Trends in HCAHPS Survey Scores, 2008-2019: A Quality Improvement Perspective.

BACKGROUND: HCAHPS' 2008 initial public reporting, 2012 inclusion in the Hospital Value-Based Purchasing Program (HVBP), and 2015 inclusion in Hospital Star Ratings were intended to improve patient experiences. OBJECTIVES: Characterize pre-COVID-19 (2008-2019) trends in hospital consumer assessment of healthcare providers and systems (HCAHPS) scores. RESEARCH DESIGN: Describe HCAHPS score trends overall, by phase: (1) initial public reporting period (2008-2013), (2) first 2 years of HVBP (2013-2015), and (3) initial HCAHPS Star Ratings reporting (2015-2019); and by hospital characteristics (HCAHPS decile, ownership, size, teaching affiliation, and urban/rural). SUBJECTS: A total of 3909 HCAHPS-participating US hospitals. MEASURES: HCAHPS summary score (HCAHPS-SS) and 9 measures. RESULTS: The mean 2007-2019 HCAHPS-SS improvement in most-positive-category ("top-box") responses was +5.2 percentage points/pp across all hospitals (where differences of 5pp, 3pp, and 1pp are "large," "medium," and "small"). Improvement rate was largest in phase 1 (+0.8/pp/year vs. +0.2pp/year and +0.1pp/year for phases 2 and 3, respectively). Improvement was largest for Overall Rating of Hospital (+8.5pp), Discharge Information (+7.3pp), and Nurse Communication (+6.5pp), smallest for Doctor Communication (+0.8pp). Some measures improved notably through phases 2 and 3 (Nurse Communication, Staff Responsiveness, Overall Rating of Hospital), but others slowed or reversed in Phase 3 (Communication about Medicines, Quietness). Bottom-decile hospitals improved more than other hospitals for all measures. CONCLUSIONS: All HCAHPS measures improved rapidly 2008-2013, especially among low-performing (bottom-decile) hospitals, narrowing the range of performance and improving scores overall. This initial improvement may reflect widespread, general quality improvement (QI) efforts in lower-performing hospitals. Subsequent slower improvement following the introduction of HVBP and Star Ratings may have reflected targeted, resource-intensive QI in higher-performing hospitals.

Medicare Advantage enrollees' reports of unfair treatment during health care encounters.

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%). Approximately 40% of those reporting any unfair treatment endorsed multiple categories. People who qualified for Medicare via disability reported unfair treatment by disability, age, income, race and ethnicity, sex, sexual orientation, and gender/gender identity more often than those who qualified via age. Enrollees dually eligible for Medicare and Medicaid or eligible for a Low-Income Subsidy (DE/LIS) reported unfair treatment by disability, income, language/accent, race and ethnicity, culture/religion, and sex more often than non-DE/LIS enrollees. Compared with White respondents, racial and ethnic minority respondents more often reported unfair treatment by race and ethnicity, language/accent, culture/religion, and income. Female respondents were more likely than male respondents to report unfair treatment based on age and sex.

Survey Protocols, Response Rates, and Representation of Underserved Patients: A Randomized Clinical Trial.

Importance: Surveys often underrepresent certain patients, such as underserved patients. Methods that improve their response rates (RRs) would help patient surveys better represent their experiences and assess equity and equity-targeted quality improvement efforts. Objective: To estimate the effect of adding an initial web mode to existing Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey protocols and extending the fielding period on RR and representativeness of underserved patient groups. Design, Setting, and Participants: This randomized clinical trial included 36 001 patients discharged from 46 US hospitals from May through December 2021. Data analysis was performed from May 2022 to September 2023. Exposures: Patients were randomized to 1 of 6 survey protocols: 3 standard HCAHPS protocols (mail only, phone only, mail-phone) plus 3 web-enhanced protocols (web-mail, web-phone, web-mail-phone). Main Outcomes and Measures: RR and number of respondents per 100 survey attempts (yield) were calculated and compared for each of the 6 survey protocols, overall, and by patient age, service line, sex, and race and ethnicity. Results: A total of 34 335 patients (median age range, 55-59 years; 59.3% female individuals and 40.7% male individuals) were eligible and included in the study. Of the respondents, 6.9% were Asian American or Native Hawaiian or Other Pacific Islander, 0.7% were American Indian or Alaska Native, 11.5% were Black, 17.4% were Hispanic, 61.0% were White, and 2.6% were multiracial. Of the 6 protocols, RRs were highest in web-mail-phone (36.5%), intermediate for the 3 two-mode survey protocols (mail-phone, web-mail, web-phone, 30.3%-31.1%), and lowest for the 2 single-mode protocols (mail only, phone only, 22.1%-24.3%). Web-mail-phone resulted in the highest yield for 3 racial and ethnic groups (Black, Hispanic, and White patients) and second highest for another (multiracial patients). Otherwise, the highest or second highest yield was almost always a 2-mode protocol. Mail only was the lowest-yield protocol for Black, Hispanic, and multiracial patients and phone-only was the lowest-yield protocol for White patients; these 2 protocols tied for lowest-yield for Asian American or Native Hawaiian or Other Pacific Islander patients. Gains from multimode approaches were often 2 to 3 times as large for Asian American or Native Hawaiian or Other Pacific Islander, Black, Hispanic, and multiracial patients as for White patients. Web-mail-phone had the highest RR for 6 of 8 age groups and 4 of 5 combinations of service line and sex. Conclusions and Relevance: In this randomized clinical trial, web-first multimode survey protocols significantly improved the RR and representativeness of patient surveys. The best-performing protocol based on RR and representativeness was web-mail-phone. Web-phone performed well for young and diverse patient populations, and web-mail for older and less diverse patient populations. The US Centers for Medicare & Medicaid Services will allow hospitals to use the web-mail, web-phone, and web-mail-phone protocols for HCAHPS administration beginning in 2025.

Interventions and Hospital Characteristics Associated With Patient Experience: An Update of the Evidence.

Patient experience is a key hospital quality measure. We review and characterize the literature on interventions, care and management processes, and structural characteristics associated with better inpatient experiences as measured by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. Prior reviews identified several promising interventions. We update these previous efforts by including more recent peer-reviewed literature and expanding the review's scope to include observational studies of HCAHPS measures with process measures and structural characteristics. We used PubMed to identify U.S. English-language peer-reviewed articles published in 2017 to 2020 and focused on hospital patient experience. The two HCAHPS domains for which we found the fewest potential quality improvement interventions were Communication with Doctors and Quietness. We identified several modifiable processes that could be rigorously evaluated in the future, including electronic health record patient engagement functionality, care management processes, and nurse-to-patient ratios. We describe implications for future policy, practice, and research.

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.

Changes in Patient Experiences of Hospital Care During the COVID-19 Pandemic.

Importance: It is important to assess how the COVID-19 pandemic was adversely associated with patients' care experiences. Objective: To describe differences in 2020 to 2021 patient experiences from what would have been expected from prepandemic (2018-2019) trends and assess correlates of changes across hospitals. Design, Setting, and Participants: This cohort study compared 2020 to 2021 data with 2018 to 2019 data from 3 900 887 HCAHPS respondents discharged from 3381 HCAHPS-participating US hospitals. The data were analyzed from 2022 to 2023. Main Outcomes and Measures: The primary outcome was an HCAHPS summary score (HCAHPS-SS), which averaged 10 HCAHPS measures. The primary analysis estimated whether HCAHPS scores from patients discharged from 2020 to 2021 differed from scores that would be expected based on quarterly and linear trends from 2018 to 2019 discharges. Secondary analyses stratified hospitals by prepandemic overall star ratings and staffing levels. Results: Of the 3 900 887 HCAHPS 2020 to 2021 respondents, 59% were age 65 years or older, and 35% (11%) were in the surgical (maternity) service lines. Compared with trends expected based on prepandemic (2018-2019) data, HCAHPS-SS was 1.2 percentage points (pp) lower for quarter (Q) 2/2020 discharges and -1.9 to -2.0 pp for Q3/2020 to Q1/2021, which then declined to -3.6 pp by Q4/2021. The most affected measures (Q4/2021) were staff responsiveness (-5.6 pp) and cleanliness (-4.9 pp); the least affected were discharge information (-1.6 pp) and quietness (-1.8 pp). Overall rating and hospital recommendation measures initially exhibited smaller-than-average decreases, but then fell as much as the more specific experience measures by Q2/2021. Quietness did not decline until Q2/2021. The HCAHPS-SS fell most for hospitals with the lowest prepandemic staffing levels; hospitals with bottom-quartile staffing showed the largest decrements, whereas top-quartile hospitals showed smaller decrements in most quarters. Hospitals with better overall prepandemic quality showed consistently smaller HCAHPS-SS drops, with effects for 5-star hospitals about 25% smaller than for 1-star and 2-star hospitals. Conclusions and Relevance: The results of this cohort study of HCAHPS-participating hospitals found that patient experience scores declined during 2020 to 2021. By Q4/2021, the HCAHPS-SS was 3.6 pp lower than would have been expected, a medium effect size. The most affected measures (staff responsiveness and cleanliness) showed large effect sizes, possibly reflecting high illness-associated hospital workforce absenteeism. Hospitals that were lower performing and less staffed prepandemic may have been less resilient to reduced staff availability and other pandemic-associated challenges. However, by Q4/2021, even prepandemic high-performing hospitals had similar declines.

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.

The hospital care experiences of older patients compared to younger patients.

BACKGROUND: Hospitals may provide less positive patient experiences for older than younger patients. METHODS: We used 2019 HCAHPS data from 4358 hospitals to compare patient-mix adjusted HCAHPS Survey scores for 19 experience of care items for patients ages 75+ versus 55-74 years and tested for interactions of age group with patient and hospital characteristics. We contrasted the age patterns observed for inpatient experiences with those among respondents to the 2019 Medicare CAHPS (MCAHPS) Survey of overall experience. RESULTS: Patients 75+ years (31% of all HCAHPS respondents) reported less-positive experiences than those 55-74 (46% of respondents) for 18 of 19 substantive HCAHPS items (mean difference -3.3% points). Age differences in HCAHPS top-box scores were large (>5 points) for 1 of 3 Nurse Communication items, 1 of 3 Doctor Communication, 2 of 2 Communication about Medication items, 1 of 2 Discharge Information items, and 2 of 3 Care Transition items. In contrast, for MCAHPS, those 75+ reported similar experiences to younger adults. The magnitude of age differences varied considerably across hospitals; some hospitals had very large age disparities for older patients (age 75+ vs. ages 55-74), while others had none. These age differences were generally smaller for patients in government and non-profit than in for-profit hospitals, and in the Pacific region than in other parts of the United States. This variation in age disparities across hospitals may help to identify best practices. CONCLUSIONS: Patients ages 75+ reported less-positive experiences than patients ages 55-74, especially for measures of communication. These differences may be specific to inpatient care. Further study should investigate the effectiveness of hospital staffs' communication with older patients. Hospital protocols designed for younger patients may need to be adjusted to meet the needs of older patients. There may also be opportunities to learn from outpatient interactions with older patients.

Community-dwelling adults with functional limitations are at greater risk for sleep disturbances.

OBJECTIVE: To evaluate whether sleep disturbances vary along a continuum of functional limitations in a large nationally representative sample of US adults. METHODS: Using 2014-2015 National Health Interview Survey data (n = 33,424), we considered associations between each of 5 sleep disturbance measures (duration, trouble falling asleep, trouble staying asleep, use of sleep medications, waking rested) and Functional Limitations Index score, which distinguishes among adults with little-or-no (least-limited), moderate (somewhat-limited), and high functional limitations (most-limited). RESULTS: Somewhat-limited and most-limited respondents reported significantly worse sleep health for all sleep disturbance measures than people with little-or-no limitations, even controlling for body mass index, psychological distress, and 14 health indicators. CONCLUSIONS: People with significant self-reported limitations in physical functioning, independent of specific disabilities or disabling condition, report more sleep disturbances. Clinicians may want to evaluate the sleep health of patients with functional limitations.

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.

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.

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.

Associations of Mail Survey Length and Layout With Response Rates.

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. Beneficiary-age-by-survey-characteristic interactions assessed whether survey characteristics were more strongly related to RRs among older beneficiaries. We found that surveys with more supplemental items and less attractive layouts had lower adjusted odds of response. RRs were more sensitive to format among older beneficiaries. The difference in adjusted RRs for the most favorable versus the least favorable survey design was 14.5%. For a 65-year-old, this difference was 13.6%; for an 80-year-old, it was 21.0%. These findings suggest that even within a relatively standardized survey, formatting can substantially influence RRs.

The development of a patient-reported functional limitations index.

OBJECTIVES: To develop an easy-to-interpret, patient-reported Functional Limitations Index (FLI) that can be used to assess and monitor the full spectrum of functioning in a community-dwelling population. STUDY DESIGN: Observational design using nationally representative survey data. METHODS: We used self-rated health as a criterion for empirically assigning weights to 5 National Health Interview Survey items assessing difficulty with seeing, hearing, walking, cognition, and self-care. In addition to succinctly summarizing cumulative limitations, we addressed 2 main questions: (1) Which limitations have stronger associations with self-rated health? and (2) How does severity (from 0, no difficulty, to 3, unable to do) relate to self-rated health? We generated a respondent-level summary score based on a model predicting self-rated health from the 5 linearly scored (0-3) items and used splines to account for nonlinear severity-self-rated health associations. RESULTS: The strongest association of specific functional limitations with self-rated health involved mobility; the weakest associations involved sensory limitations. The association of severity with self-rated health was nonlinear and largest moving from no difficulty to somewhat difficult. Nationally, 5% of noninstitutionalized adults were considered most limited, 8% somewhat limited, and 87% least limited. Great mobility limitations (defined as a lot of difficulty or unable to do) most distinguished limitation groups (present in 0% of least limited, 25% of somewhat limited, and 70% of most limited). CONCLUSIONS: The FLI is an easy-to-administer, easy-to-interpret, and valid summary measure of disability that health plans and health care organizations can use for quality-of-care monitoring across a variety of settings to improve care for patients with disabilities.

Using Ancillary Sociodemographic Data to Identify Sexual Minority Adults Among Those Responding "Something Else" or "Don't Know" to Sexual Orientation Questions.

BACKGROUND: General population surveys are increasingly offering broader response options for questions on sexual orientation-for example, not only gay or lesbian, but also "something else" (SE) and "don't know" (DK). However, these additional response options are potentially confusing for those who may not know what the terms mean. Researchers studying sexual orientation-based disparities face difficult methodological trade-offs regarding how best to classify respondents identifying with the SE and DK categories. OBJECTIVES: Develop respondent-level probabilities of sexual minority orientation without excluding or misclassifying the potentially ambiguous SE and DK responses. Compare 3 increasingly inclusive analytic approaches for estimating health disparities using a single item: (a) omitting SE and DK respondents; (b) classifying SE as sexual minority and omitting DK; and (c) a new approach classifying only SE and DK respondents with >50% predicted probabilities of being sexual minorities as sexual minority. MATERIALS AND METHODS: We used the sociodemographic information and follow-up questions for SE and DK respondents in the 2013-2014 National Health Interview Survey to generate predicted probabilities of identifying as a sexual minority adult. RESULTS: About 94% of the 144 SE respondents and 20% of the 310 DK respondents were predicted to identify as a sexual minority adult, with higher probabilities for younger, wealthier, non-Hispanic white, and urban-dwelling respondents. Using a more specific definition of sexual minority orientation improved the precision of health and health care disparity estimates. CONCLUSIONS: Predicted probabilities of sexual minority orientation may be used in this and other surveys to improve representation and categorization of those who identify as a sexual minority adult.

The effects of survey version on patient experience scores and plan rankings.

OBJECTIVE: 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 (5.0) CAHPS survey; 38 832 beneficiaries received version 4.0. Linear mixed-effect regression predicted CAHPS measures from fixed effects for survey version and beneficiary characteristics and random effects for plan and plan-by-version random slope. PRINCIPAL FINDINGS: Response rates were 42 percent for both versions. Removal of "try to" from screeners increased the percentage of respondents eligible for follow-up questions. Version 5.0 caused a small increase (1-3 points on a 0-100 scale, P < 0.05) in the mean of three altered measures and a moderate increase (>3 points) in one. There was a small statistically significant increase in two unaltered measures. These changes were uniform across plans, so there would be no expected change compared to results using the legacy survey in the score distributions other than uniform mean shifts, and no expected effect on summary measures. CONCLUSIONS: These analyses illustrate how to assess the impact of seemingly minor survey modifications for other national surveys considering changes and highlight the importance of screeners in instrument design.

An Integrated Approach to Measuring Sexual Orientation Disparities in Women's Access to Health Services: A National Health Interview Survey Application.

PURPOSE: The extent to which disparities affect all sexual minority women (SMW) versus specific subgroups of lesbian, bisexual, or other women remains unclear, in part due to inconsistent analysis of available data. We propose an integrated approach that aggregates subgroups to maximize power to detect broadly applicable disparities, then tests for subgroup heterogeneity, exercising caution with disaggregation when there is no direct evidence of heterogeneity. METHODS: Multivariate analyses of 2014-2015 National Health Interview Survey data examined six barriers to care. We compared heterosexual women (n = 36,474) with SMW (n = 1048) overall and tested for heterogeneous outcomes among subgroups of SMW compared with heterosexual women and with each other. RESULTS: Controlling for sociodemographics and health status, aggregated analyses showed that SMW were more likely than heterosexual peers to have trouble finding a provider (adjusted percentages 5.1% vs. 3.2%, p < 0.01) and no optimal usual place of care (14.5% vs. 11.2%, p < 0.01). There was no evidence of subgroup heterogeneity for either barrier, suggesting uniform disparities for SMW. In contrast, only lesbian/gay women were more likely than heterosexual women to be told their health insurance was not accepted (p = 0.03); this was the only outcome for which the adjusted difference between bisexual and lesbian/gay women was significant (2.8% vs. 6.3%, p = 0.02). CONCLUSION: Analyses that only disaggregated data would have understated overall sexual minority disparities and perhaps overstated subgroup differences; an integrated approach can more accurately characterize disparities experienced by all SMW versus those specific to certain subgroups. Large national surveys should include sexual orientation questions to support adequately powered comparisons.