Effects of Medicare comprehensive medication review on racial/ethnic disparities in nonadherence to statin medications among patients with Alzheimer's Disease: an observational analysis

The association between comprehensive medication review and medication adherence among medicare beneficiaries with chronic obstructive pulmonary disease

Background

Medicare Part D plans are required to provide Medication therapy management (MTM) services to eligible beneficiaries to optimize medication utilization. Comprehensive medication review (CMR) is a core element of the MTM program. Despite the availability of advanced medical treatment for patients with chronic obstructive pulmonary disease (COPD), medication adherence to maintenance medications poses a continued challenge for patients with COPD.

Objective

To examine the effects of CMR on medication adherence among patients with COPD.

Methods

Medicare data for 2016-2017 linked to Area Health Resource Files were analyzed. The study population was Medicare beneficiaries with COPD. The intervention group consisted of beneficiaries who received CMR in 2017 but not in 2016. Patients who were eligible for MTM services but did not receive these services in 2016 or 2017 made up the control group. Propensity score matching was used to select an intervention and control group with balanced characteristics. The study outcome was adherence to COPD medications with the proportion of days covered at or above 80%. A difference-in-differences approach was adopted in the logistic regression analyses with an interaction term between the status of CMR receipt and the year 2017.

Results

The study sample included 25,564 patients with COPD. The proportions of adherent patients were similar in the control group in both years but increased significantly from 60.08% in 2016 to 69.38% in 2017 in the intervention group (P < .001). The odds of medication adherence in the intervention group increased from 2016 to 2017 by 59% more than in the control group (adjusted odds ratio = 1.59, 95% confidence interval = 1.48-1.71).

Conclusions

Receiving CMR was associated with improved adherence to COPD medications among Medicare beneficiaries. Policymakers should ensure that Medicare beneficiaries with COPD receive CMR.

Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias

Objectives

1.1Biases inherent in electronic health records (EHRs), and therefore in medical artificial intelligence (AI) models may significantly exacerbate health inequities and challenge the adoption of ethical and responsible AI in healthcare. Biases arise from multiple sources, some of which are not as documented in the literature. Biases are encoded in how the data has been collected and labeled, by implicit and unconscious biases of clinicians, or by the tools used for data processing. These biases and their encoding in healthcare records undermine the reliability of such data and bias clinical judgments and medical outcomes. Moreover, when healthcare records are used to build data-driven solutions, the biases are further exacerbated, resulting in systems that perpetuate biases and induce healthcare disparities. This literature scoping review aims to categorize the main sources of biases inherent in EHRs.

Methods

1.2We queried PubMed and Web of Science on January 19th, 2023, for peer-reviewed sources in English, published between 2016 and 2023, using the PRISMA approach to stepwise scoping of the literature. To select the papers that empirically analyze bias in EHR, from the initial yield of 430 papers, 27 duplicates were removed, and 403 studies were screened for eligibility. 196 articles were removed after the title and abstract screening, and 96 articles were excluded after the full-text review resulting in a final selection of 116 articles.

Results

1.3Systematic categorizations of diverse sources of bias are scarce in the literature, while the effects of separate studies are often convoluted and methodologically contestable. Our categorization of published empirical evidence identified the six main sources of bias: a) bias arising from past clinical trials; b) data-related biases arising from missing, incomplete information or poor labeling of data; human-related bias induced by c) implicit clinician bias, d) referral and admission bias; e) diagnosis or risk disparities bias and finally, (f) biases in machinery and algorithms.

Conclusions

1.4Machine learning and data-driven solutions can potentially transform healthcare delivery, but not without limitations. The core inputs in the systems (data and human factors) currently contain several sources of bias that are poorly documented and analyzed for remedies. The current evidence heavily focuses on data-related biases, while other sources are less often analyzed or anecdotal. However, these different sources of biases add to one another exponentially. Therefore, to understand the issues holistically we need to explore these diverse sources of bias. While racial biases in EHR have been often documented, other sources of biases have been less frequently investigated and documented (e.g. gender-related biases, sexual orientation discrimination, socially induced biases, and implicit, often unconscious, human-related cognitive biases). Moreover, some existing studies lack causal evidence, illustrating the different prevalences of disease across groups, which does not per se prove the causality. Our review shows that data-, human- and machine biases are prevalent in healthcare and they significantly impact healthcare outcomes and judgments and exacerbate disparities and differential treatment. Understanding how diverse biases affect AI systems and recommendations is critical. We suggest that researchers and medical personnel should develop safeguards and adopt data-driven solutions with a "bias-in-mind" approach. More empirical evidence is needed to tease out the effects of different sources of bias on health outcomes.

The effects of medication therapy management on medication utilization among Medicare beneficiaries with HIV/AIDS

BACKGROUND

Medicare Part D plans are required to provide medication therapy management (MTM) programs to eligible beneficiaries to optimize medication utilization. MTM programs' effects on medication utilization among older persons living with HIV/AIDS (PLWHs) remain unclear.

OBJECTIVE

This study examined the effects of the Medicare MTM programs on medication utilization among PLWHs.

METHODS

This study analyzed 2017 Medicare databases linked to the Area Health Resources Files. Recipients and nonrecipients of the MTM services were compared on their medication utilization: adherence to antiretroviral medications, drug-drug interactions (DDI), and concurrent use of opioids and benzodiazepines. The intervention group comprised recipients of the MTM services, and the control group was nonrecipients meeting the eligibility criteria. A propensity score with a ratio of 1:2 between the intervention and control groups was used to identify study groups with balanced characteristics. A logistic regression was used to control for patient/community characteristics.

RESULTS

After matching, the intervention and comparison groups comprised 3298 and 6596 beneficiaries for the antiretroviral adherence measure, 809 and 1618 for the DDI measure, and 691 and 1382 for the concurrent use of opioids and benzodiazepines measure. The intervention was associated with higher odds of adherence to antiretroviral medications (adjusted odds ratio = 1.15, 95% CI = 1.04-1.26), and no concurrent use of opioids and benzodiazepines (adjusted odds ratio = 1.255, 95% CI = 1.005-1.568). The study groups did not differ on no DDI (adjusted odds ratio = 0.95, 95% CI = 0.74-1.20).

CONCLUSIONS

Medicare MTM programs effectively improved medication utilization among PLWHs. Future studies should explore the long-term effects of the program.

Racial and ethnic disparities in Medicare Part D medication therapy management services utilization

Background

The Medicare Part D medication therapy management (MTM) program has positive effects on medication and health service utilization. However, little is known about its utilization, much less so about the use among racial and ethnic minorities.

Objective

To examine MTM service utilization among older Medicare beneficiaries and to identify any racial and ethnic disparity patterns.

Methods

A retrospective cross-sectional analysis of 2017 Medicare administrative data, linked to the Area Health Resources Files. Fourteen outcomes related to MTM service nature, initiation, quantity, and delivery were examined using logistic, negative binomial, and Cox proportional hazards regression models.

Results

Racial and ethnic disparities were found with varying patterns across outcomes. For example, compared with White patients, the odds of opting out of MTM were 8% higher for Black patients (odds ratio [OR] = 1.08, 95% confidence interval [CI] = 1.03-1.14), 57% higher for Hispanic patients (OR = 1.57, 95% CI = 1.42-1.72), and 57% higher for Asian patients (OR = 1.57, 95% CI = 1.33-1.85). The odds of continuing MTM from the previous years were 12% lower for Black patients (OR = 0.88, 95% CI = 0.86-0.90) and 3% lower for other patients (OR = 0.97, 95% CI = 0.95-0.99). In addition, the probability of being offered a comprehensive medication review (CMR) after MTM enrollment was 9% lower for Hispanic patients (hazard ratio [HR] = 0.91, 95% CI = 0.85-0.97), 9% lower for Asian patients (HR = 0.91, 95% CI = 0.87-0.94), and 3% lower for other patients (HR = 0.97, 95% CI = 0.95-0.99). Hispanic and Asian patients were more likely to have someone other than themselves receive a CMR.

Conclusions

Racial and ethnic disparities in MTM service utilization were identified. Although the disparities in specific utilization outcomes vary across racial/ethnic groups, it is evident that these disparities exist and may result in vulnerable communities not fully benefiting from the MTM services. Causes of the disparities should be explored to inform future reform of the Medicare Part D MTM program.

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.

Acute, periprocedural and longterm antithrombotic therapy in older adults: 2022 Update by the ESC Working Group on Thrombosis

The first international guidance on antithrombotic therapy in the elderly came from the European Society of Cardiology Working Group on Thrombosis in 2015. This same group has updated its previous report on antiplatelet and anticoagulant drugs for older patients with acute or chronic coronary syndromes, atrial fibrillation, or undergoing surgery or procedures typical of the elderly (transcatheter aortic valve implantation and left atrial appendage closure). The aim is to provide a succinct but comprehensive tool for readers to understand the bases of antithrombotic therapy in older patients, despite the complexities of comorbidities, comedications and uncertain ischaemic- vs. bleeding-risk balance. Fourteen updated consensus statements integrate recent trial data and other evidence, with a focus on high bleeding risk. Guideline recommendations, when present, are highlighted, as well as gaps in evidence. Key consensus points include efforts to improve medical adherence through deprescribing and polypill use; adoption of universal risk definitions for bleeding, myocardial infarction, stroke and cause-specific death; multiple bleeding-avoidance strategies, ranging from gastroprotection with aspirin use to selection of antithrombotic-drug composition, dosing and duration tailored to multiple variables (setting, history, overall risk, age, weight, renal function, comedications, procedures) that need special consideration when managing older adults.