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This program promotes teaching and research on issues related to pharmaceuticals and the pharmaceutical industry. It trains professionals seeking careers in the area, and supports the work of industry and government.

Cover page of The Productivity of Health Care and Pharmaceuticals: An International Comparison

The Productivity of Health Care and Pharmaceuticals: An International Comparison

(1996)

Much work has been done analyzing the determinants of health care expenditures. Much less effort has been devoted to analyzing the determinants of health itself. The focus of the analysis presented here is the production of health, with special attention paid to disaggregating health into pharmaceuticals and other health care. We also analyze the effects that wealth and certain lifestyle factors have on health.

Researchers who have analyzed the determinants of health across geographic units have found certain striking and consistent results. First, basic public health services, in the form of potable water and sanitation services, provide the biggest payoffs in decreased mortality for all age groups. Second, the expansion of health care services does not improve mortality to anywhere near the extent that public health infrastructure development does, if at all. Some researchers have even found positive relationships between some health care inputs and mortality. The results on income and wealth have been more mixed. In studies which have analyzed developing countries, researchers have found that higher incomes are negatively related to mortality. Other researchers have found exactly the opposite result when they have limited their samples to rich countries and/or regions thereof. Many researchers have also found that lifestyle factors such as nutrition, and cigarette and alcohol consumption, are important determinants of health.

Very few studies have estimated the effects of pharmaceutical consumption on mortality rates either directly or indirectly. The studies which have dealt with this directly in an international comparison context have had serious flaws. Some micro studies and many studies of restricted formularies in the United States Medicaid program have provided indirect evidence that pharmaceutical consumption has a positive impact on health.

To investigate whether such an effect could be found in an analysis of international data, we analyze a sample consisting of 21 OECD (Organization for Economic Cooperation and Development) countries as of the early 1990s. We convert pharmaceutical and total health care expenditures to U.S. dollars using purchasing power parity exchange rates for pharmaceuticals and health care, respectively. The purchasing power parities were provided by the OECD. Although other conversions are available for a limited number of countries, the measures of pharmaceutical and other health care consumption used here are the best available for a large number of OECD countries. We measure each country's health crudely, but objectively, using life expectancies at birth, at age 40, and at age 60, along with infant mortality.

The analysis consists of various multivariate regressions in which we estimate production functions for health. A functional form is used that allows for diminishing returns in each of the inputs in the production functions. The explanatory variables in each regression include pharmaceutical consumption, other health care consumption, gross domestic product, alcohol consumption, cigarette consumption, and richness of diet.

In our analysis, we find that pharmaceutical consumption has a positive and significant (both statistically and economically) effect on remaining life expectancy at age 40 and at age 60. It has a small, positive and statistically insignificant effect on life expectancy at birth. The elasticities of pharmaceutical consumption on life expectancy are roughly 0.017 at age 40 and 0.040 at age 60. The estimates are also quite robust to small changes. In a sample comprised of only the 16 European countries for which complete data were available, these elasticities were higher (0.023 for age forty and 0.050 for age sixty) and pharmaceutical consumption even had a small positive significant effect on life expectancy at birth. Pharmaceutical consumption appears to have no significant effect on infant mortality, although it appears that, controlling for lifestyle factors, increased pharmaceutical consumption may even be related to slightly increased infant mortality. Unfortunately, the infant mortality model is not robust to small changes, which does not inspire much confidence.

We also find that gross domestic product has a positive and significant effect on life expectancies at the ages of 40 and 60, although this effect is not present in the European-only sample. The results from the infant mortality regressions are mixed. It also appears that non-pharmaceutical health care consumption has no measurable effect on life expectancy, either at birth, at age 40, or at age 60. However, in one specification, we find that it has a negative effect on infant mortality. Again, where infant mortality is concerned, the results are mixed and not robust.

The lifestyle variable with the biggest effect on health is dietary richness, measured by the consumption of animal fat. Increased richness of diet improves mortality up to a point but the impact becomes negative as a diet becomes very rich. This result is consistent with the idea of the epidemiological transition: the idea that at low nutritional levels, enriching a diet allows one to better fight off infections, but that at high nutritional levels, enriching a diet leads to a greater incidence of degenerative diseases such as cancer and heart disease. This result is slightly surprising. One might have thought that the OECD countries were wealthy enough that nutrition, in this basic sense, would not be an issue.

We believe that this study will add to the debate over how OECD governments should allocate resources both among different health care goods and services and between health care and other goods and services. It improves on much of the existing literature in that it uses better measures of pharmaceutical and other health care consumption and uses a functional form that allows for diminishing returns. The results have been surprising, but they have also been fairly robust in the life expectancy models. The final conclusion is that increased pharmaceutical consumption helps improve mortality outcomes, especially for those at middle age and beyond.

Cover page of Drug Evaluations: Type I vs. Type II Errors

Drug Evaluations: Type I vs. Type II Errors

(1996)

Drug testing in the United States is currently biased toward the minimization of "Type I" error, that is, toward minimizing the chance of approving drugs that are unsafe or ineffective. This regulatory focus of the Food and Drug Administration (FDA) ignores the potential for committing the alternative "Type II" error, that is, the error of not approving drugs that are, in fact, safe and effective. Such Type II errors can result in the loss of significant benefits to society when the sale of drugs that are safe and effective is prohibited. The present drug approval system puts enormous stress on Type I errors and largely ignores Type II errors, thereby raising the cost of drug testing and delaying the availability of safe and effective drugs. A more balanced set of FDA drug approval standards, accounting for the consequences of both Type I and Type II errors, could result in better outcomes, as compared to the present system.