Racial/ethnic disparities in measure calculations for Part D Star Ratings among Medicare beneficiaries with diabetes, hypertension, and/or hyperlipidemia

Barriers to person-centered service design in pharmacy practice: examples, lessons, and potential solutions

Despite increased attention to, and frameworks conceptualizing person-centered care, systematic, organizational, and provider-level barriers continue to discourage the development and delivery of person-centered care (PCC) in pharmacy practice and beyond. This commentary describes existing pharmacy-specific literature related to PCC, barriers to PCC within the context of pharmacy practice, and potential solutions to increase person-centeredness in pharmacy services. Literature to substantiate and describe barriers and potential solutions was identified from 2008 to 2023, a period where the emphasis on PCC in pharmacy practice dramatically increased. Overall, pharmacy-specific literature was identified describing four key barriers to PCC. Several potential solutions were identified, including: using innovative and theory-informed approaches to collecting individual need and preference information, employing processes and equipping providers to facilitate trust, changing organizational culture, and aligning quality metrics and financial incentives with PCC. Identified solutions may be used to address individual, organizational, and systematic barriers to promote PCC.

Impact of star ratings on Medicare health plan enrollment: A systematic literature review

BACKGROUND

The Medicare star ratings program was developed by the Centers for Medicare and Medicaid Services in 2007 as an approach to evaluate health plan performance and quality.

OBJECTIVE

This study aimed to identify and narratively describe studies that attempted to quantitatively assess the impact that Medicare star ratings have on health plan enrollment.

METHODS

A systematic literature review (SLR) was conducted of PubMed MEDLINE, Embase, and Google to identify articles that quantitatively assessed the impact of Medicare star ratings on health plan enrollment. Inclusion criteria consisted of studies that conducted quantitative analyses to estimate the potential impact. Exclusion criteria consisted of qualitative studies and studies that did not directly assess plan enrollment.

RESULTS

This SLR identified 10 studies that sought to measure the impact of Medicare star ratings on plan enrollment. Nine of the studies found that plan enrollment increased in accordance with increases in star ratings or that plan disenrollment increased with decreases in star ratings. One study conducted of data before the implementation of the Medicare quality bonus payment found contradictory results from one year to the next, whereas all the studies that assessed data after implementation found increases in enrollment in accordance to increases in star ratings or increases in disenrollment for decreases in star ratings. One concerning finding from some of the articles included in the SLR is that increases in star ratings had less of an impact on enrollment in higher-rated plans for ethnic and racial minorities and older adults.

CONCLUSIONS

Increases in Medicare star ratings led to statistically significant increases in health plan enrollment and decreases in health plan disenrollment. Future studies are needed to assess whether this increase has a causal association or is caused by additional factors outside of or in addition to increases in overall star rating.

Addressing racial/ethnic disparities associated with Medicare Part D Star Ratings among population with Alzheimer's disease and related dementias

BACKGROUND

Previous studies noted that racial/ethnic minority groups were less likely than non-Hispanic White beneficiaries to be included in the assessment of medication utilization measures of Medicare Part D Star Ratings due to restrictive inclusion criteria for measure calculation. This study explored whether adding a measure with less stringent inclusion criteria to Star Ratings can reduce disparities in measure assessment among beneficiaries with Alzheimer's disease and related dementias (ADRD).

METHODS

This cross-sectional study utilized 2017 Medicare databases linked to Area Health Resources Files. Multivariable logistic regression was used to compare disparities before and after adding the new measure.

RESULTS

By adding the new measure, disparities in the odds for assessment inclusion between non-Hispanic White beneficiaries and Black, Hispanic, Asian, and Other beneficiaries were respectively reduced by 97% (odds ratio, or OR = 1.97, 95% Confidence Interval or CI = 1.89-2.05), 72% (OR = 1.72, 95% CI = 1.58-1.87), 115% (OR = 2.15, 95% CI = 1.87-2.46), and 44% (OR = 1.44, 95% CI = 1.28-1.62).

CONCLUSIONS

To improve the selection of medication utilization measures in Star Ratings among beneficiaries with ADRD, policymakers should investigate the optimal composition of measures to better align the interests of patients, providers, and health plans.

Solving racial/ethnic disparities associated with Medicare Part D Star Ratings

OBJECTIVE

Medicare Part D Star Ratings are instrumental in shaping healthcare quality improvement efforts. However, the calculation metrics for medication performance measures for this program have been associated with racial/ethnic disparities. In this study, we aimed to explore whether an alternative program, named Star Plus by us that included all medication performance measures developed by Pharmacy Quality Alliance and applicable to our study population, would reduce such disparities among Medicare beneficiaries with diabetes, hypertension, and/or hyperlipidemia.

METHOD

We conducted an analysis of a 10% random sample of Medicare A/B/D claims linked to the Area Health Resources File. Multivariate logistic regressions with minority dummy variables were used to examine racial/ethnic disparities in measure calculations of Star Ratings and Star Plus, respectively.

RESULTS

Adjusted results indicated that relative to non-Hispanic Whites (Whites), racial/ethnic minorities had significantly lower odds of being included in the Star Ratings measure calculations: the odds ratios (ORs) for Blacks, Hispanics, Asians, and Others were 0.68 (95% confidence interval [CI] = 0.66-0.71), 0.73 (CI = 0.69-0.78), 0.88 (CI = 0.82-0.93), and 0.92 (CI = 0.88-0.97), respectively. In contrast, every beneficiary in the sample was included in Star Plus. Further, racial/ethnic minorities had significantly higher increase in the odds of being included in measure calculation in Star Plus than Star Ratings. The ORs for Blacks, Hispanics, Asians, and Others were 1.47 (CI = 1.41-1.52), 1.37 (CI = 1.29-1.45), 1.14 (CI = 1.07-1.22), and 1.09 (CI = 1.03-1.14), respectively.

CONCLUSIONS

Our study demonstrated that racial/ethnic disparities may be eliminated by including additional medication performance measures to Star Ratings.

Disparities associated with Medicare Part D Star Ratings measures among patients with Alzheimer's disease and related dementias

The Medicare Parts C and D Star Ratings system was established to improve care quality in Medicare. Previous studies reported racial/ethnic disparities in the calculation of medication adherence measures of Star Ratings in patients with diabetes, hypertension, and hyperlipidemia. This study aimed to identify possible racial/ethnic disparities in the calculation of adherence measures of Medicare Part D Star Ratings among patients with Alzheimer's disease and related dementias (ADRD) and diabetes, hypertension, or hyperlipidemia. This retrospective study analyzed the 2017 Medicare data and Area Health Resources Files. Non-Hispanic White (White) patients were compared to Black, Hispanic, Asian/Pacific Islander (Asian), and other patients on their likelihood of being included in the calculation of adherence measures for diabetes, hypertension, and/or hyperlipidemia. To adjust for the individual/community characteristics, logistic regression was used when the outcome is the inclusion in the calculation of one adherence measure; multinomial regression was used when examining the inclusion in the calculation of multiple adherence measures. Analyzing the data of 1438,076 Medicare beneficiaries with ADRD, this study found that Black (adjusted odds ratio, or OR = 0.79, 95% confidence interval, or 95% CI = 0.73-0.84) and Hispanic (OR = 0.82, 95% CI = 0.75-0.89) patients were less likely than White patients to be included in the calculation of adherence measure for diabetes medications. Further, Black patients were less likely to be included in the calculation of the adherence measure for hypertension medications than White patients (OR = 0.81, 95% CI = 0.78-0.84). All minorities were less likely to be included in calculating the adherence measure for hyperlipidemia medications than Whites. The ORs for Black, Hispanic, and Asian patients were 0.57 (95% CI = 0.55-0.58), 0.69 (95% CI = 0.64-0.74), and 0.83 (95% CI = 0.76-0.91), respectively. Minority patients were generally likely to be included in the measure calculation of fewer measures than White patients. Racial/ethnic disparities were observed in the calculation of Star Ratings measures among patients with ADRD and diabetes, hypertension, and/or hyperlipidemia. Future studies should explore possible causes of and solutions to these disparities.

Effects of Part D Star Ratings on racial and ethnic disparities in health care costs

Background

Racial/ethnic minorities are less likely than non-Hispanic White (White) patients to be included in the Medicare Part D Star Ratings measure assessment due to the restrictive inclusion criteria for the measures.

Objective

This paper examined the effects of racial/ethnic disparities in the measure assessment in Part D Star Ratings on disparities in healthcare costs among patients with Alzheimer's disease and related dementias (ADRD).

Methods

This cross-sectional study analyzed 2017 Medicare data. Proportions of Beneficiaries with ADRD were categorized into the included and excluded groups based on the inclusion criteria for the calculation of medication adherence measures in Star Ratings. Outcomes included costs for medications, physician visits, emergency room (ER) visits, and total costs. A generalized linear model was employed to compare costs across racial/ethnic groups. To explore the differential disparities in healthcare costs between the 2 groups, interaction terms between dummy variables for being excluded from the measure calculation and racial/ethnic minorities were included in the models.

Results

The patterns of racial/ethnic disparities in healthcare costs found in this study were generally consistent with expectations, with some exceptions. For example, compared with White patients, in the hyperlipidemia cohort, the physician visit cost for Black patients among the included group was 31% lower (cost ratio or CR = 0.69, 95% CI = 0.67-0.72); in the hypertension cohort, the hospitalization cost for Blacks among the excluded group was 15% higher (CR = 1.15, 95% CI = 1.12-1.19). More importantly, exclusion from measurement assessments was associated with differential cost disparities. For example, compared with individuals included in the measure assessment for hypertension, the Black-White disparities in costs for hospitalization and total healthcare were 30% higher (CR = 1.30, 95% CI = 1.26-1.34), and 10% higher (CR = 1.10; 95% CI = 1.08-1.12), respectively, among the excluded group.

Conclusions

Medicare Part D Star Ratings may be associated with aggravated racial/ethnic disparities in healthcare costs in the Medicare Part D population.

Racial and ethnic disparities due to Medicare Part D Star Ratings criteria among kidney transplant patients with diabetes, hypertension, and/or dyslipidemia

BACKGROUND: Policies such as Medicare Part D Star Ratings are designed to encourage medication adherence and facilitate positive health outcomes. Patients who have received a kidney transplant not included in assessment of Star Ratings measures may have worse outcomes. OBJECTIVE: To determine if criteria for inclusion in assessment of Star Ratings medication adherence measures among kidney transplant patients with diabetes, hypertension, and dyslipidemia lead to racial and ethnic disparities in who is included in this assessment. METHODS: This was a cross-sectional, secondary analysis of 94,822 adult kidney transplant patients receiving continuous coverage of Medicare Parts A/B/D and filling at least 1 prescription for diabetes, hypertension, or dyslipidemia in 2017. Utilizing 2017 Medicare claims, inclusion in assessment of Star Ratings measures was determined based on criteria for each measure concerning adherence to oral diabetes, hypertension, and dyslipidemia medication. Binary and multinomial logistic regression were conducted. RESULTS: Among kidney transplant patients with diabetes only, Black and Hispanic patients were less likely than White patients to be included in assessment of the Star Ratings adherence measure for oral diabetes medications (P < 0.0001). Among kidney transplant patients with hypertension only and dyslipidemia only, all racial and ethnic minority groups were less likely to be included in assessments of Star Ratings adherence measures for oral hypertension and dyslipidemia medications (P < 0.001). For example, among patients with hypertension, adjusted odds ratios for inclusion of Black, Hispanic, and Asian patients were 0.44 (95% CI = 0.40-0.49), 0.56 (95% CI = 0.49-0.63), and 0.55 (95% = CI 0.45-0.67), respectively. CONCLUSIONS: Disparities exist among patients who have received a kidney transplant qualifying for inclusion in Star Ratings measures, which may ultimately facilitate adverse health outcomes. DISCLOSURES: Marie Chisholm-Burns is a member of the American Society of Transplantation Board of Directors. Christina Spivey has no conflicts of interest to disclose. Chi Chun Tsang has no conflicts of interest to disclose. Junling Wang received funding for this project from the National Institute on Aging/National Institutes of Health; she has also received funding from AbbVie and Pharmaceutical Research and Manufacturers of America (additionally, she has received consulting fees from the latter). Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG049696 (Principal Investigator: Junling Wang). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The sponsor of the research does not have any role in any aspect of the research, including study design and the collection, analysis, and interpretation of data; the writing of the report; and the decision to submit the manuscript for publication.

Bayes Conditional Probability-Based Causation Analysis between Gestational Diabetes Mellitus (GDM) and Pregnancy-Induced Hypertension (PIH): A Statistic Case Study in Harbin, China

Both gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH) would influence the gestation significantly. However, the causation between these two symptoms remains speculative. 16,404 pregnant women were identified in Harbin, China, in this study. We investigated and evaluated the causal effect of GDM on PIH based on the Bayes conditional probability. The statistical results indicated that PIH might cause GDM, but not vice versa. Also, this case study demonstrated that the decrease temperature might also cause hypertension during pregnancy, and the prevalence rate of GDM increased with age. However, the prevalence of diabetes did not show a remarkable difference in varied areas and ages. This study could provide some essential information that will help to investigate the mechanism for GDM and PIH.