The ability to access high quality health care services is a necessary, but not sufficient means of improving the health status of individuals. Race, ethnicity, health literacy, nutritious dietary patterns, being physically fit, the opportunity to live in safe neighborhoods, and the availability of jobs that provide a satisfactory level of income are among the many key factors that have an impact on health. Government programs, such as Medicare have strict limits defined statutorily that determine the scope of services that can be offered to beneficiaries. As discussed below, a recent speech on November 14, 2018 at the Hatch Foundation for Civility and Solutions in Washington, DC by Alex Azar, Secretary of the Department of Health and Human Services (HHS), provides a possible way of expanding services to include a greater emphasis on addressing social determinants of health.

Also, not only do technology developments play a major role in contributing to a constant rate of growth in the cost of health care, they complement efforts to enhance service quality. Telehealth, artificial intelligence (AI), and machine learning are key items as described below.

Addressing Social Determinants Of Health In The U.S. Through Medicare Advantage
HHS Secretary Alex Azar on November 14 stated that the department he oversees is logically positioned to think of healthcare as broad and interconnected with other needs. "Social determinants would be important to HHS even if all we did was healthcare services, but at HHS, we cover health and human services, all under one roof. In our very name and structure, we are set up to think about all the needs of vulnerable Americans, not just their healthcare needs. But what if we went beyond connections and referrals? What if we provided solutions for the whole person, including addressing housing, nutrition and other social needs? What if we gave organizations more flexibility so they could pay a beneficiary’s rent if they were in unstable housing, or make sure that a diabetic had access to, and could afford, nutritious food?” One of the best ways to do so is through Medicare Advantage, which is Part C of the Medicare program. Beginning next year, plans under Part C will be allowed to pay for a wider array of health-related benefits, such as transportation and home health visits.

Telemedicine Usage Increases In Medicare
A report sent to Congress on November 16, 2018 by the Centers for Medicare & Medicaid Services (CMS) describes an increase in telemedicine usage of about 50% in fee-for-service Medicare from 2014 to 2016. Telehealth is emerging as a tool with the potential to improve access to care, potentially reduce costs, and enhance patient satisfaction. Medicare and other telehealth services are being used currently for a range of services in rural communities, allowing patients to connect directly with health care providers and support these providers with clinical decision-making. Moreover, telestroke services connect neurologists to rural patients and providers to provide remote diagnoses and treatment recommendations. Research indicates that telepsychiatry can reduce disparities in access to psychiatric care. When delivered remotely, psychiatric care increases the chances that individuals living in rural communities will be able to access professionals who are culturally and linguistically competent.

Bioethics Influence On Artificial Intelligence and Machine Learning
According to an essay in the September/October 2018 issue of The Hastings Center Report, artificial intelligence (AI) and machine learning have the potential to revolutionize the delivery of health care. AI systems generate conclusions by applying complex algorithms to enormous data sets by replacing human reasoning with rote‐like analysis. Machine learning “trains” or “teaches” the algorithm so that it can “learn” and eventually perform its given tasks automatically. Empirical research has demonstrated that the latest generation of AI and machine learning applications not only can identity at‐risk patients, but even achieve better diagnostic performance than expert physicians can. An example of why it is important to develop ethical frameworks that can support novel technologies has to do with the possibility that schizophrenia is over diagnosed in black patients. For a decision model to make correct predictions about the diagnosis or prognosis of these individuals seeking mental health care, factors such as their social history, their access to providers or hospitals, and the quality of hospitals available to this patient population play an important role. If a machine learning‐based decision support system continually is exposed to this ailment in black patients without appropriate context, then the algorithm will wrongly “teach” the decision system that schizophrenia is common in these patients.

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