain and long-term opioid use (LTO). The role of social determinants of health (SDoH) in LTO is not well established. We hypothesized that SDoH would be associated with postsurgical LTO after controlling for relevant demographic and clinical variables. This study utilized data from the Veterans Affairs Surgical Quality Improvement Program, VA Corporate Data Warehouse, and Centers for Medicare and Medicaid Services, including Veterans aged ≥ 65 who underwent elective TKA between 2013 and 2019 with no postsurgical complications or history of significant opioid use. LTO was defined as > 90 days of opioid use beginning within 90 days postsurgery. SDoH variables included the Area Deprivation Index, rurality, and housing instability in the last 12 months identified via medical record screener or International Classification of Diseases, Tenth Revision codes. Multivariable risk adjustment models controlled for demographic and clinical characteristics. Of the 9,064 Veterans, 97% were male, 84.2% white, mean age was 70.6 years, 46.3% rural, 11.2% living in highly deprived areas, and 0.9% with a history of homelessness/housing instability. Only 3.7% (n = 336) developed LTO following TKA. In a logistic regression model of only SDoH variables, housing instability (odds ratio [OR] = 2.38, 95% confidence interval [CI]: 1.09-5.22) and rurality conferred significant risk for LTO. After adjusting for demographic and clinical variables, LTO was only associated with increasing days of opioid supply in the year prior to surgery (OR = 1.52, 95% CI: 1.43-1.63 per 30 days) and the initial opioid fill (OR = 1.07; 95% CI: 1.06-1.08 per day). Our primary hypothesis was not supported; however, our findings do suggest that patients with housing instability may present unique challenges for postoperative pain management and be at higher risk for LTO.

Quality Improvement Efforts in VA Community Living Centers Following Public Reporting of Performance.

For two decades, the U.S. government has publicly reported performance measures for most nursing homes, spurring some improvements in quality. Public reporting is new, however, to Department of Veterans Affairs nursing homes (Community Living Centers [CLCs]). As part of a large, public integrated healthcare system, CLCs operate with unique financial and market incentives. Thus, their responses to public reporting may differ from private sector nursing homes. In three CLCs with varied public ratings, we used an exploratory, qualitative case study approach involving semi-structured interviews to compare how CLC leaders (n = 12) perceived public reporting and its influence on quality improvement. Across CLCs, respondents said public reporting was helpful for transparency and to provide an "outside perspective" on CLC performance. Respondents described employing similar strategies to improve their public ratings: using data, engaging staff, and clearly defining staff roles vis-à-vis quality improvement, although more effort was required to implement change in lower performing CLCs. Our findings augment those from prior studies and offer new insights into the potential for public reporting to spur quality improvement in public nursing homes and those that are part of integrated healthcare systems.

National Survey of the Bone Densitometry Evaluation Process Within an Integrated Healthcare System.

BACKGROUND: To assess the current state of bone mineral density evaluation services via dual energy x-ray absorptiometry (DXA) provided to Veterans with fracture risk through the development and administration of a nationwide survey of facilities in the Veterans Health Administration. METHODOLOGY: The Bone Densitometry Survey was developed by convening a Work Group of individuals with expertise in bone densitometry and engaging the Work Group in an iterative drafting and revision process. Once completed, the survey was beta tested, administered through REDCap, and sent via e-mail to points of contact at 178 VHA facilities. RESULTS: Facility response rate was 31 % (56/178). Most DXA centers reported positively to markers of readiness for their bone densitometers: less than 10 years old (n=35; 63 %); in "excellent" or "good" condition (n=44; 78 %, 32 % and 46 %, respectively); and perform phantom calibration (n=43; 77 %). Forty-one DXA centers (73 %) use intake processes that have been shown to reduce errors. Thirty-seven DXA centers (66 %) reported their technologists receive specialized training in DXA, while 14 (25 %) indicated they receive accredited training. Seventeen DXA centers (30 %) reported performing routine precision assessment. CONCLUSIONS: Many DXA centers reported using practices that meet minimal standards for DXA reporting and preparation; however, the lack of standardization, even within an integrated healthcare system, indicates an opportunity for quality improvement to ensure consistent high quality bone mineral density evaluation of Veterans.

The epidemiology of mild cognitive impairment, Alzheimer's disease and related dementia in U.S. veterans.

INTRODUCTION: US veterans have a unique dementia risk profile that may be evolving over time. METHODS: Age-standardized incidence and prevalence of Alzheimer's disease (AD), AD and related dementias (ADRD), and mild cognitive impairment (MCI) was estimated from electronic health records (EHR) data for all veterans aged 50 years and older receiving Veterans Health Administration (VHA) care from 2000 to 2019. RESULTS: The annual prevalence and incidence of AD declined, as did ADRD incidence. ADRD prevalence increased from 1.07% in 2000 to 1.50% in 2019, primarily due to an increase in the prevalence of dementia not otherwise specified. The prevalence and incidence of MCI increased sharply, especially after 2010. The prevalence and incidence of AD, ADRD, and MCI were highest in the oldest veterans, in female veterans, and in African American and Hispanic veterans. DISCUSSION: We observed 20-year trends of declining prevalence and incidence of AD, increasing prevalence of ADRD, and sharply increasing prevalence and incidence of MCI.

Using the Kitagawa Decomposition to Measure Overall-and Individual Facility Contributions to-Within-facility and Between-facility Differences: Analyzing Racial and Ethnic Wait Time Disparities in the Veterans Health Administration.

BACKGROUND: Identifying whether differences in health care disparities are due to within-facility or between-facility differences is key to disparity reductions. The Kitagawa decomposition divides the difference between 2 means into within-facility differences and between-facility differences that are measured on the same scale as the original disparity. It also enables the identification of facilities that contribute most to within-facility differences (based on facility-level disparities and the proportion of patient population served) and between-facility differences. OBJECTIVES: Illustrate the value of a 2-stage Kitagawa decomposition to partition a disparity into within-facility and between-facility differences and to measure the contribution of individual facilities to each type of difference. SUBJECTS: Veterans receiving a new outpatient consult for cardiology or orthopedic services during fiscal years 2019-2021. MEASURES: Wait time for a new-patient consult. METHODS: In stage 1, we predicted wait time for each Veteran from a multivariable model; in stage 2, we aggregated individual predictions to determine mean adjusted wait times for Hispanic, Black, and White Veterans and then decomposed differences in wait times between White Veterans and each of the other groups. RESULTS: Noticeably longer wait times were experienced by Hispanic Veterans for cardiology (2.32 d, 6.8% longer) and Black Veterans for orthopedics (3.49 d, 10.3% longer) in both cases due entirely to within-facility differences. The results for Hispanic Veterans using orthopedics illustrate how positive within-facility differences (0.57 d) can be offset by negative between-facility differences (-0.34 d), resulting in a smaller overall disparity (0.23 d). Selecting 10 facilities for interventions in orthopedics based on the largest contributions to within-in facility differences instead of the largest disparities resulted in a higher percentage of Veterans impacted (31% and 12% of Black and White Veterans, respectively, versus 9% and 10% of Black and White Veterans, respectively) and explained 21% of the overall within-facility difference versus 11%. CONCLUSIONS: The Kitagawa approach allows the identification of disparities that might otherwise be undetected. It also allows the targeting of interventions at those facilities where improvements will have the largest impact on the overall disparity.

Disparities in Wait Times for Care Among US Veterans by Race and Ethnicity.

Importance: Prior studies indicate that Black and Hispanic vs White veterans wait longer for care. However, these studies do not capture the COVID-19 pandemic, which caused care access disruptions, nor implementation of the US Department of Veterans Affairs (VA) Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION), which is intended to improve care access by increasing veterans' options to use community clinicians. Objective: To determine whether wait times increased differentially for Black and Hispanic compared with White veterans from the pre-COVID-19 to COVID-19 periods given concurrent MISSION implementation. Design, Setting, and Participants: This cross-sectional study used data from the VA's Corporate Data Warehouse for fiscal years 2019 to 2021 (October 1, 2018, to September 30, 2021). Participants included Black, Hispanic, and White veterans with a new consultation for outpatient cardiology and/or orthopedic services during the study period. Multivariable mixed-effects models were used to estimate individual-level adjusted wait times and a likelihood ratio test of the significance of wait time disparity change over time. Main Outcomes and Measures: Overall mean wait times and facility-level adjusted relative mean wait time ratios. Results: The study included 1 162 148 veterans (mean [SD] age, 63.4 [14.4] years; 80.8% men). Significant wait time disparities were evident for orthopedic services (eg, Black veterans had wait times 2.09 [95% CI, 1.57-2.61] days longer than those for White veterans) in the pre-COVID-19 period, but not for cardiology services. Mean wait times increased from the pre-COVID-19 to COVID-19 periods for both services for all 3 racial and ethnic groups (eg, Hispanic wait times for cardiology services increased 5.09 [95% CI, 3.62-6.55] days). Wait time disparities for Black veterans (4.10 [95% CI, 2.44-5.19] days) and Hispanic veterans (4.40 [95% CI, 2.76-6.05] days) vs White veterans (3.75 [95% CI, 2.30-5.19] days) increased significantly from the pre-COVID-19 to COVID-19 periods (P < .001). During the COVID-19 period, significant disparities were evident for orthopedic services (eg, mean wait times for Hispanic vs White veterans were 1.98 [95% CI, 1.32-2.64] days longer) but not for cardiology services. Although there was variation in wait time ratios across the 140 facilities, only 6 facility wait time ratios were significant during the pre-COVID-19 period and 26 during the COVID-19 period. Conclusions and Relevance: These findings suggest that wait time disparities increased from the pre-COVID-19 to COVID-19 periods, especially for orthopedic services for both Black and Hispanic veterans, despite MISSION's goal to improve access. Facility-level analyses identified potential sites that could be targeted to reduce disparities.

A Citation Review of 83 Dissemination and Implementation Theories, Models, or Frameworks Utilized in U.S.-Based Aging Research.

BACKGROUND AND OBJECTIVES: Dissemination-implementation.org outlines 110 theories, models, and frameworks (TMFs): we conducted a citation analysis on 83 TMFs, searching Web of Science and PubMed databases. RESEARCH DESIGN AND METHODS: Search terms were broad and included "aging," "older," "elderly," and "geriatric." We extracted each TMF in identified articles from inception through January 28, 2022. Included articles must have used a TMF in research or quality improvement work directly linked to older adults within the United States. RESULTS: We reviewed 2,681 articles of which 295 articles cited at least one of 56 TMFs. Five TMFs represented 50% of the citations: Reach, Effectiveness, Adoption, Implementation, and Maintenance 1.0, Consolidated Framework for Implementation Research, Greenhalgh Diffusion of Innovation in Service Organizations, Quality Enhancement Research Initiative, Community-Based Participatory Research, and Promoting Action on Research Implementation in Health Services. TMF application varied and there was a steady increase in TMF citations over time, with a 2- to 3-fold increase in citations in 2020-2021. We identified that only 41% of TMF use was meaningful. DISCUSSION AND IMPLICATIONS: Our results suggest TMF utilization is increasing in aging research, but there is a need to more meaningful utilize TMFs. As the population of older adults continues to grow, there will be increasing demand for effective evidence-based practices and models of care to be quickly and effectively translated into routine care. Use of TMFs is critical to building such evidence and to identifying and evaluating methods to support this translation.

Evidence to Inform Policy and Practice: Mechanisms to Address Racial/Ethnic Disparities in Nursing Home Quality of Life.

Background and Objectives: Abundant evidence documents racial/ethnic disparities in access, quality of care, and quality of life (QoL) among nursing home (NH) residents who are Black, Indigenous, and people of color (BIPOC) compared with White residents. BIPOC residents are more likely to be admitted to lower quality NHs and to experience worse outcomes. Yet, little is known about processes for differences in QoL among residents receiving care in high-proportion BIPOC NHs. This study presents an examination of the processes for racial/ethnic disparities in QoL in high-proportion BIPOC facilities while highlighting variability in QoL between these facilities. Research Design and Methods: Guided by the Minority Health and Health Disparities Research Framework and the Zubritsky framework for QoL in NHs, we employ a concurrent mixed-methods approach involving in-depth case studies of 6 high-proportion BIPOC NHs in Minnesota (96 resident interviews; 61 staff interviews; 614 hours of observation), coupled with statewide survey data on residents' QoL linked to resident clinical Minimum Data Set assessments. Results: Quantitative findings show that BIPOC residents experience lower QoL than White residents across various domains. Qualitative findings reveal variability in BIPOC residents' QoL between high-proportion BIPOC facilities. In some facilities, BIPOC residents experienced worse QoL based on their race/ethnicity, whereas in others BIPOC residents QoL was not directly affected by their race/ethnicity or they had mixed experiences. Discussion and Implications: The findings highlight variability in racial/ethnic disparities in QoL across NHs with a high proportion of BIPOC residents. We identify health equity initiatives, including engaging with community BIPOC organizations and volunteers, and providing more resources to high-proportion BIPOC facilities to support staff training, additional staffing, and culturally specific programming. Given the increasing racial/ethnic diversity of NHs, ensuring equity in QoL for BIPOC residents is an urgent priority for NHs to remain relevant in the future.

Why Men Fare Worse: A Mixed-Methods Study Examining Gender Differences in Nursing Home Resident Quality of Life.

BACKGROUND AND OBJECTIVES: Despite research documenting gender differences in numerous outcomes in later life, we know little about gender differences in quality of life (QoL) for nursing home (NH) residents. This study examines the relationship between gender and residents' QoL, including possible reasons for differences observed. RESEARCH DESIGN AND METHODS: We used a mixed-methods design including surveys with a random sample of Minnesota NH residents using a multidimensional measure of QoL (n = 9,852), resident clinical data, facility-level characteristics (n = 364), interviews with residents (n = 64), and participant observations. We used linear mixed models and thematic analysis of resident interviews and observations to examine possible gender-related differences in residents' QoL. RESULTS: After controlling for individual and facility characteristics, men reported lower overall QoL than women, including significantly lower ratings in several QoL domains. In interviews, men noted being less satisfied with activities than women, having fewer friends, and being less able to rely on family for support. Some women described the NH as a place of respite, but men more often described being dissatisfied with life in the NH and undesirable for long-term living. Our observations were consistent with interview findings but provide additional nuances, such as that some men organized their own social groups. DISCUSSION AND IMPLICATIONS: Our findings suggest that men and women experience QoL differently in NHs, with men reporting lower QoL in several domains. Tailoring more activities for men and finding ways to strengthen relationships for men in NHs could help reduce the gender differences in QoL we observed.

Supporting Veterans with dementia to remain in the community: strategies used in 12 Veterans Health Administration programs.

The Veterans Health Administration (VA) provides services to growing numbers of Veterans with dementIa, individuals at heightened risk for hospitalizations and nursing home placement. Beginning in 2010, the VA funded 12 innovative pilot programs to improve dementia care and help Veterans remain at home. We conducted a retrospective qualitative analysis of program materials and interviews with physicians, nurses, social workers, and other personnel (n = 33) to understand the strategies these programs adopted. Interviews were conducted every 6 months between 2010-2013 (4-5 interviews per program) and focused on factors affecting program design and implementation, challenges, and strategies to reduce hospitalizations and nursing home placements. Programs varied considerably yet shared three overarching strategies to improve dementia care: involving and supporting family caregivers; engaging interdisciplinary teams; and improving coordination with other healthcare providers. Our results highlight the importance of adapting common dementia care strategies based on the local context and needs of individuals served.

The Quality Measures Domain in Nursing Home Compare: Is High Performance Meaningful or Misleading?

BACKGROUND AND OBJECTIVES: The reported percent of nursing home residents suffering adverse outcomes decreased dramatically since Nursing Home Compare began reporting them, but the validity of scores is questionable for nursing homes that score well on measures using facility-reported data but poorly on inspections. Our objective was to assess whether nursing homes with these "discordant" scores are meaningfully better than nursing homes that score poorly across domains. RESEARCH DESIGN AND METHODS: We used a convergent mixed-methods design, starting with quantitative analyses of 2012-2016 national data. We conducted in-depth interviews and observations in 12 nursing homes in 2017-2018, focusing on how facilities achieved their Nursing Home Compare ratings. Additional quantitative analyses were conducted in parallel to study performance trajectories over time. Quantitative and qualitative results were interpreted together. RESULTS: Discordant facilities engage in more quality improvement strategies than poor performers, but do not seem to invest in quality improvement in resource-intensive, broad-based ways that would spill over into other domains of quality and change their trajectory of improvement. Instead, they focus on lower-resource improvements related to data quality, staff training, leadership, and communication. In contrast, poor-performing facilities seemed to lack the leadership and continuity of staff required for even these low-resource interventions. DISCUSSION AND IMPLICATIONS: High performance on the quality measures using facility-reported data is mostly meaningful rather than misleading to consumers who care about those outcomes, although discordant facilities still have quality deficits. The quality measures domain should continue to have a role in Nursing Home Compare.

Maximizing Well-Being in the Context of Long-Term Services and Supports: A Q Methodological Approach.

OBJECTIVES: The goal of this study was to investigate diversity in stakeholders' perspectives on how best to maximize older adults' well-being when they use long-term services and supports (LTSS). METHODS: We used Q methodology, an exploratory method, to investigate preference patterns among a purposive sample of older adults, family members, and leadership professionals (n = 57). Participants categorized 52 items related to 9 domains of LTSS quality relevant to well-being into categories of importance. We used factors analysis and qualitative methods to identify groups of individuals who identified similar priorities. RESULTS: The analysis identified four shared viewpoints, each prioritizing different aspects of well-being: 1) physical health and safety; 2) independence; 3) emotional well-being; and 4) social engagement. Individual and contextual factors, including stakeholder role, care needs, and expectations for LTSS, appeared to influence participants' perspectives. CONCLUSIONS: Distinct viewpoints on how to maximize well-being when older adults use LTSS exist. Our results affirm the importance of person-centered care yet demonstrate that shared preference patterns LTSS exist. CLINICAL IMPLICATIONS: Engaging with older adults' values and preferences is critical to improving their experiences with LTSS. Better understanding common preference patterns could help providers deliver person-centered care more efficiently and effectively.

Health Care Providers and the Public Reporting of Nursing Home Quality in the United States Department of Veterans Affairs: Protocol for a Mixed Methods Pilot Study.

BACKGROUND: In June 2018, the United States Department of Veterans Affairs (VA) began the public reporting of its 134 Community Living Centers' (CLCs) overall quality by using a 5-star rating system based on data from the national quality measures captured in CLC Compare. Given the private sector's positive experience with report cards, this is a seminal moment for stimulating measurable quality improvements in CLCs. However, the public reporting of CLC Compare data raises substantial and immediate implications for CLCs. The report cards, for example, facilitate comparisons between CLCs and community nursing homes in which CLCs generally fare worse. This may lead to staff anxiety and potentially unintended consequences. Additionally, CLC Compare is designed to spur improvement, yet the motivating aspects of the report cards are unknown. Understanding staff attitudes and early responses is a critical first step in building the capacity for public reporting to spur quality. OBJECTIVE: We will adapt an existing community nursing home public reporting survey to reveal important leverage points and support CLCs' quality improvement efforts. Our work will be grounded in a conceptual framework of strategic orientation. We have 2 aims. First, we will qualitatively examine CLC staff reactions to CLC Compare. Second, we will adapt and expand upon an extant community nursing home survey to capture a broad range of responses and then pilot the adapted survey in CLCs. METHODS: We will conduct interviews with staff at 3 CLCs (1 1-star CLC, 1 3-star CLC, and 1 5-star CLC) to identify staff actions taken in response to their CLCs' public data; staff's commitment to or difficulties with using CLC Compare; and factors that motivate staff to improve CLC quality. We will integrate these findings with our conceptual framework to adapt and expand a community nursing home survey to the current CLC environment. We will conduct cognitive interviews with staff in 1 CLC to refine survey items. We will then pilot the survey in 6 CLCs (2 1-star CLCs, 2 3-star CLCs, and 2 5-star CLCs) to assess the survey's feasibility, acceptability, and preliminary psychometric properties. RESULTS: We will develop a brief survey for use in a future national administration to identify system-wide responses to CLC Compare; evaluate the impact of CLC Compare on veterans' clinical outcomes and satisfaction; and develop, test, and disseminate interventions to support the meaningful use of CLC Compare for quality improvement. CONCLUSIONS: The knowledge gained from this pilot study and from future work will help VA refine how CLC Compare is used, ensure that CLC staff understand and are motivated to use its quality data, and implement concrete actions to improve clinical quality. The products from this pilot study will also facilitate studies on the effects of public reporting in other critical VA clinical areas. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23516.

Did Access to Care Improve Since Passage of the Veterans Choice Act?: Differences Between Rural and Urban Veterans.

BACKGROUND: The 2014 Veterans Choice Program aimed to improve care access for Veterans through expanded availability of community care (CC). Increased access to CC could particularly benefit rural Veterans, who often face obstacles in obtaining medical care at the Veterans Health Administration (VHA). However, whether Veterans Choice Program improved timely access to care for this vulnerable population is understudied. OBJECTIVES: To examine wait times among rural and urban Veterans for 5 outpatient specialty care services representing the top requests for CC services among rural Veterans. RESEARCH DESIGN: Retrospective study using VHA and CC outpatient consult data from VHA's Corporate Data Warehouse in Fiscal Year (FY) 2015 (October 1, 2014 to September 30, 2015) and FY2018 (October 1, 2017 to September 30, 2018). SUBJECTS: All Veterans who received a new patient consult for physical therapy, cardiology, optometry, orthopedics, and/or dental services in VHA and/or CC. MEASURES: Wait time, care setting (VHA/CC), rural/urban status, sociodemographics, and comorbidities. RESULTS: Our sample included 1,112,876 Veterans. Between FY2015 and FY2018, mean wait times decreased for all services for both rural and urban Veterans; declines were greatest in VHA (eg, mean optometry wait times for rural Veterans in VHA vs. CC declined 8.3 vs. 6.4 d, respectively, P<0.0001). By FY2018, for both rural and urban Veterans, CC mean wait times for most services were longer than VHA wait times. CONCLUSIONS: Timely care access for all Veterans improved between FY15 and FY18, particularly in VHA. As expansion of CC continues under the MISSION Act, more research is needed to evaluate quality of care across VHA and CC and what role, if any, wait times play.