Objective: To examine whether care experiences and immunization for racial/ethnic/language minority Medicare beneficiaries vary with the proportion of same-group beneficiaries in Medicare Advantage (MA) contracts.
Data Sources/study Setting: Exactly 492,495 Medicare beneficiaries responding to the 2008-2009 MA Consumer Assessment of Healthcare Providers and Systems (CAHPS) Survey.
Data Collection/extraction Methods: Mixed-effect regression models predicted eight CAHPS patient experience measures from self-reported race/ethnicity/language preference at individual and contract levels, beneficiary-level case-mix adjustors, along with contract and geographic random effects.
Principal Findings: As a contract's proportion of a given minority group increased, overall and non-Hispanic, white patient experiences were poorer on average; for the minority group in question, however, high-minority plans may score as well as low-minority plans. Spanish-preferring Hispanic beneficiaries also experience smaller disparities relative to non-Hispanic whites in plans with higher Spanish-preferring proportions.
Conclusions: The tendency for high-minority contracts to provide less positive patient experiences for others in the contract, but similar or even more positive patient experiences for concentrated minority group beneficiaries, may reflect cultural competency, particularly language services, that partially or fully counterbalance the poorer overall quality of these contracts. For some beneficiaries, experiences may be just as positive in some high-minority plans with low overall scores as in plans with higher overall scores.
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http://dx.doi.org/10.1111/1475-6773.12292 | DOI Listing |
BMC Prim Care
December 2024
Health Campus The Hague/Department of Public Health and Primary Care, Leiden University Medical Center, The Hague, The Netherlands.
Background: This study aimed to explore the impact of the COVID-19 pandemic and resulting changes to diabetes care, especially concerning disease control, the use of (tele)consultation and lessons worth implementing to improve diabetes care, with a specific focus on ethnic minority groups.
Methods: A mixed-methods prospective cohort study among people with type 2 Diabetes Mellitus (T2DM) treated in primary care during the COVID-19 pandemic. A survey was sent regionally, including items related to teleconsultation and amount of contact with the healthcare professional.
J Racial Ethn Health Disparities
December 2024
Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Background: The Charlson Comorbidity Index (CCI) is a frequently used mortality predictor based on a scoring system for the number and type of patient comorbidities health researchers have used since the late 1980s. The initial purpose of the CCI was to classify comorbid conditions, which could alter the risk of patient mortality within a 1-year time frame. However, the CCI may not accurately reflect risk among American Indians because they are a small proportion of the US population and possibly lack representation in the original patient cohort.
View Article and Find Full Text PDFJ Mol Med (Berl)
December 2024
Department of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
In one of the earliest reports from China during COVID-19, it was noted that over 20% of patients hospitalized with the disease had significant elevations of troponin, a marker of myocardial tissue damage, that put them at a higher risk. In a hypothesis-independent whole exome sequencing (WES) study in hospitalized COVID-19 patients of diverse ancestry, we observed putative enrichment in pathogenic variants in genes known to be involved in the pathogenesis of cardiomyopathy. This observation led us to hypothesize that the observed high morbidity and mortality in these patients might be due to the presence of rare genetic factors that had previously been silent but became relevant as a consequence of the severe stress inflicted by an infection with SARS-CoV-2.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Introduction: Down Syndrome Regression Disorder (DSRD) is a neuropsychiatric condition causing insomnia, catatonia, encephalopathy, and obsessive-compulsive behavior in otherwise healthy individuals with Down syndrome (DS). Smaller cohorts have identified heterogenous diagnostic abnormalities which have predicted immunotherapy responsiveness although pattern analysis in a large cohort has never been performed.
Methods: A multi-center, retrospective study of individuals with DSRD was performed.
Sci Rep
December 2024
School of Big Data, Fuzhou University of International Studies and Trade, Fuzhou, 350202, China.
The traditional machine learning methods such as decision tree (DT), random forest (RF), and support vector machine (SVM) have low classification performance. This paper proposes an algorithm for the dry bean dataset and obesity levels dataset that can balance the minority class and the majority class and has a clustering function to improve the traditional machine learning classification accuracy and various performance indicators such as precision, recall, f1-score, and area under curve (AUC) for imbalanced data. The key idea is to use the advantages of borderline-synthetic minority oversampling technique (BLSMOTE) to generate new samples using samples on the boundary of minority class samples to reduce the impact of noise on model building, and the advantages of K-means clustering to divide data into different groups according to similarities or common features.
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