Chronic Disease, Functional Limitations, and Workforce Participation Among Medicaid Enrollees Over 50: The Potential Impact of Medicaid Work Requirements Post-COVID-19

From 2018-2020, 19 states enacted Medicaid work requirements as a strategy for reducing program enrollment and overall cost. While these requirements were later rescinded, strategies to reduce Medicaid costs are likely to reemerge as states attempt to recover economically from the COVID-19 pandemic. Here, we evaluated the impact of Medicaid work requirements on adults aged > 50, a group that likely faces significant age-related chronic disease burden. Using 2016 Health and Retirement Study data, we evaluated the chronic disease burden of adult Medicaid beneficiaries aged 51-64 years (n = 1460) who would be at risk of losing their Medicaid coverage due to work requirements. We compared Medicaid beneficiaries working <20 hours per week (i.e. those at risk of coverage loss) to those working at least 20 hours per week on eight chronic health conditions, adjusting for demographic characteristics. Among those with chronic health conditions, we also evaluated differences in disease severity based on hours worked per week. Among those working fewer than 20 hours per week, odds of disease were greater for seven of eight chronic conditions, including history of stroke (OR: 5.66; 95% CI: 2.22-14.43) and lung disease (OR: 3.79; 95% CI: 2.10-6.85). Further, those with greater disease severity were likely to work fewer hours. Thus, the introduction of Medicaid work requirements would likely result in coverage loss and lower access to care among older Medicaid beneficiaries with multiple chronic health conditions.

Chronic Disease Among Medicaid Beneficiaries Over 50: The Potential Impact of Medicaid Work Requirements

Since 2018, several states have proposed requiring work or other community engagement activities as a condition of receiving Medicaid; however, there has been little inquiry into the impact of such policies on Medicaid recipients over 50. Here, we describe the prevalence and burden of chronic disease among Medicaid beneficiaries over 50 who might be impacted by Medicaid work requirements. We used data from the 2016 wave of the Health and Retirement Study, a large-scale population-based study of adults aged >50. Our sample included individuals over 50 who were not Medicare-eligible (<65 years old) and not receiving Social Security Income. We used logistic regression models to compare those working <20 hours per week (the minimal community engagement/work cutoff) to those working >=20 hours per week, adjusting for age, race/ethnicity, sex, education, and marital status. Individuals working <20 hours per week had greater prevalence of chronic health conditions, including greater odds of diabetes (OR: 2.06; 95% CI: 1.37-2.46), hypertension (OR:2.56; 95% CI: 1.69-3.89), arthritis (OR: 2.96; 95% CI: 2.06-4.62, and lung disease (OR: 4.11; 95% CI: 2.31-7.32). Further, among those with chronic health conditions, those working <20 hours per week reported more, medication use, more worsening of their conditions in the past 2 years, and more hospitalization than their counterparts. Taken together, these finding suggest that Medicaid work requirements in this population would have the most impact on the most medically vulnerable individuals. Policymakers should consider this as they propose policies impacting Medicaid coverage in this population.

A note on multiply robust predictive mean matching imputation with complex survey data

Predictive mean matching is a commonly used imputation procedure for addressing the problem of item nonrespone in surveys. The customary approach relies upon the specification of a single outcome regression model. In this note, we propose a novel predictive mean matching procedure that allows the user to specify multiple outcome regression models. The resulting estimator is multiply robust in the sense that it remains consistent if one of the specified outcome regression models is correctly specified. The results from a simulation study suggest that the proposed method performs well in terms of bias and efficiency.

Oversampling of Minority Populations Through Dual-Frame Surveys

Previous studies have shown disparities in health conditions and behaviors among different ethnic groups. Sampling designs that do not consider oversampling certain minority populations, such as American Indians or African Americans, may not produce sufficient sample sizes for estimating health parameters for minority populations. Oversampling is one of the most common approaches that researchers use to achieve required precision levels for small domain estimation. However, it has not been rigorously investigated in dual-frame survey settings. To take advantage of extra information for minority populations in the Marketing Systems Group database, we propose a novel optimal oversampling strategy that minimizes the domain variance subject to total cost restriction or vice versa. We further extend the method to oversample multiple minorities simultaneously. Empirical study using a population-based community survey shows the benefits of our proposed methods compared with traditional methods in terms of statistical efficiency and cost balance.

Communication Strategies in Mohs Micrographic Surgery: A Survey of Methods, Time Savings, and Perceived Patient Satisfaction

Mohs micrographic surgery (MMS) entails multiple time-consuming surgical and histological examinations for each patient. Efficient communication is key in improving clinic flow, and we surveyed members of the American College of Mohs Surgery to evaluate the efficacy of different techniques utilized by Mohs surgeons across the nation.

Parental disclosure from the perspective of late adolescents

Although parental relations are considered influential in adolescents' transition to adulthood, we know little about lessons that parents provide through self-disclosure. This study explored the content and extent of parents' disclosure, from the perspective of their children in late adolescence. College students were asked to indicate how much each parent had shared about various matters in their lives, to characterize the quality of each parent's disclosure to them and their disclosure to each parent, and to recall each parent's most meaningful, awkward and first disclosures. Based on previous research regarding adolescents' disclosure to parents, gender differences in disclosure, and reciprocity of disclosure, it was predicted that greater disclosure would be exchanged with mothers than with fathers. Results confirmed initial predictions, indicated some of the functions that parental disclosure may serve, and suggested a model by which intra-family disclosure might evolve.