Implementing a Social Needs Screening and Referral Program Among Veterans: Assessing Circumstances & Offering Resources for Needs (ACORN).

BACKGROUND: The Department of Veterans Affairs (VA) healthcare system routinely screens Veterans for food insecurity, housing instability, and intimate partner violence, but does not systematically screen for other health-related social needs (HRSNs). OBJECTIVES: To (1) develop a process for systematically identifying and addressing Veterans' HRSNs, (2) determine reported prevalence of HRSNs, and (3) assess the acceptability of HRSN screening among Veterans. DESIGN: "Assessing Circumstances and Offering Resources for Needs" (ACORN) is a Veteran-tailored HRSN screening and referral quality improvement initiative. Veterans were screened via electronic tablet for nine HRSNs (food, housing, utilities, transportation, legal needs, social isolation, interpersonal violence, employment, and education) and provided geographically tailored resource guides for identified needs. Two-week follow-up interviews with a purposive sample of Veterans explored screening experiences. PARTICIPANTS: Convenience sample of Veterans presenting for primary care at a VA urban women's health clinic and suburban community-based outpatient clinic (October 2019-May 2020). MAIN MEASURES: Primary outcomes included prevalence of HRSNs, Veteran-reported acceptability of screening, and use of resources guides. Data were analyzed using descriptive statistics, chi-square tests, and rapid qualitative analysis. KEY RESULTS: Of 268 Veterans screened, 50% reported one or more HRSNs. Social isolation was endorsed most frequently (29%), followed by educational needs (19%), interpersonal violence (12%), housing instability (9%), and utility concerns (7%). One in five Veterans reported at least one form of material hardship. In follow-up interviews (n = 15), Veterans found screening acceptable and felt VA should continue screening. No Veterans interviewed had contacted recommended resources at two-week follow-up, although several planned to use resource guides in the future. CONCLUSION: In a VA HRSN screening and referral program, Veterans frequently reported HRSNs, felt screening was important, and thought VA should continue to screen for these needs. Screening for HRSNs is a critical step towards connecting patients with services, identifying gaps in service delivery, and informing future resource allocation.

Incorporating TechQuity in Virtual Care Within the Veterans Health Administration: Identifying Future Research and Operations Priorities.

BACKGROUND: The Covid-19 pandemic dramatically changed healthcare delivery, driving rapid expansion of synchronous (i.e., real-time) audio-only and video telehealth, otherwise known as virtual care. Yet evidence describes significant inequities in virtual care utilization, with certain populations more dependent on audio-only virtual care than video-based care. Research is needed to inform virtual care policies and processes to counteract current inequities in access and health outcomes. OBJECTIVE: Given the importance of incorporating equity into virtual care within the Veterans Health Administration (VHA), we convened a Think Tank to identify priorities for future research and virtual care operations focused on achieving equitable implementation of virtual care within the VHA. METHODS: We used participatory activities to engage clinicians, researchers, and operational partners from across the VHA to develop priorities for equitable implementation of virtual care. We refined priorities through group discussion and force-ranked prioritization and outlined next steps for selected priorities. KEY RESULTS: Think Tank participants included 43 individuals from the VHA who represented diverse geographical regions, offices, and backgrounds. Attendees self-identified their associations primarily as operations (n = 9), research (n = 28), or both (n = 6). We identified an initial list of 63 potential priorities for future research and virtual care operations. Following discussion, we narrowed the list to four priority areas: (1) measure inequities in virtual care, (2) address emerging inequities in virtual care, (3) deploy virtual care equitably to accommodate differently abled veterans, and (4) measure and address potential adverse consequences of expanded virtual care. We discuss related information, data, key partners, and outline potential next steps. CONCLUSIONS: This Think Tank of research and operational partners from across the VHA identified promising opportunities to incorporate equity into the design and implementation of virtual care. Although much work remains, the priorities identified represent important steps toward achieving this vital goal.

Racial Disparities in Sepsis-Related In-Hospital Mortality: Using a Broad Case Capture Method and Multivariate Controls for Clinical and Hospital Variables, 2004-2013.

OBJECTIVES: As sepsis hospitalizations have increased, in-hospital sepsis deaths have declined. However, reported rates may remain higher among racial/ethnic minorities. Most previous studies have adjusted primarily for age and sex. The effect of other patient and hospital characteristics on disparities in sepsis mortality is not yet well-known. Furthermore, coding practices in claims data may influence findings. The objective of this study was to use a broad method of capturing sepsis cases to estimate 2004-2013 trends in risk-adjusted in-hospital sepsis mortality rates by race/ethnicity to inform efforts to reduce disparities in sepsis deaths. DESIGN: Retrospective, repeated cross-sectional study. SETTING: Acute care hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases for 18 states with consistent race/ethnicity reporting. PATIENTS: Patients diagnosed with septicemia, sepsis, organ dysfunction plus infection, severe sepsis, or septic shock. MEASUREMENTS AND MAIN RESULTS: In-hospital sepsis mortality rates adjusted for patient and hospital factors by race/ethnicity were calculated. From 2004 to 2013, sepsis hospitalizations for all racial/ethnic groups increased, and mortality rates decreased by 5-7% annually. Mortality rates adjusted for patient characteristics were higher for all minority groups than for white patients. After adjusting for hospital characteristics, sepsis mortality rates in 2013 were similar for white (92.0 per 1,000 sepsis hospitalizations), black (94.0), and Hispanic (93.5) patients but remained elevated for Asian/Pacific Islander (106.4) and "other" (104.7; p < 0.001) racial/ethnic patients. CONCLUSIONS: Our results indicate that hospital characteristics contribute to higher rates of sepsis mortality for blacks and Hispanics. These findings underscore the importance of ensuring that improved sepsis identification and management is implemented across all hospitals, especially those serving diverse populations.

Managed care and inpatient mortality in adults: effect of primary payer.

BACKGROUND: Because managed care is increasingly prevalent in health care finance and delivery, it is important to ascertain its effects on health care quality relative to that of fee-for-service plans. Some stakeholders are concerned that basing gatekeeping, provider selection, and utilization management on cost may lower quality of care. To date, research on this topic has been inconclusive, largely because of variation in research methods and covariates. Patient age has been the only consistently evaluated outcome predictor. This study provides a comprehensive assessment of the association between managed care and inpatient mortality for Medicare and privately insured patients. METHODS: A cross-sectional design was used to examine the association between managed care and inpatient mortality for four common inpatient conditions. Data from the 2009 Healthcare Cost and Utilization Project State Inpatient Databases for 11 states were linked to data from the American Hospital Association Annual Survey Database. Hospital discharges were categorized as managed care or fee for service. A phased approach to multivariate logistic modeling examined the likelihood of inpatient mortality when adjusting for individual patient and hospital characteristics and for county fixed effects. RESULTS: Results showed different effects of managed care for Medicare and privately insured patients. Privately insured patients in managed care had an advantage over their fee-for-service counterparts in inpatient mortality for acute myocardial infarction, stroke, pneumonia, and congestive heart failure; no such advantage was found for the Medicare managed care population. To the extent that the study showed a protective effect of privately insured managed care, it was driven by individuals aged 65 years and older, who had consistently better outcomes than their non-managed care counterparts. CONCLUSIONS: Privately insured patients in managed care plans, especially older adults, had better outcomes than those in fee-for-service plans. Patients in Medicare managed care had outcomes similar to those in Medicare FFS. Additional research is needed to understand the role of patient selection, hospital quality, and differences among county populations in the decreased odds of inpatient mortality among patients in private managed care and to determine why this result does not hold for Medicare.

Length of stay in EDs: variation across classifications of clinical condition and patient discharge disposition.

STUDY OBJECTIVE: Duration of a stay in an emergency department (ED) is considered a measure of quality, but current measures average lengths of stay across all conditions. Previous research on ED length of stay has been limited to a single condition or a few hospitals. We use a census of one state's data to measure length of ED stays by patients' conditions and dispositions and explore differences between means and medians as quality metrics. METHODS: The data source was the Healthcare Cost and Utilization Project 2011 State Emergency Department Databases and State Inpatient Databases for Florida. Florida is unique in collecting ED length of stay for both released and admitted patients. Clinical Classifications Software was used to group visits based on first-listed International Classification of Disease, Ninth Edition, Clinical Modification, diagnoses. RESULTS: For the 10 most common diagnoses, patients with relatively minor injuries typically required the shortest mean stay (3 hours or less); conditions resulting in admission or transfer tended to be more serious, resulting in longer stays. Patients requiring the longest stays, by disposition, had discharge diagnoses of nonspecific chest pain (mean 7.4 hours among discharged patients), urinary tract infections (4.8 hours among admissions), and schizophrenia (9.6 hours among transfers) among the top 10 diagnoses. CONCLUSION: Emergency department length of stay as a measure of ED quality should take into account the considerable variation by condition and disposition of the patient. Emergency department length of stay measurement could be improved in the United States by standardizing its definition; distinguishing visits involving treatment, observation, and boarding; and incorporating more distributional information.

The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study.

BACKGROUND: The presence of multiple chronic conditions (MCCs) complicates inpatient hospital care, leading to higher costs and utilization. Multimorbidity also complicates primary care, increasing the likelihood of hospitalization for ambulatory care sensitive conditions. The purpose of this study was to evaluate how MCCs relate to inpatient hospitalization costs and utilization for ambulatory care sensitive conditions. METHODS: The 2012 Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) provided data to carry out a cross-sectional analysis of 1.43 million claims related to potentially preventable hospitalizations classified by the AHRQ Prevention Quality Indicator (PQI) composites. Categories of MCCs (0-1, 2-3, 4-5, and 6+) were examined in sets of acute, chronic, and overall PQIs. Multivariate models determined associations between categories of MCCs and 1) inpatient costs per stay, 2) inpatient costs per day, and 3) length of inpatient hospitalization. Negative binomial was used to model costs per stay and costs per day. RESULTS: The most common category observed was 2 or 3 chronic conditions (37.8 % of patients), followed by 4 or 5 chronic conditions (30.1 % of patients) and by 6+ chronic conditions (10.1 %). Compared with costs for patients with 0 or 1 chronic condition, hospitalization costs per stay for overall ambulatory care sensitive conditions were 19 % higher for those with 2 or 3 (95 % confidence interval [CI] 1.19-1.20), 32 % higher for those with 4 or 5 (95 % CI 1.31-1.32), and 31 % higher (95 % CI 1.30-3.32) for those with 6+ conditions. Acute condition stays were 11 % longer when 2 or 3 chronic conditions were present (95 % CI 1.11-1.12), 21 % longer when 4 or 5 were present (95 % CI 1.20-1.22), and 27 % longer when 6+ were present (95 % CI 1.26-1.28) compared with those with 0 or 1 chronic condition. Similar results were seen within chronic conditions. Associations between MCCs and total costs were driven by longer stays among those with more chronic conditions rather than by higher costs per day. CONCLUSIONS: The presence of MCCs increased inpatient costs for ambulatory care sensitive conditions via longer hospital stays.

Racial differences in hospital mortality for medical and surgical admissions: variations by patient and hospital characteristics.

OBJECTIVE: To determine if there are disparities between White and Black inpatient mortality rates for specific medical and surgical conditions and whether disparities vary by patient and hospital subgroups. DESIGN, SETTING, PARTICIPANTS: All-payer discharge records in the 2009 Healthcare Cost and Utilization Project, State Inpatient Databases (SID) for 36 states that comprised about 80% of the Black and White populations in the United States were used to create a random, stratified sample of about 1,900 community hospitals (a 40% sample of US hospitals). All discharges in the hospitals were included and weighted for national estimates. MAIN OUTCOME MEASURES: Inpatient Quality Indicators, developed by the Agency for Healthcare Research and Quality, were used to measure risk-adjusted hospital mortality for six medical conditions and four surgeries. National estimates compared non-Hispanic Whites to Blacks by patient and hospital characteristics. RESULTS: Blacks had lower mortality for all medical conditions compared to Whites. However, they had higher mortality rates for two surgical procedures (coronary artery bypass graft and craniotomy) and lower mortality for one surgery (abdominal aortic anuerysm repair). These patterns held for most, though not all, patient and hospital subgroups for medical conditions, but disparities typically varied by subgroup for surgeries. CONCLUSIONS: Policymakers and researchers may use these findings in targeting interventions, designing quality reporting programs and designing studies on why the disparities exist and how to reduce them.

Differences by Sexual Orientation in Patient-Centered Care Outcomes for Veterans Utilizing Primary Care Services at the Veterans Health Administration.

Purpose: This study examined the differences by sexual orientation in patient-centered care outcomes (including health care experiences and health-related screening) of veterans utilizing Veterans Health Administration (VHA) primary care. Methods: VHA's adapted version of the Consumer Assessment of Healthcare Providers and Systems was used to compare the health care experience of primary care services among sexual minority (SM) and heterosexual veterans. Health care experience measures were dichotomized to "always" versus "less" and stratified by SM status. Health-related screening measures were dichotomous. Survey data were weighted using provided sample weights. Descriptive statistics were performed on sociodemographic characteristics. Logistic regression coefficients were represented as adjusted odds ratios (aORs). A total of 66,348 veterans were included in the analytic sample, of which 2.9% (n = 1,935) identified as SM. Sexual orientation was ascertained by self-report measures by veterans. Results: SM veterans were significantly younger (56.95 years vs. 63.43 years, p < 0.001), were less likely to report that their provider showed respect for what they had to say (aOR: 0.76; 95% confidence interval [CI]: 0.61-0.95), that they were asked about difficulties taking care of their health (aOR: 0.81; 95% CI: 0.67-0.96), and their provider listened carefully to them (aOR: 0.71; 95% CI: 0.57-0.87) compared to heterosexual veterans. Conclusion: Health care experiences differed between SM and heterosexual veterans who sought VHA primary care, suggesting the need to increase provider trainings, which may improve cultural competency and promote a more welcoming and inclusive environment.

Evaluation of regional variation in racial and ethnic differences in patient experience among Veterans Health Administration primary care users.

OBJECTIVE: To evaluate racial and ethnic differences in patient experience among VA primary care users at the Veterans Integrated Service Network (VISN) level. DATA SOURCE AND STUDY SETTING: We performed a secondary analysis of the VA Survey of Healthcare Experiences of Patients-Patient Centered Medical Home for fiscal years 2016-2019. STUDY DESIGN: We compared 28 patient experience measures (six each in the domains of access and care coordination, 16 in the domain of person-centered care) between minoritized racial and ethnic groups (American Indian or Alaska Native [AIAN], Asian, Black, Hispanic, Multi-Race, Native Hawaiian or Other Pacific Islander [NHOPI]) and White Veterans. We used weighted logistic regression to test differences between minoritized and White Veterans, controlling for age and gender. DATA COLLECTION/EXTRACTION METHODS: We defined meaningful difference as both statistically significant at two-tailed p < 0.05 with a relative difference ≥10% or ≤-10%. Within VISNs, we included tests of group differences with adequate power to detect meaningful relative differences from a minimum of five comparisons (domain agnostic) per VISN, and separately for a minimum of two for access and care coordination and four for person-centered care domains. We report differences as disparities/large disparities (relative difference ≥10%/≥ 25%), advantages (experience worse or better, respectively, than White patients), or equivalence. PRINCIPAL FINDINGS: Our analytic sample included 1,038,212 Veterans (0.6% AIAN, 1.4% Asian, 16.9% Black, 7.4% Hispanic, 0.8% Multi-Race, 0.8% NHOPI, 67.7% White). Across VISNs, the greatest proportion of comparisons indicated disparities for three of seven eligible VISNs for AIAN, 6/10 for Asian, 3/4 for Multi-Race, and 2/6 for NHOPI Veterans. The plurality of comparisons indicated advantages or equivalence for 17/18 eligible VISNs for Black and 12/14 for Hispanic Veterans. AIAN, Asian, Multi-Race, and NHOPI groups had more comparisons indicating disparities by VISN in the access domain than person-centered care and care coordination. CONCLUSIONS: We found meaningful differences in patient experience measures across VISNs for minoritized compared to White groups, especially for groups with lower population representation.

Relationship between health system quality and racial and ethnic equity in diabetes care.

Failing to consider disparities in quality measures, such as by race and ethnicity, may obscure inequities in care, which could exist in facilities with overall high-quality ratings. We examined the relationship between overall quality and racial and ethnic disparities in diabetes care quality by health care facility-level performance on a diabetes-related quality measure within a national dataset of veterans using Veterans Health Administration (VA) ambulatory care between March 1, 2020 and Feburary 28, 2021, and were eligible for diabetes quality assessment. We found racial and ethnic disparities in diabetes care quality existed in top-performing VA medical centers (VAMCs) among American Indian or Alaska Native (AIAN) (predicted probability = 30%), Black (predicted probability = 29%), and Hispanic VA-users (predicted probability = 30%) vs White VA-users (predicted probability = 26%). While disparities among Black and Hispanic VA-users were similar relative to White VA-users across VAMCs at all performance levels, disparities were exacerbated for AIAN and Native Hawaiian or Other Pacific Islander VA-users in bottom-performing VAMCs. Equity remains an issue even in facilities providing overall high-quality care. Integrating equity as a component of quality measures can incentivize greater focus on equity in quality improvement.

Assessing equity in the uptake of remote foot temperature monitoring in a large integrated US healthcare system.

OBJECTIVE: We assessed equity in the uptake of remote foot temperature monitoring (RTM) for amputation prevention throughout a large, integrated US healthcare system between 2019 and 2021, including comparisons across facilities and between patients enrolled and eligible patients not enrolled in RTM focusing on the Reach and Adoption dimensions of the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. MATERIAL AND METHODS: To assess whether there was equitable use of RTM across facilities, we examined distributions of patient demographic, geographic, and facility characteristics across facility RTM use categories (e.g., no RTM use, and low, moderate, and high RTM use) among all eligible patients (n = 46,294). Second, to understand whether, among facilities using RTM, there was equitable enrollment of patients in RTM, we compared characteristics of patients enrolled in RTM (n = 1066) relative to a group of eligible patients not enrolled in RTM (n = 27,166) using logistic regression and including all covariates. RESULTS: RTM use increased substantially from an average of 11 patients per month to over 40 patients per month between 2019 and 2021. High-use RTM facilities had higher complexity and a lower ratio of patients per podiatrist but did not have consistent evidence of better footcare process measures. Among facilities offering RTM, enrollment varied by age, was inversely associated with Black race (vs. white), low income, living far from specialty care, and being in the highest quartiles of telehealth use prior to enrollment. Enrollment was positively associated with having osteomyelitis, Charcot foot, a partial foot amputation, BMI≥30 kg/m2, and high outpatient utilization. CONCLUSIONS: RTM growth was concentrated in a small number of higher-resourced facilities, with evidence of lower enrollment among those who were Black and lived farther from specialty care. Future studies are needed to identify and address barriers to uptake of new interventions like RTM to prevent exacerbating existing ulceration and amputation disparities.

Addressing Veteran Health-Related Social Needs: How Joint Commission Standards Accelerated Integration and Expansion of Tools and Services in the Veterans Health Administration.

BACKGROUND: The Joint Commission recently named reduction of health care disparities and improvement of health care equity as quality and safety priorities (Leadership [LD] Standard LD.04.03.08 and National Patient Safety Goal [NPSG] Standard NPSG.16.01.01). As the largest integrated health system, the Veterans Health Administration (VHA) sought to leverage these new accreditation standards to further integrate and expand existing tools and initiatives to reduce health care disparities and address health-related social needs (HRSNs). INITIATIVES AND TOOLS: A combination of existing data tools (for example, Primary Care Equity Dashboard), resource tools (for example, Assessing Circumstances and Offering Resources for Needs tool), and a care delivery approach (for example, Whole Health) are discussed as quality improvement opportunities to further integrate and expand how VHA addresses health care disparities and HRSNs. The authors detail the development timeline, building, limitations, and future plans for these tools and initiatives. COORDINATION OF INITIATIVES: Responding to new health care equity Joint Commission standards led to new implementation strategies and deeper partnerships across VHA that facilitated expanded dissemination, technical assistance activities, and additional resources for VHA facilities to meet new standards and improve health care equity for veterans. Health care systems may learn from VHA's experiences, which include building actionable data platforms, employing user-centered design for initiative development and iteration, designing wide-reaching dissemination strategies for tools, and recognizing the importance of providing technical assistance for stakeholders. FUTURE DIRECTIONS: VHA continues to expand implementation of a diverse set of tools and resources to reduce health care disparities and identify and address unmet individual veteran HRSNs more widely and effectively.

Building Tailored Resource Guides to Address Social Risks and Advance Health Equity in the Veterans Health Administration.

Background: Health care organizations, including the Veterans Health Administration (VHA), are increasingly adopting programs to address social determinants of health. As part of a comprehensive social risk screening and referral model, tailored resource guides can support efforts to address unmet social needs. However, limited guidance is available on best practices for the development of resource guides in health care settings. Observations: This article describes the development of geographically tailored resource guides for a national VHA quality improvement initiative, Assessing Circumstances and Offering Resources for Needs (ACORN), which aims to systematically screen for and address social needs among veterans. We outline the rationale for using resource guides as a social needs intervention and provide a pragmatic framework for resource guide development and maintenance. We offer guidance based on lessons learned from the development of ACORN resource guides, emphasizing a collaborative approach with VHA social workers and other frontline clinical staff, as well as with community-based organizations. Our how-to guide provides steps for identifying high-yield resources along with formatting considerations to maximize accessibility and usability among patients. Conclusions: Resource guides can serve as a valuable cross-cutting component of health care organizations' efforts to address social needs. We provide a practical approach to resource guide development that may support successful implementation within the VHA and other clinical settings.

"You want people to listen to you": Patient experiences of women's healthcare within the Veterans Health Administration.

OBJECTIVE: To identify constructs that are critical in shaping Veterans' experiences with Veterans Health Administration (VA) women's healthcare, including any which have been underexplored or are not included in current VA surveys of patient experience. DATA SOURCES AND STUDY SETTING: From June 2022 to January 2023, we conducted 28 semi-structured interviews with a diverse, national sample of Veterans who use VA women's healthcare. STUDY DESIGN: Using VA data, we divided Veteran VA-users identified as female into four groups stratified by age (dichotomized at age 45) and race/ethnicity (non-Hispanic White vs. all other). We enrolled Veterans continuously from each recruitment strata until thematic saturation was reached. DATA COLLECTION/EXTRACTION METHODS: For this qualitative study, we asked Veterans about past VA healthcare experiences. Interview questions were guided by a priori domains identified from review of the literature, including trust, safety, respect, privacy, communication and discrimination. Analysis occurred concurrently with interviews, using inductive and deductive content analysis. PRINCIPAL FINDINGS: We identified five themes influencing Veterans' experiences of VA women's healthcare: feeling valued and supported, bodily autonomy, discrimination, past military experiences and trauma, and accessible care. Each emergent theme was associated with multiple of the a priori domains we asked about in the interview guide. CONCLUSIONS: Our findings underscore the need for a measure of patient experience tailored to VA women's healthcare. Existing patient experience measures used within VA fail to address several aspects of experience highlighted by our study, including bodily autonomy, the influence of past military experiences and trauma on healthcare, and discrimination. Understanding distinct factors that influence women and gender-diverse Veterans' experiences with VA care is critical to advance efforts by VA to measure and improve the quality and equity of care for all Veterans.

Ethnic differences in potentially preventable hospitalizations among Asian Americans, Native Hawaiians, and other Pacific Islanders: implications for reducing health care disparities.

OBJECTIVES: A serious challenge to eliminating US health disparities stems from the inability to reliably measure outcomes, particularly for numerically small populations. Our study aimed to produce reliable estimates of health care quality among Native Hawaiian (NH), Other Pacific Islander (PI), and Asian American (AA) subgroups. DESIGN: Prevention Quality Indicators (PQIs) from the Agency for Healthcare Research and Quality were used to calculate 3 PQI composites and 8 individual chronic condition indicators. Data sources were the Healthcare Cost and Utilization Project State Inpatient Databases and the Hawaii Health Survey. MAIN OUTCOME MEASURES: Risk-adjusted PQI rates for adults were computed for 2005 through 2007. Relative rates for 2007 were calculated for each racial/ethnic group and compared to Whites. Statistical significance was based on P < .05 from a two-sided t test. RESULTS: The combined AANHPI group had higher overall and chronic PQI composite rates than Whites in 2007. When disaggregated into discrete racial/ethnic subgroups, Chinese and Japanese had lower rates than Whites for all 3 composites, whereas NH and Other PI subgroups typically had the worst health outcomes. Trends in PQI rates from 2005 through 2007 showed persistent gaps between groups, especially across chronic PQIs. CONCLUSIONS: Despite recent efforts to reduce racial/ethnic health care disparities, significant gaps remain in potentially preventable hospitalization rates. Practical tools that measure inequities across diverse, numerically small populations may suggest ways to optimally funnel limited resources toward improving racial/ethnic differences in health outcomes.

Influenza and Pneumococcal Vaccination Among Male Veterans and Nonveterans, 2016-2018.

OBJECTIVES: The Advisory Committee on Immunization Practices recommends persons aged ≥6 months receive an influenza vaccination annually, and certain adults aged ≥19 years receive the 23-valent pneumococcal polysaccharide vaccine alone or in series with the 13-valent pneumococcal conjugate vaccine, depending on age, chronic conditions, and smoking status. This study examines the prevalence of influenza and pneumococcal vaccination relative to Healthy People 2020 goals to understand how vaccination receipt differs by veteran status and sociodemographic subgroups. METHODS: We analyzed pooled data from the 2016-2018 National Health Interview Survey (N = 35 094) in 2021 to estimate the prevalence of influenza and pneumococcal vaccination for men aged 25-64 years and for men aged ≥65 years by veteran status and selected sociodemographic subgroups. We used 2-tailed t tests with an α = .05 to identify significant differences. RESULTS: Among men, 44.7% of veterans and 33.5% of nonveterans aged 25-64 years and 71.0% of veterans and 64.9% of nonveterans aged ≥65 years received an influenza vaccine in the past year. Among men aged 25-64 years at high risk for pneumococcal disease, 35.9% of veterans and 20.8% of nonveterans had ever received ≥1 dose of any pneumococcal vaccination. Disparities in the prevalence of vaccination within examined sociodemographic characteristics were often smaller in magnitude among veterans than among nonveterans for both vaccinations. CONCLUSIONS: Vaccination rates were below Healthy People 2020 targets for both groups, except influenza vaccination among veterans aged ≥65 years. Understanding differences in vaccine uptake may inform efforts to improve vaccination rates by identifying subgroups who are at high risk of disease and have low vaccination rates.

VA Research and Operations Uniting to Combat COVID-19 Inequities.

As novel coronavirus 2019 disease (COVID-19) began to spread across the United States in early 2020, health care systems faced extreme demands on resources. As the country's largest single-payer health care system, the U.S. Department of Veterans Affairs (VA) was uniquely positioned to study how the virus impacted different communities and work to improve care provided to all. Early on, a literature review of prior epidemics revealed that occupational exposures and an inability to socially distance could impact some groups more than others. The VA's Office of Health Equity leveraged a general sense of community to create a collaborative research space and a dedicated analytic space to inform pandemic operations. VA researchers and operations staff were able to quickly share information and respond to updates to produce accurate and reliable publications for medical professionals and the general public. Partnerships with VA Medical Centers and Veteran Service Organizations helped to increase communication across the nation and determine the most critical needs. Although COVID-19 was dynamic in nature, VA's intentional examination of social and structural factors was crucial in informing a more equitable approach. Moving forward, these inequities must be intentionally addressed in future pandemic responses.

Developing a brief assessment of social risks for the Veterans Health Administration Survey of Healthcare Experiences of Patients.

OBJECTIVE: To determine whether a 6- or 12-month look-back period affected rates of reported social risks in a social risk survey for use in the Veterans Health Administration and to assess associations of social risks with overall health and mental health. STUDY DESIGN: Cross-sectional survey of respondents randomized to 6- or 12-month look-back period. DATA SOURCES AND STUDY SETTING: Online survey with a convenience sample of Veterans in June and July 2021. DATA COLLECTION/EXTRACTION METHODS: Veteran volunteers were recruited by email to complete a survey assessing social risks, including financial strain, adult caregiving, childcare, food insecurity, housing, transportation, internet access, loneliness/isolation, stress, discrimination, and legal issues. Outcomes included self-reported overall health and mental health. Chi-squared tests compared the prevalence of reported social risks between 6- and 12-month look-back periods. Spearman correlations assessed associations among social risks. Bivariate and multivariable logistic regression models estimated associations between social risks and fair/poor overall and mental health. PRINCIPAL FINDINGS: Of 3418 Veterans contacted, 1063 (31.10%) responded (87.11% male; 85.61% non-Hispanic White; median age = 70, interquartile range [IQR] = 61-74). Prevalence of most reported social risks did not significantly differ by look-back period. Most social risks were weakly intercorrelated (median |r| = 0.24, IQR = 0.16-0.31). Except for legal issues, all social risks were associated with higher odds of fair/poor overall health and mental health in bivariate models. In models containing all significant social risks from bivariate models, adult caregiving and stress remained significant predictors of overall health; food insecurity, housing, loneliness/isolation, and stress remained significant for mental health. CONCLUSIONS: Six- and 12-month look-back periods yielded similar rates of reported social risks. Although most individual social risks are associated with fair/poor overall and mental health, when examined together, only adult caregiving, stress, loneliness/isolation, food, and housing remain significant.

Assessing an electronic self-report method for improving quality of ethnicity and race data in the Veterans Health Administration.

Objective: Evaluate self-reported electronic screening (eScreening) in a VA Transition Care Management Program (TCM) to improve the accuracy and completeness of administrative ethnicity and race data. Materials and Methods: We compared missing, declined, and complete (neither missing nor declined) rates between (1) TCM-eScreening (ethnicity and race entered into electronic tablet directly by patient using eScreening), (2) TCM-EHR (Veteran-completed paper form plus interview, data entered by staff), and (3) Standard-EHR (multiple processes, data entered by staff). The TCM-eScreening (n = 7113) and TCM-EHR groups (n = 7113) included post-9/11 Veterans. Standard-EHR Veterans included all non-TCM Gulf War and post-9/11 Veterans at VA San Diego (n = 92 921). Results: Ethnicity: TCM-eScreening had lower rates of missingness than TCM-EHR and Standard-EHR (3.0% vs 5.3% and 8.6%, respectively, P < .05), but higher rates of "decline to answer" (7% vs 0.5% and 1.2%, P < .05). TCM-EHR had higher data completeness than TCM-eScreening and Standard-EHR (94.2% vs 90% and 90.2%, respectively, P < .05). Race: No differences between TCM-eScreening and TCM-EHR for missingness (3.5% vs 3.4%, P > .05) or data completeness (89.9% vs 91%, P > .05). Both had better data completeness than Standard-EHR (P < .05), which despite the lowest rate of "decline to answer" (3%) had the highest missingness (10.3%) and lowest overall completeness (86.6%). There was strong agreement between TCM-eScreening and TCM-EHR for ethnicity (Kappa = .92) and for Asian, Black, and White Veteran race (Kappas = .87 to .97), but lower agreement for American Indian/Alaska Native (Kappa = .59) and Native Hawaiian/Other Pacific Islander (Kappa = .50) Veterans. Conculsions: eScreening is a promising method for improving ethnicity and race data accuracy and completeness in VA.