Racial differences in parent response to COVID schooling policies

This paper examines whether school COVID-19 policies influenced enrollment differently by student age and race/ethnicity. Unlike much prior research, we i) analyze enrollments for virtually the entire U.S. public school population for both the 2020-2021 and 2021-2022 school years, ii) compare enrollment trends within districts in order to isolate subgroup heterogeneity from district characteristics, and iii) account for district selection into preferred learning modes. Analyzing data on over 9,000 districts that serve more than 90% of public school students in the United States, we find enrollment responses to COVID policies differed notably. We find that White enrollments declined more than Black, Hispanic, and Asian enrollments in districts that started the 2020-2021 school year virtually, but in districts that started in-person the reverse was true: Non-White enrollments declined more than White enrollments. Moreover, Black, Hispanic, and Asian families responded more than White families to higher COVID-19 death rates in the months preceding the start of the 2021 school year. In 2021-2022, enrollment differences by the previous year's learning mode persisted. Racial/ethnic differences did not vary by whether the district required masking in classrooms. These findings are consistent with the greater risk faced by communities of color during the pandemic and demonstrate an additional source of disparate impact from COVID policies.

Decision Making for Patients With Severe Dementia Versus Normal Cognition Near the End of Life

Background and Objectives

The clinical progression of severe dementia frequently leads to situations where surrogate decision makers must quickly make choices about potentially burdensome treatments that offer limited clinical benefit. We examined whether the number of decision makers and their access to advance directives were related to treatment choice for patients with severe dementia in comparison to those with normal cognition.

Research Design and Methods

We retrospectively linked survey responses about end-of-life treatment decisions to Medicare claims for Health and Retirement Study respondents dying between 2002 and 2015 whose next-of-kin reported a need for surrogate decision making. We estimated multivariable logistic regression models to study measures of aggressive care in the last 6 months of life; in-hospital death, burdensome transfers, and burdensome treatments.

Results

Compared to patients who were cognitively normal near the end of life (n = 1 198), patients with severe dementia (n = 722) were less likely to experience burdensome treatments (18% [95% confidence interval {CI} 14-21] vs 32% [95% CI 29-35]), burdensome transfers (20% [95% CI 17-24] vs 30% [95% CI 27-33]), and in-hospital death (24% [95% CI 20-28] vs 30% [95% CI 26-33]) when surrogates were involved. Rates of burdensome treatments, transfers, or in-hospital death for decedents with severe dementia did not vary with single versus multiple decision makers or when decision makers were informed by advance directives. However, among decedents with normal cognition, a single decision maker informed by an advance directive was associated with the lowest rates of burdensome treatments and in-hospital death.

Discussion and Implications

Surrogate decision makers made similar choices around end-of-life care for patients with severe dementia regardless of the number of decision makers and availability of advance directives. However, both advance directives and single decision makers were associated with less aggressive care for cognitively normal decedents.

Does it Matter Who Decides? Outcomes of Surrogate Decision-Making for Community-Dwelling, Cognitively Impaired Older Adults Near the End of Life

CONTEXT

Cognitively impaired older adults frequently need surrogate decision-making near the end-of-life. It is unknown whether differences in the surrogate's relationship to the decedent are associated with different end-of-life treatment choices.

OBJECTIVES

To describe differences in end-of-life care for community dwelling, cognitively impaired older adults when children and spouses are involved in decision-making.

METHODS

Retrospective observational study.

RESULTS

Among 742 community-dwelling adults with cognitive impairment (mild cognitive impairment or dementia) prior to death, children participated in end-of-life decisions for 615 patients (83%) and spouses participated in decisions for 258 patients (35%), with both children and spouses participating for 131 patients (18%). When controlling for demographic characteristics, decedents with only a spouse decision-maker were less likely to undergo a life-sustaining treatment than decedents with only children decision-makers (P < 0.05). There was no difference in the probability of in-hospital death or burdensome transfers across facilities across decedent-decision-maker relationships. Differences in rates of life-sustaining treatment were greater when we restricted to decedents with dementia.

CONCLUSION

Decedents with cognitive impairment or dementia were less likely to receive life-sustaining treatments when spouses versus children were involved with end-of-life treatment decisions but were no less likely to experience other measures of potentially burdensome end-of-life care.

Identifying Cohabiting Couples in Administrative Data: Evidence from Medicare Address Data

Marital status is recognized as an important social determinant of health, income, and social support, but is rarely available in administrative data. We assessed the feasibility of using exact address data and zip code history to identify cohabiting couples using the 2018 Medicare Vital Status file and ZIP codes in the 2011-2014 Master Beneficiary Summary Files. Medicare beneficiaries meeting our algorithm displayed characteristics consistent with assortative mating and resembled known married couples in the Health and Retirement Study linked to Medicare claims. Address information represents a promising strategy for identifying cohabiting couples in administrative data including healthcare claims and other data types.