Objectives: To examine characteristics of Medicare Advantage (MA) enrollees who use their plan's customer service to help plans understand how to better meet members' needs.
Study Design: National sample of 259,533 respondents to MA Consumer Assessment of Healthcare Providers and Systems survey enrolled in any of the 559 MA contracts in 2022.
Methods: We assessed the association between self-reported customer service use in the prior 6 months and enrollee demographic, coverage, health, and health care utilization characteristics.
We investigated unfair treatment among 1863 Medicare Advantage (MA) enrollees from 21 MA plans using 2022 survey data (40% response rate) in which respondents indicated whether they were treated unfairly in a health care setting based on any of 10 personal characteristics. We calculated reported unfair treatment rates overall and by enrollee characteristics. Nine percent of respondents reported any unfair treatment, most often based on health condition (6%), disability (3%), or age (2%).
View Article and Find Full Text PDFArch Gerontol Geriatr
September 2024
Background: While a number of tools exist to predict mortality among older adults, less research has described the characteristics of Medicare Advantage (MA) enrollees at higher risk for 1 year mortality.
Objectives: To describe the characteristics of MA enrollees at higher mortality risk using patient survey data.
Research Design: Retrospective cohort.
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.
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.
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.
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.
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).
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.
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.
View Article and Find Full Text PDFBackground: 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.
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.
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.
View Article and Find Full Text PDFBackground: Little is known about the health care experiences of American Indians and Alaska Natives (AIANs) due to limited data.
Objective: The objective of this study was to investigate the health care experiences of AIAN Medicare beneficiaries relative to non-Hispanic Whites using national survey data pooled over 5 years.
Subjects: A total of 1,193,248 beneficiaries who responded to the nationally representative 2012-2016 Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys.
We assess the association between survey layout and response rates (RRs) in the 2017 Medicare Advantage Consumer Assessment of Healthcare Providers and Systems mail survey. Among 438 Medicare Advantage plans surveyed by six vendors, there was latitude in survey layout, and plans could add up to 12 supplemental items. Regression models predicted survey response from survey characteristics (page count, number of supplemental items, and survey attractiveness), and beneficiary sociodemographics.
View Article and Find Full Text PDFObjective: To assess the effect of changing survey questions on plan-level patient experience measures and ratings.
Data Source: 2015 Medicare Advantage CAHPS Survey respondents.
Study Design: Ninety three randomly selected beneficiaries in each of 40 MA plans received a revised (5.
Background: Health plans often require that patients have a personal doctor. Older adults rely on specialists for much of their care and may use a specialist in this role, but little is known about how many or which Medicare beneficiaries use specialists as their personal doctor and how their care experiences differ from others'.
Objective: To examine the prevalence and characteristics of Medicare beneficiaries with a specialist as a personal doctor and compare their patient experiences and immunization to other beneficiaries'.
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.
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.
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.
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.
Objective: Spanish-preferring Medicare beneficiaries are underrepresented in national patient experience surveys. We test a method for improving their representation via higher response rates.
Data Sources/study Setting: 2009-2010 Medicare CAHPS surveys; Medicare population.
Background: Race/ethnicity information is vital for measuring disparities across groups, and self-report is the gold standard. Many surveys assign simplified race/ethnicity based on responses to separate questions about Hispanic ethnicity and race and instruct respondents to "check all that apply." When multiple races are endorsed, standard classification methods either create a single heterogenous multiracial group, or attempt to impute the single choice that would have been selected had only one choice been allowed.
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