Geological Observatory of Coldigioco

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    Order Denying Confirmation of Eighth Amended Plan

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    [024] Excel Sheet Step 7 Sub-Step 7A Sheet 1 of 1 Allocation of Purchase Price

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    Highlighting State Innovation to Close Coverage Gaps in Perinatal Care for Noncitizens

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    Under the Consolidated Appropriations Act of 2023, states are now beginning to disenroll individuals newly ineligible for Medicaid, whose coverage had been extended under COVID-19 pandemic-era rules. Commentators across the political spectrum emphasize the need to pursue alternative coverage options for vulnerable populations, including pregnant or postpartum individuals currently enrolled in Medicaid. Low-income individuals whose Medicaid eligibility was tied to postpartum care may initially bear the brunt of unwinding continuous enrollment. Given the national focus on addressing the maternal health crisis, states should consider closing significant coverage gaps in perinatal care for noncitizens. This Viewpoint highlights key steps that states could take to expand perinatal care coverage for noncitizens. The Biden administration aims to reduce gaps in coverage by encouraging states to elect to cover 12 months of postpartum care for Medicaid and CHIP beneficiaries through the American Rescue Plan Act of 2021 (ARPA)

    Prevention of Bias and Discrimination in Clinical Practice Algorithms

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    The Department of Health and Human Services (DHHS) recently announced its intention to combat the use of biased algorithms in health care decision-making and telehealth services.1 It is a fact that many clinical algorithms are flawed, either because they incorporate bias by design or because they are trained on biased data sets, and it is important to combat discrimination by algorithm. Some examples of discrimination by algorithm include a machine learning tool to diagnose Alzheimer disease that misdiagnoses patients who speak with certain accents; an algorithm designed to distinguish between malignant and benign moles that was trained mostly on light-skinned patients; and a scheduling tool whose algorithm encouraged double booking for lower-income patients because they are more likely to be a “no-show.

    The Shared Responsibility for Effective Supervisory Relationships in Law Practice

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    Interagency Dynamics in Matters of Health and Immigration

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    When Congress delegates authority to an executive agency, it tells us something important about the expertise that Congress wishes to harness in policymaking on an issue. In the legal literature on interagency dynamics and cooperation, issues at the nexus of health and immigration are largely understudied. This Article extends this literature by examining how delegations of authority on issues at the intersection of health and immigration influence policymaking. In an analysis of how administrative law models apply to three topics in the shared regulatory space of the Department of Health and Human Services (“HHS”) and the Department of Homeland Security (“DHS”), I demonstrate that health-related expertise is frequently marginalized rather than leveraged. Specifically, health policy expertise and priorities are subordinated to an administration’s immigration policy preferences, contravening Congress’s purpose in establishing related or overlapping jurisdictional assignments to HHS and DHS. Administrative law theories of shared regulatory space inadequately account for the predictable subordination of certain policy areas to others, as illustrated in this Article’s case studies on issues at the intersection of health and immigration. The routine capitulation of health policy actors to immigration enforcement actors reveals a need to extend the theory to accommodate this evidence. Although structural solutions may address some sources of health policy marginalization, effective dissemination of health related expertise in matters of health and immigration may require changing the way that political leaders prioritize health issues and acknowledge collateral consequences of immigration enforcement

    Dedication

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    Table of Contents

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    [001] Excel Sheet Step 1 Sub-Step 1A Sheet 1 of 3 FCFS for Year 1 2023.12.13

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