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Background: Governance, health financing, and service delivery are critical elements of health systems for provision of robust and sustainable chronic disease care. We leveraged the third iteration of the International Society of Nephrology Global Kidney Health Atlas (ISN-GKHA) to evaluate oversight and financing for kidney care worldwide., Methods: A survey was administered to stakeholders from countries affiliated with the ISN from July to September 2022. We evaluated funding models utilized for reimbursement of medications, services for the management of chronic kidney disease, and provision of kidney replacement therapy (KRT). We also assessed oversight structures for the delivery of kidney care., Results: Overall, 167 of the 192 countries and territories contacted responded to the survey, representing 97.4% of the global population. High-income countries tended to use public funding to reimburse all categories of kidney care in comparison with low-income countries (LICs) and lower-middle income countries (LMICs). In countries where public funding for KRT was available, 78% provided universal health coverage. The proportion of countries that used public funding to fully reimburse care varied for non-dialysis chronic kidney disease (27%), dialysis for acute kidney injury (either hemodialysis or peritoneal dialysis) (44%), chronic hemodialysis (45%), chronic peritoneal dialysis (42%), and kidney transplant medications (36%). Oversight for kidney care was provided at a national level in 63% of countries, and at a state/provincial level in 28% of countries., Conclusion: This study demonstrated significant gaps in universal care coverage, and in oversight and financing structures for kidney care, particularly in in LICs and LMICs., (© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.)

Background and Objectives: In 2022, 239 New York state long-term care facilities (LTCFs) challenged a "Safe Staffing" law in court. Our study compares LTCFs involved and not involved in the lawsuit, testing for differences in staffing measures and resident outcomes during the first year of the coronavirus disease 2019 (COVID-19) pandemic., Research Design and Methods: New York LTCF-level data were obtained from the Centers for Medicare and Medicaid Services 2019 organization and 2020 COVID-19 data files. These data were then linked to data from the Long-Term Care Community Coalition, which identified the LTCFs involved in the "Safe Staffing" lawsuit. We first tested for differences in reported 2019 staffing levels by lawsuit involvement. Second, we specified "Doubly Robust" regression models to test if lawsuit involvement was associated with differences in resident COVID-19 infections, COVID-19 deaths, and overall mortality., Results: LTCFs involved in the lawsuit reported lower staff ratings and fewer staffing hours compared to LTCFs not involved in the lawsuit. Despite finding higher rates of admissions with COVID-19 in LTCFs involved in the lawsuit, we did not find that COVID-19 infections, COVID-19 deaths, or overall mortality differed by lawsuit involvement., Discussion and Implications: LTCFs involved in the lawsuit were deemed by policymakers as reducing staff, earning excess profits, and placing residents at risk. While these LTCFs reported lower staffing levels, we observed no differences in resident outcomes during the first year of the COVID-19 pandemic. Researchers and policymakers should develop more nuanced perspectives concerning the relationship among LTCF staffing, outcomes, and organizational profitability., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The development of autonomous artificial intelligence (A-AI) products in health care raises novel regulatory challenges, including how to ensure their safety and efficacy in real-world settings. Supplementing a device-centered regulatory scheme with a regulatory scheme that considers A-AI products as a 'physician extender' may improve the real-world monitoring of these technologies and produce other benefits, such as increased access to the services offered by these products. In this article, we review the three approaches to the oversight of nurse practitioners, one type of physician extender, in the USA and extrapolate these approaches to produce a framework for the oversight of A-AI products. Under the framework, the US Food and Drug Administration would evaluate A-AI products and determine whether they are allowed to operate independently of physician oversight; required to operate under some physician oversight via a 'collaborative protocol' model; or required to operate under direct physician oversight via a 'supervisory protocol' model., (© The Author(s) 2022. Published by Oxford University Press on behalf of Duke University School of Law, Harvard Law School, Oxford University Press, and Stanford Law School. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: No potential conflict of interest was reported by the authors.

First introduced in 2011, the Synthetic Yeast Genome (Sc2.0) PROJECT is a large international synthetic genomics project that will culminate in the first eukaryotic cell (Saccharomyces cerevisiae) with a fully synthetic genome. With collaborators from across the globe and from a range of institutions spanning from do-it-yourself biology (DIYbio) to commercial enterprises, it is important that all scientists working on this project are cognizant of the ethical and policy issues associated with this field of research and operate under a common set of principles. In this commentary, we survey the current ethics and regulatory landscape of synthetic biology and present the Sc2.0 Statement of Ethics and Governance to which all members of the project adhere. This statement focuses on four aspects of the Sc2.0 PROJECT: societal benefit, intellectual property, safety, and self-governance. We propose that such project-level agreements are an important, valuable, and flexible model of self-regulation for similar global, large-scale synthetic biology projects in order to maximize the benefits and minimize potential harms., (Copyright © 2015 by the Genetics Society of America.)