Assessing the accuracy of race-and-ethnicity data in the Outcome and Assessment Information Set.

BACKGROUND: Limitations in the quality of race-and-ethnicity information in Medicare's data systems constrain efforts to assess disparities in care among older Americans. Using demographic information from standardized patient assessments may be an efficient way to enhance the accuracy and completeness of race-and-ethnicity information in Medicare's data systems, but it is critical to first establish the accuracy of these data as they may be prone to inaccurate observer-reported or third-party-based information. This study evaluates the accuracy of patient-level race-and-ethnicity information included in the Outcome and Assessment Information Set (OASIS) submitted by home health agencies. METHODS: We compared 2017-2022 OASIS-D race-and-ethnicity data to gold-standard self-reported information from the Medicare Consumer Assessment of Healthcare Providers and Systems® survey in a matched sample of 304,804 people with Medicare coverage. We also compared OASIS data to indirect estimates of race-and-ethnicity generated using the Medicare Bayesian Improved Surname and Geocoding (MBISG) 2.1.1 method and to existing Centers for Medicare & Medicaid Services (CMS) administrative records. RESULTS: Compared with existing CMS administrative data, OASIS data are far more accurate for Hispanic, Asian American and Native Hawaiian or other Pacific Islander, and White race-and-ethnicity; slightly less accurate for American Indian or Alaska Native race-and-ethnicity; and similarly accurate for Black race-and-ethnicity. However, MBISG 2.1.1 accuracy exceeds that of both OASIS and CMS administrative data for every racial-and-ethnic category. Patterns of inconsistent reporting of racial-and-ethnic information among people for whom there were multiple observations in the OASIS and Consumer Assessment of Healthcare Providers and Systems (CAHPS) datasets suggest that some of the inaccuracies in OASIS data may result from observation-based reporting that lessens correspondence with self-reported data. CONCLUSIONS: When health record data on race-and-ethnicity includes observer-reported information, it can be less accurate than both true self-report and a high-performing imputation approach. Efforts are needed to encourage collection of true self-reported data and explicit record-level data on the source of race-and-ethnicity information.

Do Hospital Characteristics Predict Racial-and-Ethnic Disparities in Patient Experience? National Results From the HCAHPS Survey.

OBJECTIVE: Assess whether hospital characteristics associated with better patient experiences overall are also associated with smaller racial-and-ethnic disparities in inpatient experience. BACKGROUND: Hospitals that are smaller, non-profit, and serve high proportions of White patients tend to be high-performing overall, but it is not known whether these hospitals also have smaller racial-and-ethnic disparities in care. RESEARCH DESIGN: We used linear mixed-effect regression models to predict a summary measure that averaged eight Hospital CAHPS (HCAHPS) measures (Nurse Communication, Doctor Communication, Staff Responsiveness, Communication about Medicines, Discharge Information, Care Coordination, Hospital Cleanliness, and Quietness) from patient race-and-ethnicity, hospital characteristics (size, ownership, racial-and-ethnic patient-mix), and interactions of race-and-ethnicity with hospital characteristics. SUBJECTS: Inpatients discharged from 4,365 hospitals in 2021 who completed an HCAHPS survey ( N =2,288,862). RESULTS: While hospitals serving larger proportions of Black and Hispanic patients scored lower on all measures, racial-and-ethnic disparities were generally smaller for Black and Hispanic patients who received care from hospitals serving higher proportions of patients in their racial-and-ethnic group. Experiences overall were better in smaller and non-profit hospitals, but racial-and-ethnic differences were slightly larger. CONCLUSIONS: Large, for-profit hospitals and hospitals serving higher proportions of Black and Hispanic patients tend to be lower performing overall but have smaller disparities in patient experience. High-performing hospitals might look at low-performing hospitals for how to provide less disparate care whereas low-performing hospitals may look to high-performing hospitals for how to improve patient experience overall.

Patient Comments on the Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) Survey Reflect Improvements in Provider Behaviors From Coaching.

GOAL: Patient experience survey data are used to examine the patient-centeredness of care, identify areas for improvement, and monitor interventions aimed to enhance the patient experience. Most healthcare organizations measure patient experience using Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys. Studies have documented the use of CAHPS closed-ended survey responses for completing public reports, monitoring internal feedback and performance, identifying areas of improvement, and evaluating interventions to improve care. However, limited evidence exists on the utility of patients' comments on CAHPS surveys for evaluating provider-level interventions. To explore this potential, we examined comments on the CAHPS Clinician and Group (CG-CAHPS) 2.0 visit survey before and after a provider intervention. The "shadow coaching" intervention had been shown to improve provider performance and patient experience scores on the CG-CAHPS overall provider rating and provider communication composite. METHODS: We examined how patient comments on the CG-CAHPS survey differed before and after shadow coaching of 74 providers. We described the valence (tone), content, and actionability of 1,935 comments-1,051 collected before coaching and 884 collected after coaching-to see how these aspects changed before and after providers were coached. PRINCIPAL FINDINGS: Patient comments reflected improved CG-CAHPS scores after shadow coaching. The proportion of positive comments increased, and comments about doctors were more positive. Comments about time spent in the examination room decreased, apparently reflecting the decreased proportion of negative comments after coaching. Comments regarding three of the four aspects of provider communication asked on the CG-CAHPS survey were more positive after coaching (provider listens carefully, shows respect, spends enough time); the valence of comments about the fourth aspect (provider explains things in a way that is easy to understand) did not change. Also, comments describing an overall positive evaluation of the practice increased. Comments were generally less actionable after coaching, perhaps reflecting the increased positivity of the comments. PRACTICAL APPLICATIONS: Patient comments collected before the provider intervention reflected overall improvements in provider behavior, as indicated by medium-to-large statistically significant improvements in CG-CAHPS composite scores. These results suggest that patient comments from the CG-CAHPS survey can be used as input for quality improvement or an evaluation of provider-level interventions. Tracking the valence and content of comments about providers before and after an intervention to improve care is a practical method to learn how provider behavior changes.

Development of a Medicare plan dashboard to promote health equity.

OBJECTIVE: To describe a multistage process of designing and evaluating a dashboard that presents data on how equitably health plans provide care for their members. STUDY DESIGN: We designed a dashboard for presenting summative and finer-grained data to health plans for characterizing how well plans are serving individuals who belong to racial/ethnic minority groups and individuals with low income. The data presented in the dashboard were based on CMS' Health Equity Summary Score (HESS) for Medicare Advantage plans. METHODS: Interviews and listening sessions were conducted with health plan representatives and other stakeholders to assess understanding, perceived usefulness, and interpretability of HESS data. Usability testing was conducted with individuals familiar with quality measurement and reporting to evaluate dashboard design efficiency. RESULTS: Listening session participants understood the purpose of the HESS and expressed a desire for this type of information. Usability testing revealed a need to improve dashboard navigability and to streamline content. CONCLUSIONS: The HESS dashboard is a potentially useful tool for presenting data on health equity to health plans. The multistage process of continual testing and improvement used to develop the dashboard could be a model for targeting and deciding upon quality improvement efforts in the domain of health equity.

Measuring Equity in the Hospital Setting: An HCAHPS Application of the Health Equity Summary Score.

BACKGROUND: Health care quality varies by patient factors, including race-and-ethnicity and preferred language. Addressing inequities requires identifying them and incentivizing equity. OBJECTIVES: We apply an approach first implemented in the Medicare Advantage setting to measure equity in patient experiences by race-and-ethnicity [Asian American and Native Hawaiian or Pacific Islander (AA and NHPI), Black, Hispanic, vs. White] and language preference (English-preferring vs. another-language-preferring). We identify characteristics of hospitals providing high-quality equitable care. RESEARCH DESIGN: We estimated, standardized, and combined performance measures into a Health Equity Summary Score (HESS) using 2016-2019 Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey data. The HCAHPS HESS considered current cross-sectional performance, within-hospital improvement, and overall improvement by race-and-ethnicity and language preference. SUBJECTS: A total of 3333 US hospitals with 2019 HCAHPS Star Ratings. RESULTS: The HCAHPS HESS was calculable for 44% of hospitals. High-scoring (4-5 diamonds on a 1-diamond to 5-diamond scale) hospitals tended to be smaller than intermediate-scoring [3 diamonds (14% of high-scoring hospitals had <100 beds vs. 7% of intermediate-scoring hospitals, P <0.001) and were less often for-profit (20% vs. 31%, P <0.001)]. While a significant percentage (29%) of patients served by high-scoring hospitals were AA and NHPI, Black, or Hispanic, and 9% were another-language-preferring, there were smaller proportions of Black and Hispanic patients in high-scoring versus other hospitals. HESS performance was negatively associated with the percentage of patients preferring another language to English. HESS scores were moderately correlated with overall Star Ratings ( r =0.70). CONCLUSIONS: The HCAHPS HESS and practices of high-scoring hospitals could promote more equitable patient experiences.

Rural disparities in the quality of clinical care are notable and larger for males.

PURPOSE: To investigate whether rural-urban differences in quality of care for Medicare Advantage (MA) enrollees vary between females and males. METHODS: Data for this study came from the 2019 Healthcare Effectiveness Data and Information Set. Linear regression was used to investigate urban-rural differences in individual MA enrollee scores on 34 clinical care measures grouped into 7 categories, and how those differences varied by sex (through evaluation of statistical interactions). FINDINGS: Across all 7 categories of measures, scores for rural residents were worse than scores for urban residents. For 4 categories-care for patients with (suspected) chronic obstructive pulmonary disease, avoiding prescription misuse, behavioral health, and diabetes care-the average difference across measures in the category was greater than 3 percentage points. Across all 34 measures, there were 15 statistically significant rural-by-sex interactions that exceeded 1 percentage point. In 11 of those cases, the deficit associated with living in a rural area was greater for males than for females. In 3 cases, the deficit associated with living in a rural area was larger for females than for males. In 1 case involving Follow-up After Hospitalization for Mental Illness, rural residents had an advantage, and it was larger for males than for females. CONCLUSIONS: Interventions may help address patient- (eg, health literacy and patient activation), provider- (eg, workforce recruitment and retention), and structural-level issues contributing to these disparities, especially for rural males.

Income-related disparities in Medicare advantage behavioral health care quality.

OBJECTIVE: To inform efforts to improve equity in the quality of behavioral health care by examining income-related differences in performance on HEDIS behavioral health measures in Medicare Advantage (MA) plans. DATA SOURCES AND STUDY SETTING: Reporting Year 2019 MA HEDIS data were obtained and analyzed. STUDY DESIGN: Logistic regression models were used to estimate differences in performance related to enrollee income, adjusting for sex, age, and race-and-ethnicity. Low-income enrollees were identified by Dual Eligibility for Medicare and Medicaid or receipt of the Low-Income Subsidy (DE/LIS). Models without and with random effects for plans were used to estimate overall and within-plan differences in measure performance. Heterogeneity by race-and-ethnicity in the associations of low-income with behavioral health quality were examined using models with interaction terms. DATA COLLECTION/EXTRACTION METHODS: Data were included for all MA contracts in the 50 states and the District of Columbia that collect HEDIS data. PRINCIPAL FINDINGS: For six of the eight measures, enrollees with DE/LIS coverage were more likely to have behavioral health conditions that qualify for HEDIS measures than higher income enrollees. In mixed-effects logistic regression models, DE/LIS coverage was associated with statistically significantly worse overall performance on five measures, with four large (>5 percentage point) differences (-7.5 to -11.1 percentage points) related to follow-up after hospitalization and avoidance of drug-disease interactions. Where the differences were large, they were primarily within-plan rather than between-plan. Interactions between DE/LIS and race-and-ethnicity were statistically significant (p < 0.05) for all measures; income-based quality gaps were larger for White enrollees than for Black or Hispanic enrollees. CONCLUSIONS: Low income is associated with lower performance on behavioral health HEDIS measures in MA, but these associations differ across racial-and-ethnic groups. Improving care integration and addressing barriers to care for low-income enrollees may improve equity across income levels in behavioral health care.

Poor self-rated mental health and Medicare beneficiaries' routine care-seeking.

OBJECTIVES: To assess the relationship between self-rated mental health (SRMH) and infrequent routine care among Medicare beneficiaries and to investigate the roles of managed care and having a personal doctor. STUDY DESIGN: Cross-sectional analysis of data from the 2018 Medicare Consumer Assessment of Healthcare Providers and Systems survey. METHODS: Logistic regression was used to predict infrequent routine care (having not made an appointment for routine care in the last 6 months) from SRMH, Medicare coverage type (fee-for-service [FFS] vs Medicare Advantage [MA], the managed care version of Medicare), and the interaction of these variables. Models that did and did not include having a personal doctor were compared. All models controlled for demographics and physical health. RESULTS: Overall, 14.9% of beneficiaries did not make a routine care appointment in the last 6 months, with rates adjusted for demographics and physical health ranging from 14.5% for those with "excellent" SRMH to 19.2% for those with "poor" SRMH. Beneficiaries with poor SRMH were less likely to make a routine care appointment in FFS than in MA (20.1% vs 16.4%, respectively, had not done so in the last 6 months; P < .05). Accounting for having a personal doctor reduced the association between SRMH and infrequent routine care by about a third. CONCLUSIONS: Extra efforts are needed to ensure receipt of routine care by beneficiaries with poor mental health-particularly in FFS, where more should be done to ensure that beneficiaries have a personal doctor.

Patient Experience for Hispanic Older Adults Varies by Language Preference.

BACKGROUND: Hispanic people with Medicare report worse patient experiences than non-Hispanic White counterparts. However, little research examines how these disparities may vary by language preference (English/Spanish). OBJECTIVES: Using Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey data, assess whether 2014-2018 disparities in patient experiences for Hispanic people with Medicare vary by language preference. RESEARCH DESIGN: We fit a series of linear, case-mix adjusted models predicting Medicare CAHPS measures by race/ethnicity/language preference (Hispanic Spanish-respondents; Hispanic Spanish-preferring English-respondents; Hispanic English-preferring respondents; and non-Hispanic White English-respondents). SUBJECTS: A total of 1,006,543 Hispanic and non-Hispanic White respondents to the Medicare 2014-2018 CAHPS surveys. RESULTS: There were disparities for all Hispanic groups relative to non-Hispanic White English-respondents. Hispanic Spanish-preferring English-respondents reported worse experience than Hispanic Spanish-respondents for getting care quickly (-8 points), getting needed care (-5 points), doctor communication (-2 points), and customer service (-1 point), but better experiences for flu immunization (+2 points). Similarly, Hispanic Spanish-preferring English-respondents reported worse experience than Hispanic English-preferring respondents for getting care quickly (-4 points) and getting needed care (-2 points). Hispanic English-preferring respondents reported worse experience than Hispanic Spanish-respondents for getting care quickly (-4 points), getting needed care (-3 points), doctor communication and customer service (-2 points each), but better experience for flu immunization (+2 points). CONCLUSIONS: Regardless of language preference, Hispanic people with Medicare experience disparities in patient care relative to non-Hispanic White English-preferring counterparts. Hispanic Spanish-preferring English-respondents report the worse experiences, followed by Hispanic English-preferring respondents. Hispanic Spanish-respondents experienced the least disparities of the three Hispanic language subgroups.

Predicting Race And Ethnicity To Ensure Equitable Algorithms For Health Care Decision Making.

Algorithms are currently used to assist in a wide array of health care decisions. Despite the general utility of these health care algorithms, there is growing recognition that they may lead to unintended racially discriminatory practices, raising concerns about the potential for algorithmic bias. An intuitive precaution against such bias is to remove race and ethnicity information as an input to health care algorithms, mimicking the idea of "race-blind" decisions. However, we argue that this approach is misguided. Knowledge, not ignorance, of race and ethnicity is necessary to combat algorithmic bias. When race and ethnicity are observed, many methodological approaches can be used to enforce equitable algorithmic performance. When race and ethnicity information is unavailable, which is often the case, imputing them can expand opportunities to not only identify and assess algorithmic bias but also combat it in both clinical and nonclinical settings. A valid imputation method, such as Bayesian Improved Surname Geocoding, can be applied to standard data collected by public and private payers and provider entities. We describe two applications in which imputation of race and ethnicity can help mitigate potential algorithmic biases: equitable disease screening algorithms using machine learning and equitable pay-for-performance incentives.

Disparities In The Quality Of Clinical Care Delivered To American Indian/Alaska Native Medicare Advantage Enrollees.

This study used data from the 2019 Healthcare Effectiveness Data and Information Set (HEDIS) to examine differences in the quality of care received by American Indian/Alaska Native beneficiaries versus care received by non-Hispanic White beneficiaries enrolled in Medicare Advantage (managed care) plans. American Indian/Alaska Native beneficiaries were more likely than White beneficiaries to receive care that meets clinical standards for eight of twenty-six HEDIS measures and were less likely than White beneficiaries to receive care that meets clinical standards for five of twenty-six measures. Measures for which American Indian/Alaska Native beneficiaries were less likely to receive care meeting clinical standards were mainly ones pertaining to appropriate treatment of diagnosed conditions. In all cases, differences in care for American Indian/Alaska Native and White beneficiaries were largely within-plan differences. These findings indicate the need for improved clinical care for all beneficiaries. For American Indian/Alaska Native beneficiaries, there is a particular need for improvement in the treatment of diagnosed conditions, including diabetes, chronic obstructive pulmonary disease, and alcohol and other forms of substance abuse.

Measuring Inconsistency in Quality Across Patient Groups to Target Quality Improvement.

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.

Standardized assessment of depression symptoms in post-acute care: A screening threshold approach.

BACKGROUND: Depression symptoms have impacts on quality of life, rehabilitation and treatment adherence, and resource utilization among patients in post-acute care (PAC) settings. The PHQ-2 and PHQ-9 are instruments for the assessment of depression, previously used in PAC settings, that have tradeoffs in terms of measurement depth versus respondent/assessor burden. Therefore, the present study tested a gateway version of the protocol (PHQ-2 to 9). METHODS: In 143 PAC settings in 14 U.S. markets across 10 states from November 2017 to August 2018, facility and research nurses administered the PHQ-2 to communicative patients (n = 3010). Nurses administered the full PHQ-9 if the patient screened positive for either of the two cardinal symptoms assessed by the PHQ-2 (depressed mood and anhedonia). We assessed the prevalence and frequency of depression symptoms using the PHQ-2 to 9, associations between depression screening results and patient characteristics and clinical conditions, and feasibility indicators. RESULTS: More than 1 in 4 patients (28%) screened positive on the PHQ-2. Only 6% of those completing the full PHQ-9 had a score indicating "minimal" severity. The average score (M = 11.9) met the threshold for moderate depression. Positive PHQ-2 screening was associated with age, female gender, disposition at discharge, septicemia/severe sepsis, and dependence for ADLs of toileting and lying to sitting mobility. Age was also associated with full PHQ-9 scores; patients ages 45-64 had the highest mean score. Length of stay was not associated with PHQ-2 screening results or full PHQ-2 to 9 scores. Missing data were minimal (<2.4%). The average time to complete was 2.3 min. Interrater reliability and percent agreement were excellent. CONCLUSIONS: These findings suggest the feasibility of a gateway scoring approach to standardized assessment of depression symptoms among PAC patients, and that depression symptoms are relatively common among this inpatient population.

Distinguishing neighborhood and individual social risk factors in health care.

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.

Disparities in Care Experienced by Older Hispanic Medicare Beneficiaries in Urban and Rural Areas.

BACKGROUND: Hispanic older adults face substantial health disparities compared with non-Hispanic-White (hereafter "White") older adults. To the extent that these disparities stem from cultural and language barriers faced by Hispanic people, they may be compounded by residence in rural areas. OBJECTIVE: The objective of this study was to investigate possible interactions between Hispanic ethnicity and rural residence in predicting the health care experiences of older adults in the United States, and whether disparities in care for rural Hispanic older adults differ in Medicare Advantage versus Medicare Fee-for-Service. SUBJECTS: Medicare beneficiaries age 65 years and older who responded to the 2017-2018 nationally representative Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys. METHODS: We fit a series of linear, case-mix-adjusted models predicting Medicare CAHPS measures of patient experience (rescaled to a 0-100 scale) from ethnicity, place of residence, and Medicare coverage type. RESULTS: In all residential areas, Hispanic beneficiaries reported worse experiences with getting needed care (-3 points), getting care quickly (-4 points), and care coordination (-1 point) than White beneficiaries (all P's<0.001). In rural areas only, Hispanic beneficiaries reported significantly worse experiences than White beneficiaries on doctor communication and customer services (-3 and -9 points, respectively, P<0.05). Tests of a 3-way interaction between ethnicity, rural residence, and coverage type were nonsignificant. CONCLUSIONS: There is a need to improve access to care and care coordination for Hispanic beneficiaries overall and doctor-patient communication and customer service for rural Hispanic beneficiaries. Strategies for addressing deficits faced by rural Hispanics may involve cultural competency training and provision of language-appropriate services for beneficiaries (perhaps as telehealth services).

Racial/Ethnic Differences in Emergency Department Utilization and Experience.

BACKGROUND: Previous work has demonstrated racial/ethnic differences in emergency department (ED) utilization, but less is known about racial/ethnic differences in the experience of care received during an ED visit. OBJECTIVE: To examine differences in self-reported healthcare utilization and experiences with ED care by patients' race/ethnicity. DESIGN: Adult ED patients discharged to community (DTC) were surveyed (response rate: 20.25%) using the Emergency Department Patient Experience of Care (EDPEC) DTC Survey. Linear regression was used to estimate case-mix-adjusted differences in patient experience between racial/ethnic groups. PARTICIPANTS: 3122 survey respondents who were discharged from the EDs of 50 hospitals nationwide January-March 2016. MAIN MEASURES: Six measures: getting timely care, doctor and nurse communication, communication about medications, receipt of sufficient information about test results, whether hospital staff discussed the patient's ability to receive follow-up care, and willingness to recommend the ED. KEY RESULTS: Black and Hispanic patients were significantly more likely than White patients to report visiting the ED for an ongoing health condition (40% Black, 30% Hispanic, 28% White, p<0.001), report having visited an ED 3+ times in the last 6 months (26% Black, 25% Hispanic, 19% White, p<0.001), and report not having a usual source of care (19% Black, 19% Hispanic, 8% White, p<0.001). Compared with White patients, Hispanic patients more often reported that hospital staff talked with them about their ability to receive needed follow-up care (+7.2 percentile points, p=0.038) and recommended the ED (+7.2 points, p=0.037); Hispanic and Black patients reported better doctor and nurse communication (+6.4 points, p=0.008; +4 points, p=0.036, respectively). CONCLUSIONS: Hispanic and Black ED patients reported higher ED utilization, lacked a usual source of care, and reported better experience with ED care than White patients. Results may reflect differences in care delivery by staff and/or different expectations of ED care among Hispanic and Black patients.

Rates of Disenrollment From Medicare Advantage Plans Are Higher for Racial/Ethnic Minority Beneficiaries.

BACKGROUND: Each year, about 10% of Medicare Advantage (MA) enrollees voluntarily switch to another MA contract, while another 2% voluntarily switch from MA to fee-for-service Medicare. Voluntary disenrollment from MA plans is related to beneficiaries' negative experiences with their plan, disrupts the continuity of care, and conflicts with goals to reduce Medicare costs. Little is known about racial/ethnic disparities in voluntary disenrollment from MA plans. OBJECTIVE: The objective of this study was to investigate differences in rates of voluntary disenrollment from MA plans by race/ethnicity. SUBJECTS: A total of 116,770,319 beneficiaries enrolled in 736 MA plans in 2015. METHODS: Differences in rates of disenrollment across racial/ethnic groups [Asian or Pacific Islander (API), Black, Hispanic, and White] were summarized using 4 types of logistic regression models: adjusted and unadjusted models estimating overall differences and adjusted and unadjusted models estimating within-plan differences. Unadjusted overall models included only racial/ethnic group probabilities as predictors. Adjusted overall models added age, sex, dual eligibility, disability, and state of residence as control variables. Between-plan differences were estimated by subtracting within-plan differences from overall differences. RESULTS: Adjusted rates of disenrollment were significantly (P<0.001) higher for Hispanic (+1.2 percentage points), Black (+1.2 percentage points), and API beneficiaries (+2.4 percentage points) than for Whites. Within states, all 3 racial/ethnic minority groups tended to be concentrated in higher disenrollment plans. Within plans, API beneficiaries voluntarily disenrolled considerably more often than otherwise similar White beneficiaries. CONCLUSION: These findings suggest the need to address cost, information, and other factors that may create barriers to racial/ethnic minority beneficiaries' enrollment in plans with lower overall disenrollment rates.

Incentivizing Excellent Care to At-Risk Groups with a Health Equity Summary Score.

BACKGROUND: Social risk factors (SRFs) such as minority race-and-ethnicity or low income are associated with quality-of-care, health, and healthcare outcomes. Organizations might prioritize improving care for easier-to-treat groups over those with SRFs, but measuring, reporting, and further incentivizing quality-of-care for SRF groups may improve their care. OBJECTIVE: To develop, as a proof-of-concept, a Health Equity Summary Score (HESS): a succinct, easy-to-understand score that could be used to promote high-quality care to those with SRFs in Medicare Advantage (MA) health plans, which provide care for almost twenty million older and disabled Americans and collect extensive quality measure and SRF data. DESIGN: We estimated, standardized, and combined performance scores for two sets of quality measures for enrollees in 2013-2016 MA health plans, considering both current levels of care, within-plan improvement, and nationally benchmarked improvement for those with SRFs (specifically, racial-and-ethnic minority status and dual-eligibility for Medicare and Medicaid). PARTICIPANTS: All MA plans with publicly reported quality scores and 500 or more 2016 enrollees. MAIN MEASURES: Publicly reported clinical quality and patient experience measures. KEY RESULTS: Almost 90% of plans measured for MA Star Ratings received a HESS; plans serving few patients with SRFs were excluded. The summary score was moderately positively correlated with publicly reported overall Star Ratings (r = 0.66-0.67). High-scoring plans typically had sizable enrollment of both racial-and-ethnic minorities (38-42%) and dually eligible beneficiaries (29-38%). CONCLUSIONS: We demonstrated the feasibility of developing and estimating a HESS that is intended to promote and incentivize excellent care for racial-and-ethnic minorities and dually eligible MA enrollees. The HESS measures SRF-specific performance and does not simply duplicate overall plan Star Ratings. It also identifies plans that provide excellent care to large numbers of those with SRFs. Our methodology could be extended to other SRFs, quality measures, and settings.