20 research outputs found
Resource requirements to fight HIV/AIDS in Latin America and the Caribbean.
OBJECTIVES: Economists and epidemiologists from 10 countries in Latin America and the Caribbean (LAC) reviewed the methods used to develop estimates for resource requirements to address HIV/AIDS prevention and care in low- and middle-income countries. METHODS: They applied their country-specific knowledge to re-estimate the costs, coverage, and capacity of their health and education systems to expand HIV/AIDS interventions by 2005. A discrepancy of 173 million US dollars exists between the model estimates and those of country specialists. RESULTS: The most important difference between the model estimates and those of country specialists was in the estimated future price of highly active antiretroviral therapy. To a large extent, the estimates of the model reflect the efficiency gains that could result from purchasing arrangements that lead LAC countries to lower prices for antiretroviral drugs. CONCLUSION: This preliminary exercise with 10 LAC countries confirmed the validity of the use of these estimates as tools at the international level, given current data limitations, both to guide the allocation of resources across diseases and countries, and for advocacy and resource mobilization. In addition, with the country revisions, these estimates have also been shown to be key tools for country-level strategic planning
Slogging and Stumbling Toward Social Justice in a Private Elementary School: The Complicated Case of St. Malachy
This case study examines St. Malachy, an urban Catholic elementary school primarily serving children traditionally marginalized by race, class, linguistic heritage, and disability. As a private school, St. Malachy serves the public good by recruiting and retaining such traditionally marginalized students. As empirical studies involving Catholic schools frequently juxtapose them with public schools, the author presents this examination from a different tack. Neither vilifying nor glorifying Catholic schooling, this study critically examines the pursuit of social justice in this school context. Data gathered through a 1-year study show that formal and informal leaders in St. Malachy adapted their governance, aggressively sought community resources, and focused their professional development to build the capacity to serve their increasingly pluralistic student population. The analysis confirms the deepening realization that striving toward social justice is a messy, contradictory, and complicated pursuit, and that schools in both public and private sectors are allies in this pursuit
Clinical, Legal, and Ethical Aspects of Artificial Intelligence–Assisted Conversational Agents in Health Care
Defining AMIA\u27s artificial intelligence principles
Recent advances in the science and technology of artificial intelligence (AI) and growing numbers of deployed AI systems in healthcare and other services have called attention to the need for ethical principles and governance. We define and provide a rationale for principles that should guide the commission, creation, implementation, maintenance, and retirement of AI systems as a foundation for governance throughout the lifecycle. Some principles are derived from the familiar requirements of practice and research in medicine and healthcare: beneficence, nonmaleficence, autonomy, and justice come first. A set of principles follow from the creation and engineering of AI systems: explainability of the technology in plain terms; interpretability, that is, plausible reasoning for decisions; fairness and absence of bias; dependability, including safe failure ; provision of an audit trail for decisions; and active management of the knowledge base to remain up to date and sensitive to any changes in the environment. In organizational terms, the principles require benevolence-aiming to do good through the use of AI; transparency, ensuring that all assumptions and potential conflicts of interest are declared; and accountability, including active oversight of AI systems and management of any risks that may arise. Particular attention is drawn to the case of vulnerable populations, where extreme care must be exercised. Finally, the principles emphasize the need for user education at all levels of engagement with AI and for continuing research into AI and its biomedical and healthcare applications