Obamacare: Doctors Turning Away From Individual Treatment in Favor of “Population Care”
Obamacare treats not for the patient in particular, but for the patient on average, globally, or in the abstract
by Michel Accad | Mises.org | May 18, 2015

The economics profession today continues to face mounting criticism for its failure to predict and explain economic crises.

According to Austrian school critics of Keynesian and neoclassical methods, this failure is in large part due to a foolish determination to bring into economics the mathematical precision of the physical sciences. To achieve this precision, neo-classical economists disproportionately focus their inquiry on global measures of economic activity: gross national product, aggregate demand, global supplies of money, goods, or labor, and other variables that lend themselves to quantification and numerical modeling. Lost in mainstream economic analysis is the attention due to the individual economic actor who, by virtue of his or her power of self-determination, is ill-suited for the equation or the graph.

A similar love affair with quantitative methods has rapidly taken over the medical field over the last several decades. As in mainstream economics, equations and predictions can only come about when one turns one’s attention away from the individual patient to focus instead on the aggregated group, or population, as the prime target of analysis and intervention. Thus, population medicine is an apt term to describe the discipline that seeks to mathematize medical practice by caring not for the patient in particular, but for the patient on average, globally, or in the abstract.

For the promoters of population medicine, the individual clinical interaction is of no interest. It is dismissed as quaint, anecdotal, and inconsequential to a proper understanding of health issues. Instead, the data of interest are those garnered from large epidemiological studies and clinical trials. From such research, one can derive “risk factors” for disease, elucidate the “determinants of health,” and promote prescriptive measures in wide swaths.

Advancing the convenient fiction that whatever is good for the group must be good for the individual, population medicine has become an indispensable framework of analysis for the central planning of health care. Accordingly, government agencies can now avail themselves of the findings of this discipline to decide which services, drugs, and interventions should be paid for and promoted, and which must be deemed unnecessary or even fraudulent. The decisions can thus be rendered under cover of “scientific proof.”

An example of activities promoted by population medicine is the “risk calculation,” which doctors are expected to embrace, or else face penalties for practicing outside of the desired norm. Risk calculation involves inputting a handful of patient factors — age, weight, cholesterol, blood pressure, and the like — into a formula to obtain the patient’s “personal risk” of dying or suffering a specific outcome in the future. Based on this mathematical insight, an intervention is prescribed. A patient can thus enjoy the privilege of being treated like a number not just figuratively, but quite literally.

Needless to say, the architects of population medicine overlook that the concept of “personal risk” is rather devoid of meaning, as statistician Richard von Mises explained many decades ago. Willful or naïve, this oversight is turning medicine into an enormous risk management enterprise aimed at solving an impossible game of health optimization.

According to the wisdom of population medicine, for example, to be healthy is to confine our weight, our blood cholesterol, or our blood sugar to an ever-more narrow range of “normal values” defined — and repeatedly revised — not on the basis of any physiological reality, but by the will of committees of medical technocrats. With each new revision in the definitions of what constitutes a “normal” blood pressure, blood cholesterol, or blood sugar, millions of hapless citizens whose numbers happen to fall outside the desired range are instantly turned into patients, to the great delight of the pharmaceutical industry.
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Population medicine ambitiously aims to improve the health of entire nations. To do so, it proceeds to sketch an ever-more quantified but all-the-more unrealistic portrait of the human being, to be analyzed by those who enjoy directing medical care from the remote comfort of their academic or governmental chairs.

http://www.infowars.com/obamacare-doctor...opulation-care/


Technocrats in action. One of the major problems of using mathematical formulas and computer programs to determine what provides for "best outcomes' not directly addressed in this article is not including variables the technocrats deem irrelevant.

An example would be the popular practice of assuming a new medicine / procedure / diet is safe because 'there have been no reported negative reactions'. What one is not told no one looked for said reports.

Another example is assuming that what is true for a small sample of people is true for everyone. You know what they say about that word assume.

Quote: truthkeeper wrote in post #2

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