Comparing HEDIS performance of Dual Eligible Special Needs Plans with other coverage types for dually eligible people.

People eligible for both Medicare and Medicaid coverage ("dually eligible individuals") have lower levels of income and assets and often higher health care needs and costs than those eligible for Medicare but not Medicaid coverage. Their 3 most common Medicare coverage options are Medicare Advantage (MA) Dual Eligible Special Needs Plans (D-SNPs), non-D-SNP MA plans, and fee-for-service (FFS) Medicare with a stand-alone prescription drug plan. No prior study has examined clinical quality of care for dually eligible individuals across these 3 coverage types. To fill that void, we used logistic regression to compare these coverage types on 6 HEDIS measures of clinical quality of care that were available for both MA and FFS (constructed from claims files). D-SNPs and non-D-SNP MA plans significantly outperformed FFS for all 6 measures for dually eligible individuals, by approximately 5 percentage points for 2 measures and by 18-34 percentage points for the other 4 measures. For the 4 measures with the greatest advantage over FFS, performance was 3-8 percentage points higher in D-SNPs than in non-D-SNP MA plans.

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.

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.

Sex differences in Medicare beneficiaries' experiences by low-income status.

OBJECTIVES: Medicare beneficiaries dually eligible for Medicaid are a low-income group who are often in poor health. Little research has examined sex differences in patient experience by dual/low-income subsidy (LIS) status. STUDY DESIGN: Cross-sectional comparison by sex and low-income status. METHODS: We used linear regression to compare 6 case mix-adjusted patient experience measures (on a 0-100 scale) by sex within non-dual/LIS and dual/LIS beneficiary groups among 549,603 respondents 65 years and older to the 2016-2017 Medicare Consumer Assessment of Healthcare Providers and Systems surveys of beneficiary experience with Medicare (mail with telephone follow-up of nonrespondents, 42% response rate). RESULTS: Dual/LIS male beneficiaries reported worse patient experiences on all 6 measures than female beneficiaries, with scores 1 to 2 percentage points lower for 3 measures and less than 1 percentage point lower for the other 3 measures. For 4 of the 6 measures, sex differences among dual/LIS beneficiaries were significantly larger than those among non-dual/LIS beneficiaries. In all 4 instances, the gaps between men and women among dual/LIS beneficiaries favored women; P < .05 for all differences discussed. CONCLUSIONS: Low-income male Medicare beneficiaries are more likely to report poor patient experiences, possibly because of lower health literacy, less patient activation, and smaller social networks, along with provider responses to these characteristics. Efforts to address these patient-level factors should happen in parallel with structural-level approaches to train and prepare providers to ensure attentive, respectful patient-centered care for all patients. Additionally, targeted use of ombudsmen and interventions may help reduce inequities.

The Contribution of First-name Information to the Accuracy of Racial-and-Ethnic Imputations Varies by Sex and Race-and-Ethnicity Among Medicare Beneficiaries.

BACKGROUND: Data on race-and-ethnicity that are needed to measure health equity are often limited or missing. The importance of first name and sex in predicting race-and-ethnicity is not well understood. OBJECTIVE: The objective of this study was to compare the contribution of first-name information to the accuracy of basic and more complex racial-and-ethnic imputations that incorporate surname information. RESEARCH DESIGN: We imputed race-and-ethnicity in a sample of Medicare beneficiaries under 2 scenarios: (1) with only sparse predictors (name, address, sex) and (2) with a rich set (adding limited administrative race-and-ethnicity, demographics, and insurance). SUBJECTS: A total of 284,627 Medicare beneficiaries who completed the 2014 Medicare Consumer Assessment of Healthcare Providers and Systems survey and reported race-and-ethnicity were included. RESULTS: Hispanic, non-Hispanic Asian/Pacific Islander, and non-Hispanic White racial-and-ethnic imputations are more accurate for males than females under both sparse-predictor and rich-predictor scenarios; adding first-name information increases accuracy more for females than males. In contrast, imputations of non-Hispanic Black race-and-ethnicity are similarly accurate for females and males, and first names increase accuracy equally for each sex in both sparse-predictor and rich-predictor scenarios. For all 4 racial-and-ethnic groups, incorporating first-name information improves prediction accuracy more under the sparse-predictor scenario than under the rich-predictor scenario. CONCLUSION: First-name information contributes more to the accuracy of racial-and-ethnic imputations in a sparse-predictor scenario than in a rich-predictor scenario and generally narrows sex gaps in accuracy of imputations.

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.

Patient-Reported Care Coordination is Associated with Better Performance on Clinical Care Measures.

BACKGROUND: Prior studies using aggregated data suggest that better care coordination is associated with higher performance on measures of clinical care process; it is unclear whether this relationship reflects care coordination activities of health plans or physician practices. OBJECTIVE: Estimate within-plan relationships between beneficiary-reported care coordination measures and HEDIS measures of clinical process for the same individuals. DESIGN: Mixed-effect regression models in cross-sectional data. PARTICIPANTS: 2013 Medicare Advantage CAHPS respondents (n=152,069) with care coordination items linked to independently collected HEDIS data on clinical processes. MAIN MEASURES: Care coordination measures assessed follow-up, whether doctors had medical records during visits, whether doctors discussed medicines being taken, how informed doctors seemed about specialist care, and help received with managing care among different providers. HEDIS measures included mammography, colorectal cancer screening, cardiovascular LDL-C screening, controlling blood pressure, 5 diabetes care measures (LDL-C screening, retinal eye exam, nephropathy, blood sugar/HbA1c <9%, LCL-C<100 mg/dL), glaucoma screening in older adults, BMI assessment, osteoporosis management for women with a fracture, and rheumatoid arthritis therapy. KEY RESULTS: For 9 of the 13 HEDIS measures, within health plans, beneficiaries who reported better care coordination also received better clinical care (p<0.05) and none of the associations went in the opposite direction; HEDIS differences between those with excellent and poor coordination exceeded 5 percentage points for 7 measures. Nine measures had positive associations (breast cancer screening, colorectal cancer screening, cardiovascular care LDL-C screening, 4 of 5 diabetes care measures, osteoporosis management, and rheumatoid arthritis therapy). CONCLUSIONS: Within health plans, beneficiaries who report better care coordination also received higher-quality clinical care, particularly for care processes that entail organizing patient care activities and sharing information among different healthcare providers. These results extend prior research showing that health plans with better beneficiary-reported care coordination achieved higher HEDIS performance scores.

Gender Differences in Patient Experience Across Medicare Advantage Plans.

BACKGROUND: Medicare beneficiaries annually select fee-for-service Medicare or a private Medicare insurance (managed care) plan; information about plan performance on quality measures can inform their decisions. Although there is drill-down information available regarding quality variation by race and ethnicity, there remains a dearth of evidence regarding the extent to which care varies by other key beneficiary characteristics, such as gender. We measured gender differences for six patient experience measures and how gender gaps differ across Medicare plans. METHODS: We used data from 300,979 respondents to the 2015-2016 Medicare Advantage Consumer Assessment of Healthcare Providers and Systems surveys. We fit case mix-adjusted linear mixed-effects models to estimate gender differences and evaluate heterogeneity in differences across health plans. RESULTS: Nationally, women's experiences were better than men's (p < .05) by 1 percentage point on measures involving interactions with administrative staff (+1.6 percentage point for customer service) and timely access to care (+1.1 percentage point for getting care quickly), but worse on a measure that may involve negotiation with physicians (getting needed care). Gender gaps varied across plans, particularly for getting care quickly and getting needed care, where plan-level differences of up to 5 to 6 percentage points were observed. CONCLUSIONS: Although the average national differences in patient experience by gender were generally small, gender gaps were larger in some health plans and for specific measures. This finding indicates opportunities for health plans with larger gender gaps to implement quality improvement efforts.

Educational Attainment and Perceived Need for Urgent Care.

While lower educational attainment is associated with worse health status, education may also affect one's ability to identify need for urgent care. Using data from the 2010 Medicare CAHPS survey, we estimated multivariate logistic models to test the relationship between self-reported educational attainment and the perceived need for urgent care, controlling for health status and other factors. As expected, lower educational attainment was associated with greater reported need for urgent care in bivariate analyses because of poorer health. However, lower educational attainment was associated with less perceived need for urgent care after controlling for health status, particularly for those in poor health. These findings suggest the need for interventions to improve the likelihood that people with less education recognize the need for urgent care, particularly those in poor health and in most need of urgent care.

Exploring Disparities in Influenza Immunization for Older Women.

OBJECTIVES: While women obtain most recommended preventive health interventions more often than men, evidence is mixed regarding influenza vaccination for older adults. Therefore, we evaluated sex differences in influenza vaccination among older adults. DESIGN: Nationally representative cross-sectional survey. SETTING: United States. PARTICIPANTS: A total of 1 252 705 adults, aged 65 years and older, responding to 2013 to 2017 Medicare Consumer Assessment of Healthcare Providers and Systems surveys. MEASUREMENTS: The dependent variable was Healthcare Effectiveness Data and Information Set self-reported influenza immunization. The primary predictor was sex. Covariates included general health status, education, race/ethnicity, and Medicare Advantage (MA; managed care) vs Fee-for-Service (FFS) coverage. RESULTS: After adjusting for health status and other sociodemographic factors, women's immunization was 2% lower than men's immunization in MA, with no significant overall sex difference in FFS. Women were immunized less often than men in 95% of MA health plans, with the largest gaps in low-immunizing plans. Further analyses revealed variation in sex differences by health status, education, and race/ethnicity in both MA and FFS. Notably in MA, women in poor health were immunized less often than men in similar health (-4%; P < .001). Black women were immunized much less often than black men in both MA and FFS (-5%; P < .001 for each). Hispanic women were immunized less often than Hispanic men in MA (-4%; P < .001) but not within FFS. CONCLUSION: Women in MA experience small disparities overall in influenza immunization, with larger disparities for black and Hispanic women. Providers and MA plans should increase efforts to recommend and monitor immunization for older women, especially black and Hispanic women and those in poor health. Given the potential to reduce morbidity and mortality, equitable access to a critical preventive health service, such as influenza immunization, is crucial for all older adults.

Geographic context of black-white disparities in Medicare CAHPS patient experience measures.

OBJECTIVE: To examine whether black-white patient experience disparities vary by geography and within-county contextual factors. DATA SOURCES: 321 300 Medicare beneficiaries responding to the 2015-2016 Medicare Consumer Assessment of Health care Providers and Systems (MCAHPS) Surveys; 2010 Census data for several within-county contextual factors. STUDY DESIGN: Mixed-effects regression models predicted three MCAHPS patient experience measures for black and white beneficiaries from geographic random effects, contextual fixed effects, and beneficiary-level case-mix adjustors. PRINCIPAL FINDINGS: Black-white disparities in patient experiences were smaller in counties with higher average patient experiences. Black-white disparities in patient experiences were not associated with county-level poverty or racial segregation. However, county racial segregation and some measures of poverty were significantly associated with all beneficiaries' level of health care access. Getting Needed Care scores were higher with greater racial segregation, while Getting Care Quickly scores were lower with higher poverty and racial segregation. CONCLUSIONS: Efforts to reduce black-white disparities in patient experiences should focus on areas with low average patient experiences. Attempts to reduce disparities in timely access to health care should target primarily black, low-income, and racially and economically segregated areas. Positive associations of racial segregation with accessing needed care were unexpected.

Indirect Estimation of Race/Ethnicity for Survey Respondents Who Do Not Report Race/Ethnicity.

BACKGROUND: Researchers are increasingly interested in measuring race/ethnicity, but some survey respondents skip race/ethnicity items. OBJECTIVES: The main objectives of this study were to investigate the extent to which racial/ethnic groups differ in skipping race/ethnicity survey items, the degree to which this reflects reluctance to disclose race/ethnicity, and the utility of imputing missing race/ethnicity. RESEARCH DESIGN: We applied a previously developed method for imputing race/ethnicity from administrative data (Medicare Bayesian Improved Surname and Geocoding 2.0) to data from a national survey where race/ethnicity was usually self-reported, but was sometimes missing. A linear mixed-effects regression model predicted the probability of self-reporting race/ethnicity from imputed racial/ethnic probabilities. SUBJECTS: In total, 508,497 Medicare beneficiaries responding to the 2013-2014 Medicare Consumer Assessment of Healthcare Providers and Systems surveys were included in this study. MEASURES: Self-reported race/ethnicity and estimated racial/ethnic probabilities. RESULTS: Black beneficiaries were most likely to not self-report their race/ethnicity (6.6%), followed by Hispanic (4.7%) and Asian/Pacific Islander (4.7%) beneficiaries. Non-Hispanic whites were the least likely to skip these items (3.2%). The 3.7% overall rate of missingness is similar to adjacent demographic items. General patterns of item missingness rather than a specific reluctance to disclose race/ethnicity appears to explain the elevated rate of missing race/ethnicity among Asian/Pacific Islander and Hispanic beneficiaries and most but not all among Black beneficiaries. Adding imputed cases to the data set did not substantially alter the estimated overall racial/ethnic distribution, but it did modestly increase sample size and statistical power. CONCLUSIONS: It may be worthwhile to impute race/ethnicity when this information is unavailable in survey data sets due to item nonresponse, especially when missingness is high.

Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity.

OBJECTIVE: To improve an existing method, Medicare Bayesian Improved Surname Geocoding (MBISG) 1.0 that augments the Centers for Medicare & Medicaid Services' (CMS) administrative measure of race/ethnicity with surname and geographic data to estimate race/ethnicity. DATA SOURCES/STUDY SETTING: Data from 284 627 respondents to the 2014 Medicare CAHPS survey. STUDY DESIGN: We compared performance (cross-validated Pearson correlation of estimates and self-reported race/ethnicity) for several alternative models predicting self-reported race/ethnicity in cross-sectional observational data to assess accuracy of estimates, resulting in MBISG 2.0. MBISG 2.0 adds to MBISG 1.0 first name, demographic, and coverage predictors of race/ethnicity and uses a more flexible data aggregation framework. DATA COLLECTION/EXTRACTION METHODS: We linked survey-reported race/ethnicity to CMS administrative and US census data. PRINCIPAL FINDINGS: MBISG 2.0 removed 25-39 percent of the remaining MBISG 1.0 error for Hispanics, Whites, and Asian/Pacific Islanders (API), and 9 percent for Blacks, resulting in correlations of 0.88 to 0.95 with self-reported race/ethnicity for these groups. CONCLUSIONS: MBISG 2.0 represents a substantial improvement over MBISG 1.0 and the use of CMS administrative data on race/ethnicity alone. MBISG 2.0 is used in CMS' public reporting of Medicare Advantage contract HEDIS measures stratified by race/ethnicity for Hispanics, Whites, API, and Blacks.

Racial And Ethnic Differences In The Attainment Of Behavioral Health Quality Measures In Medicare Advantage Plans.

As the Medicare population becomes more diverse and its demand for behavioral health care grows, a better understanding of racial/ethnic disparities in the quality of behavioral health care is crucial. Medicare Advantage (MA) plans are accountable through the public reporting of quality performance on measures, including the Healthcare Effectiveness Data and Information Set (HEDIS). We examined HEDIS data on eight MA behavioral health care quality measures, using mixed-effects logistic regressions to distinguish racial/ethnic differences within and between MA health plans. We found that performance differed across racial/ethnic groups by more than 10 percentage points on most quality measures. Significant within-plan disparities were found in twenty of twenty-four comparisons of racial/ethnic minority groups with whites. Within-plan disparities varied widely across plans, with performance being equivalent across racial/ethnic groups in some plans and widely divergent in others. Unlike other types of medical care, in behavioral health within-plan quality disparities are prominent in MA plans, which suggests a role for stratified reporting by racial/ethnic group.

How Do Gender Differences in Quality of Care Vary Across Medicare Advantage Plans?

BACKGROUND: Healthcare Effectiveness Data and Information Set (HEDIS) quality measures have long been used to compare care across health plans and to study racial/ethnic and socioeconomic disparities among Medicare Advantage (MA) beneficiaries. However, possible gender differences in seniors' quality of care have received less attention. OBJECTIVE: To test for the presence and nature of any gender differences in quality of care across MA Plans, overall and by domain; to identify those most at risk of poor care. DESIGN: Cross-sectional analysis of individual-level HEDIS measure scores from 23.8 million records using binomial mixed-effect models to estimate the effect of gender on performance. For each measure, we assess variation in gender gaps and their correlation with plan performance. PARTICIPANTS: Beneficiaries from 456 MA plans in 2011-2012 HEDIS data. MAIN MEASURES: Performance on 32 of 34 HEDIS measures which were available in both measurement years. The two excluded measures had mean performance scores below 10%. KEY RESULTS: Women experienced better quality of care than men for 22/32 measures, with most pertaining to screening or treatment. Men experienced better quality on nine measures, including four related to cardiovascular disease and three to potentially harmful drug-disease interactions. Plans varied substantially in the magnitude of gender gaps for 21/32 measures; in general, the gender gap in quality of care was least favorable to men in low-performing plans. CONCLUSIONS: Women generally experienced better quality of care than men. However, women experienced poorer care for cardiovascular disease-related intermediate outcomes and potentially harmful drug-disease interactions. Quality improvement may be especially important for men in low-performing plans and for cardiovascular-related care and drug-disease interactions for women. Gender-stratified reporting could reveal gender gaps, identify plans for which care varies by gender, and motivate efforts to address faults and close the gaps in the delivery system.

Patient-reported denials, appeals, and complaints: associations with overall plan ratings.

OBJECTIVES: To assess whether Medicare patients' reports of denied care, appeals/complaints, and satisfactory resolution were associated with ratings of their health plan or care. STUDY DESIGN: Retrospective analysis of 2010 Medicare Advantage Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey data. METHODS: Multivariate linear regression of data from 154,766 respondents (61.1% response rate) tested the association of beneficiary ratings of plan and care with beneficiary reports of denied care, appeals, complaints, and complaint resolution, adjusting for beneficiary demographics. RESULTS: Beneficiaries who reported being denied needed care rated their plans and care significantly less positively, by 17.2 points (on a 100-point scale) and 9.1 points, respectively. Filing an appeal was not statistically significantly associated with further lower ratings. Beneficiaries who filed a complaint that was satisfactorily resolved gave slightly lower ratings of plans (-3.4 points) and care (-2.5 points) than those not filing a complaint (P <.001 for all results). CONCLUSIONS: Lower ratings from patients reporting complaints and denied care may notably affect the overall 0-10 CAHPS ratings of Medicare Advantage plans. Our results suggest that beneficiaries may attribute the actions that lead to complaints or denials to plans more than to the care they received. Successful complaint resolution and utilization management review might eliminate most deficits associated with complaints and denied care, consistent with the service recovery paradox. High rates of complaints and denied care might identify areas that need improved utilization management review, customer service, and quality improvement. Among those reporting being denied care, filing an appeal was not associated with lower patient ratings of plan or care.

Do Experiences with Medicare Managed Care Vary According to the Proportion of Same-Race/Ethnicity/Language Individuals Enrolled in One's Contract?

OBJECTIVE: To examine whether care experiences and immunization for racial/ethnic/language minority Medicare beneficiaries vary with the proportion of same-group beneficiaries in Medicare Advantage (MA) contracts. DATA SOURCES/STUDY SETTING: Exactly 492,495 Medicare beneficiaries responding to the 2008-2009 MA Consumer Assessment of Healthcare Providers and Systems (CAHPS) Survey. DATA COLLECTION/EXTRACTION METHODS: Mixed-effect regression models predicted eight CAHPS patient experience measures from self-reported race/ethnicity/language preference at individual and contract levels, beneficiary-level case-mix adjustors, along with contract and geographic random effects. PRINCIPAL FINDINGS: As a contract's proportion of a given minority group increased, overall and non-Hispanic, white patient experiences were poorer on average; for the minority group in question, however, high-minority plans may score as well as low-minority plans. Spanish-preferring Hispanic beneficiaries also experience smaller disparities relative to non-Hispanic whites in plans with higher Spanish-preferring proportions. CONCLUSIONS: The tendency for high-minority contracts to provide less positive patient experiences for others in the contract, but similar or even more positive patient experiences for concentrated minority group beneficiaries, may reflect cultural competency, particularly language services, that partially or fully counterbalance the poorer overall quality of these contracts. For some beneficiaries, experiences may be just as positive in some high-minority plans with low overall scores as in plans with higher overall scores.

Do Racial/Ethnic Disparities in Quality and Patient Experience within Medicare Plans Generalize across Measures and Racial/Ethnic Groups?

OBJECTIVE: To examine how similar racial/ethnic disparities in clinical quality (Healthcare Effectiveness Data and Information Set [HEDIS]) and patient experience (Consumer Assessment of Healthcare Providers and Systems [CAHPS]) measures are for different measures within Medicare Advantage (MA) plans. DATA SOURCES/STUDY SETTING: 5.7 million/492,495 MA beneficiaries with 2008-2009 HEDIS/CAHPS data. STUDY DESIGN: Binomial (HEDIS) and linear (CAHPS) hierarchical mixed models generated contract estimates for HEDIS/CAHPS measures for Hispanics, blacks, Asian-Pacific Islanders, and whites. We examine the correlation of within-plan disparities for HEDIS and CAHPS measures across measures. PRINCIPAL FINDINGS: Plans with disparities for a given minority group (vs. whites) for a particular measure have a moderate tendency for similar disparities for other measures of the same type (mean r = 0.51/.21 and 53/34 percent positive and statistically significant for CAHPS/HEDIS). This pattern holds to a lesser extent for correlations of CAHPS disparities and HEDIS disparities (mean r = 0.05/0.14/0.23 and 4.4/5.6/4.4 percent) positive and statistically significant for blacks/Hispanics/API. CONCLUSIONS: Similarities in CAHPS and HEDIS disparities across measures might reflect common structural factors, such as language services or provider incentives, affecting several measures simultaneously. Health plan structural changes might reduce disparities across multiple measures.

Experiences of care among Medicare beneficiaries with ESRD: Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey results.

BACKGROUND: Patients with end-stage renal disease (ESRD) have special health needs; little is known about their care experiences. STUDY DESIGN: Secondary analysis of 2009-2010 Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) data, using representative random samples of Medicare beneficiaries. Description of Medicare beneficiaries with ESRD and investigation of differences in patient experiences by sociodemographic characteristics and coverage type. SETTING & PARTICIPANTS: Data were collected from 823,564 Medicare beneficiaries (3,794 with ESRD) as part of the Medicare CAHPS survey, administered by mail with telephone follow-up of nonrespondents. PREDICTOR: ESRD status, age, education, self-reported general and mental health status, race/ethnicity, sex, Medicare coverage type, state of residence, and other demographic measures. OUTCOMES: 6 composite measures of patient experience in 4 care domains (access to care, physician communication, customer service, and access to prescription drugs and drug information) and 4 ratings (overall care, personal physician, specialist physician, and prescription drug plan). RESULTS: Patients with ESRD reported better care experiences than non-ESRD beneficiaries for 7 of 10 measures (P < 0.05) after adjustment for patient characteristics, geography, and coverage type, although to only a small extent (adjusted mean difference, <3 points [scale, 0-100]). Black patients with ESRD and less educated patients were more likely than other patients with ESRD to report poor experiences. LIMITATIONS: Inability to distinguish patient experiences of care for different treatment modalities. CONCLUSIONS: On average, beneficiaries with ESRD report patient experiences that are at least as positive as non-ESRD beneficiaries. However, black and less educated patients with ESRD reported worse experiences than other ESRD patients. Stratified reporting of patient experience by race/ethnicity or education in patients with ESRD can be used to monitor this disparity. Physician choice and confidence and trust in physicians may be particularly important for patients with ESRD.