The U.S. health care system has grown to be an increasingly complex machinery. It transcends policy-making, infrastructure, economy, science, and sociology. The complexity of the field compels systematic solutions that are not necessarily limited to medicine as such. The problem is that health care needs arise from factors such as the environment or social inequality and, thus, the solution to them cannot be drawn from medical institutions alone.
Among other things, two structural aspects of the health care system are in dire need for reform. First, we need a more effective research & development that satisfy increasing health needs. Second, the current U.S. system needs to be redesigned to account for the peculiarities of community and population health.
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With regard to the research & development redesigning, the issue lies in the fact that regulatory and infrastructure constraints are limiting and even impeding the implementation of science and technology advancements for the benefit of increasing the delivery of health care. In particular, the impediments occur for the development of new drugs. Businesses and professional working on their development tend to prioritize the economic side of research and act in accordance with the market situation. The neglecting of objective needs for a quick development of new more effective drugs, for instance, for cancerous disease, is often the consequence of this model.
The literature labels this gap between the innovative capability of American science and the health care system as an “interoperability constraint”. The solution must necessarily involve an increase in public investment, regulatory incentives for the implementation of scientific advancement in health care and re-focusing the education and training of research professionals on large public health needs rather than pharma business objectives. (Dzau et. al., 2016)
The second reform priority is emphasizing the role of community and population health in the system design. Unfortunately, health care and public health policy-making are still not always reconciled in one linear process. Public health data and analysis are not put to a good use in the delivery of health care, especially for tackling diseases related to environmental factors. The typical examples are the unfortunate relationship between air pollution and risks of cardiovascular and respiratory diseases. The air quality is thus the root of the problem that should be addressed by urban management, policy-makers, and even the NGO sector.
In a similar manner, some diseases can be prevented by social policy action. For instance, the research has shown that smoking is more prevalent among underprivileged social groups and poorly educated. (Kanjilal et. al., 2006) Thus, an important action point on preventing cardiovascular diseases and lung cancer must be implemented at the level of further limiting cigarettes availability. However, these steps must be implemented based on accurate public health data that would be organized by specific external factors and particular communities or population groups. In this context, the solution must include the development of a comprehensive set of health determinants that would be based on local data. Community- and population-level determinants would allow policy-makers and the health care system for modeling responses to social, environmental, infrastructural and other causes of shortcomings in the U.S. public health situation. In other words, we must start collecting and processing localized data on environmental and social factors that negatively affect public health with the view of mitigating those risks. (Goldman et. al., 2016)
