Infant Moratality
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Elijah J. Brunson
PA 510
Infant Moratlity
How does the United States health care system fare when compared to the rest of the industrialized world? This is an important question. Accurately measuring our health care system relative to those of other nations can yield insight into the types of health care policies America should pursue. Why Life Expectancy and Infant Mortality are Popular Measures Type in the terms “life expectancy,” “infant mortality” and “health care” into the popular search engine Google, and it will yield about 449,000 results. Clearly, linking these two measures to health care is very popular. It is easy to understand why.Life expectancy and infant mortality are powerful tools for those who support some form of socialized medicine. On those measures the United States fares worse than all other industrialized nations. Most other industrialized nations have some form of government-run, universal health insurance. Thus, the reasoning goes, Americas inferior performance on life expectancy and infant mortality is due to its heavy reliance on a system of private sector care. The only measures used to compare the different nations were, not surprisingly, life expectancy and infant mortality. America spent more on health care but got less return than countries that had some form of universal health insurance. The high costs and poor outcomes seem to stem from inefficiencies that are unique to the U.S. health care system. (Measuring the Health Care Systems)Any statistic that accurately measures health-care systems across nations must satisfy three criteria. First, the statistic must assume actual interaction with the health care system. Second, it must measure a phenomenon that the health care system can actually affect. Finally, the statistic must be collected consistently across nations.
Under the first criterion, the phenomenon being measured must be one in which the individual actually has contact with the health care system. More specifically, he must have contact with a health care professional, be it a doctor, nurse, lab technician, etc. Some statistics may assume interaction with the health care system, but the phenomena they measure are not ones on which the health care system can have any meaningful impact. Take, for example, the rate of cancer incidence. While this statistic assumes interaction with the health care system (an incidence of cancer cannot be known without the diagnosis of a health care professional), there is little a health care system can do about the rate of cancer. Rather, cancer incidence is affected by factors such as genetics, diet, lifestyle, etc., over which the health care system has no control. Thus, to be an adequate measure of the effectiveness of a health care system, a statistic must measure a phenomenon that health care professionals can actually affect.Finally, a statistic must be collected consistently across nations. While this seems simple in theory, in practice it is quite complicated. Nations use diverse definitions of health phenomena. This leads to some nations excluding a segment of their populations from the collection of a statistic while other nations include those segments. In such circumstances, cross-national comparisons are largely meaningless. Thus, for health care systems across countries to be meaningful, there should be little to no variation in how statistics are collected. Both life expectancy and infant mortality are poor measures of a health care system because each fails to satisfy at least one of the above criteria. (Life Expectancy )Life expectancy is a poor statistic for determining the efficacy of a health care system because it fails the first criterion of assuming interaction with the health care system. For example, open any newspaper and, chances are, there are stories about people who die “in their sleep,” in a car accident or of some medical ailment before an ambulance ever arrives. If an individual dies with no interaction with the health care system, then his death tells us little about the quality of a health care system. Yet all such deaths are computed into the life expectancy statistic.Life expectancy also largely violates the second criterion – a health care system has, at most, minimal impact on longevity. There is no relationship between life expectancy and spending on health care. Greece, the country that spends the least per capita on health care, has higher life expectancy than seven other countries, including Belgium, Denmark, Finland, Germany, Netherlands, the United Kingdom and the United States. Spain, which spends the second least per capita on health care, has higher life expectancy than ten other countries that spend more.More robust statistical analysis confirms that health care spending is not related to life expectancy. Studies of multiple countries using regression analysis found no significant relationship between life expectancy and the number of physicians and hospital beds per 100,000 population or health care expenditures as a percentage of GDP. Rather, life expectancy was associated with factors such as sanitation, clean water, income, and literacy rate. A recent study examined cross-national data from 1980 to 1998. Indeed, GDP per capita is one of the more consistent predictors of life expectancy.Yet the United States has the highest GDP per capita in the world, so why does it have a life expectancy lower than most of the industrialized world? The primary reason is that the U.S. is ethnically a far more diverse nation than most other industrialized nations. Factors associated with different ethnic backgrounds – culture, diet, etc. – can have a substantial impact on life expectancy. Comparisons of distinct ethnic populations in the U.S. with their country of origin find similar rates of life expectancy. For example, Japanese-Americans have an average life expectancy similar to that