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.

Differential Privacy Protections in 2020 U.S. Decennial Census Data Do Not Impede Measurement of Racial and Ethnic Disparities.

Census data are vital to health care research but must also protect respondents' confidentiality. The 2020 decennial Census employs a new Differential Privacy framework; this study examines its effect on the accuracy of an important tool for measuring health disparities, the Bayesian Improved Surname and Geocoding (BISG) algorithm, which uses Census Block Group data to estimate race and ethnicity when self-reported data are unavailable. Using self-reported race and ethnicity data as our standard, we compared the accuracy of BISG estimates calculated using the original 2010 Census counts to the accuracy of estimates calculated using 2010 data but with 2020 Differential Privacy in place. The Differential Privacy methodology slightly decreases BISG accuracy for American Indian and Alaska Native people but has little effect for other groups, suggesting that the methodology will not impede health disparities research that employs BISG and similar methods.

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.

Measuring susceptibility to use tobacco in an increasingly complex consumer marketplace: How many questions do we really need?

OBJECTIVE: Predicting which young people are likely to use tobacco in the future is critical for prevention and intervention. Although measures for assessing susceptibility to using tobacco have fulfilled this goal for decades, there is almost no standard for the number of items that should be administered, or which items should be administered for which products. This study explored whether brief but psychometrically sound versions of commonly used susceptibility measures can adequately capture the construct relative to longer measures. METHOD: A sample of young people (N = 451; Mage = 16.5 years; 64% females; 65% White) completed 33 susceptibility items, which are designed to assess susceptibility to use different types of tobacco products (cigarette, smokeless tobacco, vaping products, and little cigars/cigarillos) of various flavors (tobacco, menthol, and sweet). RESULTS: Analysis of these 33 items indicated that asking about the likelihood of using each tobacco product class when a best friend offers it (four items in all) captures 98.5% of information that is captured using the longer set of items; asking the best friend question for each product by each flavor category (11 items in all) captures 99.7% of the information. CONCLUSIONS: Depending on research needs, tobacco use susceptibility can be measured with little loss of information by administering a limited set of items assessing the likelihood that a young person will use a tobacco product if a friend offers it for any product-flavor combination. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Doing more with less: A proposal to advance cigarette packaging regulations in the United States.

Cigarette packages are potent marketing tools. Following guidance from the WHO Framework Convention on Tobacco Control, many countries have sought to diminish this marketing power by mandating that (1) large graphic health warnings be affixed to the packages (i.e., text warnings combined with graphic images of the health consequences of smoking) and (2) all packages be fully "plain" in their design (i.e., all packages use the same drab/bland color and font type; no brand logos, other colors, or designs are permitted). Yet, the United States lags other countries in implementing regulations designed to blunt the marketing power of cigarette packages. This is not because of a lack of effort on the part of the Food and Drug Administration, the main governmental body charged with regulating tobacco products in the United States. Rather, it is because the regulatory options that that have been advanced in the country (e.g., graphic health warnings) have not been found - yet - to be legally feasible by its courts. This commentary works through some of the conceptual, practical, and legal issues regarding packaging regulations in the United States. It considers the political and bureaucratic risks involved with issuing new regulations. The overall intent is to prompt our field to think creatively about what is realistic in this regulatory space and to offer a novel perspective that may help move the United States tobacco control community forward in its efforts to reduce the promotional power of cigarette packages.

Does Reducing the Size of the Tobacco Power Wall Affect Young People's Risk of Future Use of Tobacco Products? An Experimental Investigation.

OBJECTIVE: A ban on tobacco power walls (in-store package displays) is unlikely in the United States because of concerns that such bans violate commercial free speech rights. This experiment evaluated the effectiveness of a more measured strategy for mitigating the influence of the power wall on young people's susceptibility to tobacco use: limiting its size. METHOD: The experiment took place in the RAND StoreLab, a life-sized replica of a convenience store. Participants (N = 275) ages 11-20 years were randomly assigned to shop in a variant of the StoreLab that had either a large (status quo), medium, or small power wall situated behind the checkout counter. Before and after shopping, participants completed measures of risk of future use of unflavored and flavored cigarettes and vaping products. RESULTS: Study condition was unrelated to future risk of smoking unflavored cigarettes, using menthol vaping products, and using sweet-flavored vaping products. Study condition was related to future risk of smoking menthol cigarettes and using unflavored vaping products; compared with exposure to a large power wall, exposure to a small power wall increased the odds of a participant's being at risk for future smoking of menthol cigarettes (odds ratio [OR] = 3.29, 95% CI [1.10, 9.83]) and the odds of a participant's being at risk for using unflavored vaping products (OR = 4.09, 95% CI [1.41, 11.85]). CONCLUSIONS: These findings call into question the viability of reducing the size of the power wall as a singular strategy for dampening its effect on young people's susceptibility to tobacco use.

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.

Does removing menthol cigarettes in convenience stores reduce susceptibility to cigarette smoking? An experimental investigation in young people.

BACKGROUND: Evidence for the effectiveness of menthol cigarette bans comes mostly from studies of adults that smoke. This experiment evaluated whether the absence of menthol products from a convenience store influenced young people's susceptibility to cigarette smoking after they shopped in the store. METHODS: This experiment took place in the RAND StoreLab (RSL), a life-sized research convenience store. A three-group, between-subjects design was used. Study conditions differed in the mix of flavored tobacco products the RSL displayed: 1) All tobacco-, sweet-, and menthol-flavors displayed; 2) only tobacco- and menthol-flavors displayed; and 3) only tobacco-flavors displayed. Participants were randomly assigned to shop in the RSL under one of these conditions and after shopping, completed measures of their susceptibility to cigarette smoking, one measure for menthol cigarettes and one for unflavored cigarettes (scores on each susceptibility measure was dichotomized: 0 = not susceptible; 1 = susceptible). RESULTS: Multivariable logistic regression assessed the main effects of condition on susceptibility to smoking menthol and unflavored cigarettes. There was no condition effect on susceptibility to smoking unflavored cigarettes. However, removing menthol-flavored products significantly increased participants' susceptibility to smoking menthol cigarettes compared to when all flavored products were available (OR = 3.66, 95% CI [1.33, 10.03]). This significant effect was only found among young people with some pre-existing risk of cigarette smoking (OR = 5.92, 95% CI [1.81, 19.39]). CONCLUSION: Results suggest the need to consider that menthol bans could unintentionally increase the appeal of menthol cigarettes among youth already at risk of smoking.

An experimental evaluation of the effects of banning the sale of flavored tobacco products on adolescents' and young adults' future nicotine vaping intentions.

BACKGROUND: Some U.S. states and municipalities have banned the sale of flavored tobacco products to help curb youth vaping. However, evidence supporting such bans is limited. This experiment tested whether removing flavored tobacco products from a retail setting diminished adolescents' (ages 11-20) future intentions to use vaping products. METHODS: The study was implemented in the RAND StoreLab, a life-sized model convenience store. The display of flavored tobacco products in the store was manipulated with these conditions: 1) tobacco, sweet, and menthol/mint flavors displayed; 2) only tobacco and menthol/mint displayed; and 3) only tobacco flavors displayed. Participants were randomly assigned to shop in one of these conditions and completed measures of future vaping intentions post-shopping. Separate logistic regression models assessed effect of condition on future intentions to use different flavors (tobacco-, menthol/mint-, and sweet-flavored) and any flavor (composite score across flavor categories) of vaping products. RESULTS: Study condition was not associated with intentions to use menthol/mint-, sweet-flavored, or any flavor. Compared to the condition in which all flavored products were displayed, removing menthol/mint- and sweet-flavored products significantly increased future intentions to use tobacco-flavored vaping products (OR = 3.97, 95 % CI [1.01, 15.58], p < .05). This effect was only observed among adolescents with history of vaping (OR = 11.30, 95 % CI [1.42, 89.96], p = .02). CONCLUSIONS: Flavor bans may not affect adolescents' intentions to use menthol/mint, sweet, or "any" flavor of vaping products but may increase intentions to use tobacco-flavored products for teens who have already started vaping.

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.

Evaluation of a protocol for eliciting narrative accounts of pediatric inpatient experiences of care.

OBJECTIVE: To evaluate the measurement properties of a set of six items designed to elicit narrative accounts of pediatric inpatient experience. DATA SOURCES: Data came from 163 participants recruited from a probability-based online panel of U.S. adults. Participants were family members of a child who had an overnight hospital stay in the past 12 months. STUDY DESIGN: Cross-sectional survey with follow-up phone interviews. DATA COLLECTION/EXTRACTION METHODS: Participants completed an online (n = 129) or phone (n = 34) survey about their child's hospitalization experience. The survey contained closed-ended items from the Child Hospital Consumer Assessment of Healthcare Providers and Systems (Child HCAHPS) survey, followed by the six narrative items. Approximately 2 weeks after completing the survey, 47 participants additionally completed a one-hour, semi-structured phone interview, the results of which served as a "gold standard" for evaluating the fidelity of narrative responses. Qualitative content analysis was used to code narrative and interview responses for domains of patient experience and actionability. PRINCIPAL FINDINGS: The average narrative was 248 words (SD = 319). Seventy-nine percent of narratives mentioned a topic included in the Child HCAHPS survey; 89% mentioned a topic not covered by that survey; and 75% included at least one detailed description of an actionable event. Overall, there was 66% correspondence between narrative and interview responses. Correspondence was higher on the phone than in the online condition (75% vs. 59%). CONCLUSIONS: Narratives elicited from rigorously designed multi-item sets can provide detailed, substantive information about pediatric inpatient experiences that hospitals could use to improve child and family experiences during pediatric hospitalization. They add context to closed-ended survey item responses and provide information about experiences of care important to children and families that are not included in quantitative surveys.

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.

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.