Objective To investigate (a) the magnitude of the independent associations of neighborhood‐level and person‐level social risk factors (SRFs) with quality, (b) whether neighborhood‐level SRF associations may be proxies for person‐level SRF associations, and (c) how the association of person‐level SRFs and quality varies by neighborhood‐level SRFs. Data sources 2015–2016 Medicare Advantage HEDIS data, Medicare beneficiary administrative data, and 2016 American Community Survey (ACS). Study design Mixed effects linear regression models (1) estimated overall inequities by neighborhood‐level and person‐level SRFs, (2) compared neighborhood‐level associations to person‐level associations, and (3) tested the interactions of person‐level SRFs with corresponding neighborhood‐level SRFs. Data collection/extraction methods Beneficiary‐level SES and disability administrative data and five‐year ACS neighborhood‐level SRF information were each linked to HEDIS data. Principal findings For all or nearly all HEDIS measures, quality was worse in neighborhoods lower in SES and in neighborhoods with higher proportions of residents with a disability. Quality by neighborhood racial and ethnic composition was mixed. Accounting for corresponding person‐level SRFs reduced neighborhood SRF associations by 25% for disability, 43% for SES, and 74%–102% for racial and ethnic groups. Person‐level SRF coefficients were not consistently reduced in models that added neighborhood‐level SRFs. In 19 of 35 instances, there were significant (p < 0.05) interactions between neighborhood‐level and corresponding person‐level SRFs. Significant interactions were always positive for disability, SES, Black, and Hispanic, indicating more negative neighborhood effects for people with SRFs that did not match their neighborhood and more positive neighborhood effects for people with SRFs that matched their neighborhood. Conclusions Relying solely on neighborhood‐level SRF models that omit similar person‐level SRFs overattributes inequities to neighborhood characteristics. Neighborhood‐level characteristics account for much less variation in these measures' scores than similar person‐level SRFs. Inequity‐reduction programs may be most effective when targeting neighborhoods with a high proportion of people with a given SRF.

Recent attention to culturally competent care has largely overlooked the needs of older LGB adults. To address this, we conducted a systematic literature review and make recommendations for how the healthcare workforce can reduce sexual-orientation-based disparities. We searched PubMed, PsycINFO & CINAHL for manuscripts 1/1/10-6/19/18 (n=799), deduplicating, dually-screening abstracts (n=80), reviewing full-text articles (n=44), and classifying relevant articles (n=27) into five domains of cultural competency and associated recommendations: 1) Physical environment: display pictures with older same-sex couples and LGB-identified symbols; 2) Education/staffing: expand to include older-specific LGB issues, especially for key conditions (e.g., cancer, dementia,) and hire LGB-identified administrative/clinical staff; 3) Inclusive language and communication: review terminology on forms, electronic health records, and used with patients to ensure a broad range of terms (e.g., partner/spouse) and note older LGB may have more limited understanding/comfort with terminologies (e.g., self-identify as ‘something else’ instead of ‘gay/lesbian’ or ‘bisexual’); 4) Patient histories: discuss how factors particular to their sexual orientation (e.g., level of outness) may affect their support networks; 5) Subgroup differences: consider specific health concerns by sexual minority subgroups (e.g., healthy weight for lesbian women, HIV for gay men, and negative health outcomes for bisexual adults related to their simultaneous isolation from sexual minority and heterosexual communities) and note additional challenges based on characteristics such as race/ethnicity and urbanicity. Cutting across these domains are the ways in which local and national policies affect healthcare access and surrogacy (e.g., legality of same-sex partners to obtain health insurance, participation in medical decision making/visitation).

Study Objective: As recent efforts to improve culturally competent clinical care (CCCC) have largely overlooked older LGB adults, we conducted a scoping review of position statements, empirical, and non-empirical research and suggest action steps. Methods: We followed PRISMA Extension for Scoping Reviews Guidelines and searched for articles 1/1/11-3/14/19 (n = 1210) and other resources (n = 52), deduplicating, dually screening abstracts (n = 1,156), reviewing full-text (n = 107), and conducted a content analysis to identify distinct and cross-cutting domains (n = 44). Main Findings: Most research was based on simple pre/post-training differences in provider knowledge. A majority of sources were non-empirical. We identified three distinct domains (education & staffing, physical environment, and inclusive language & communication) and three cross-cutting domains (subgroup differences, research, and policy). Principal Conclusions: Sparse empirical data that specify best approaches to improve CCCC exist; nevertheless, providers, in collaboration with researchers and policy makers, can initiate improved practices aimed at increasing CCCC for older LGB patients.

Background: Quality improvement (QI) may be aimed at improving care for all patients, or it may be targeted at only certain patient groups. Health care providers have little guidance when determining when targeted QI may be preferred. Objectives: The aim was to develop a method for quantifying performance inconsistency and guidelines for when inconsistency indicates targeted QI, which we apply to the performance of health plans for different patient groups. Research Design and Measures: Retrospective analysis of 7 Health Care Effectiveness Data and Information Set (HEDIS) measures of clinical care quality. Subjects: All Medicare Advantage (MA) beneficiaries eligible for any of 7 HEDIS measures 2015–2018. Results: MA plans with higher overall performance tended to be less inconsistent in their performance (r=−0.2) across groups defined by race-and-ethnicity and low-income status (ie, dual eligibility for Medicaid or receipt of Low-Income Subsidy). Plan characteristics were usually associated with only small differences in inconsistency. The characteristics associated with differences in consistency [eg, size, Health Maintenance Organization (HMO) status] were also associated with differences in overall performance. We identified 9 (of 363) plans that had large inconsistency in performance across groups (>0.8 SD) and investigated the reasons for inconsistency for 2 example plans. Conclusions: This newly developed inconsistency metric may help those designing and evaluating QI efforts to appropriately determine when targeted QI is preferred. It can be used in settings where performance varies across groups, which can be defined by patient characteristics, geographic areas, hospital wards, etc. Effectively targeting QI efforts is essential in today’s resource-constrained health care environment.

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