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Kevin Fiscella notes that, to date, progress in eliminating racial disparities has been slow. He calls for a comprehensive approach that goes beyond the narrow focus of current policy. Given the association between education and health, he advocates greater investments in early childhood education. In light of its broad geographic and demographic reach and role in preventing or delaying the onset of chronic disease, he also proposes to strengthen the delivery of primary care through the network of Federally Qualified Community Health Centers (FQHCs).

The role of gender in psychiatric disorders is not well understood, but several broad trends are known: while men and women experience psychiatric symptoms at roughly the same rate, women are more likely to experience depressive symptoms (Kessler et al., 1993) and men are more likely to experience substance use disorders (DHHS, 1999). However, women are more likely to use primary care services for mental health care than are men (Wells et al., 1986). Equally controversial and not well understood has been the differential responses to treatment interventions by gender (Kornstein, 1997). One recent study found that a depression intervention was more cost-effective for women than for men (Pyne et al., in press). Indeed, the study found that the intervention was essentially cost and outcome neutral for men, while women were found to have a cost-effectiveness ratio of over $5000 for each QALY saved.

Purpose: We estimate national health expenditures on prevention using precise definitions, a transparent methodology, and a subdivision of the estimates into components to aid researchers in applying their own concepts of prevention activities.

Methodology/Approach: We supplemented the National Health Expenditure Accounts (NHEA) with additional data to identify national spending on primary and secondary prevention for each year from 1996 to 2004 across eight spending categories.

Findings: We estimate that NHEA expenditures devoted to prevention grew from $83.2 billion in 1996 to $159.8 billion in 2004, in current dollars. As a share of NHEA, this represents an increase from 7.8 percent in 1996 to 8.6 percent in 2004. This share peaked at 9 percent in 2002 and then declined due to reductions in public health spending as a percent of NHEA between 2002 and 2004. Primary prevention represents about half the expenditures, consisting largely of public health expenditures – the largest prevention element.

Originality/Value of Paper: Our 2004 estimate that 8.6 percent of NHEA goes to prevention is nearly three times as large as the commonly cited figure of 3 percent, but depends on the definitions used: our estimate falls to 8.1 percent when the research component is excluded, 5.1 percent when consideration is limited to primary prevention plus screening, 4.2 percent for primary prevention alone, and 2.8 percent if we count only public health expenditures. These findings should contribute to a more informed discussion of our nation's allocation of health care resources to prevention.

Several high-profile prescription drugs have been withdrawn from the U.S. market in the last decade, yet there is no direct evidence of how a prescription drug withdrawal affects consumers’ use of remaining drugs within the same therapeutic class. In theory, remaining drugs in the therapeutic class could enjoy competitive benefits or suffer negative spillovers from the withdrawal of a competing drug. Using the Medical Expenditure Panel Survey, we test for spillovers following prescription drug withdrawals in six therapeutic classes between 1997 and 2001. Results vary, but we find stronger evidence of negative spillovers than competitive benefits. We conclude with a discussion of the characteristics of drugs and classes that may influence how remaining drugs are affected by a withdrawal in the class.

The purpose of this paper is to examine the impact of pharmaceutical innovation on the longevity of Australians. The approach utilized involves estimation of difference-in-differences models using longitudinal, disease-level data during the period 1995–2003 to determine whether the diseases that had above-average increases in mean vintage (FDA approval year) of drugs had above-average reductions in mortality. Our findings are that the mean age at death increased more for diseases with larger increases in mean drug vintage. A 5-year increase in mean drug vintage is estimated to increase mean age at death by almost 11 months. The number of years of potential life lost before the ages of 65 and 70 (but not before age 75) was reduced by use of newer drugs. During the period 1995–2003, mean age at death increased by about 2.0 years, from 74.4 to 76.4. The estimates imply that, in the absence of any increase in drug vintage, mean age at death would have increased by only 0.7 years. The increase in drug vintage accounts for about 65% of the total increase in mean age at death. Estimated cost per life-year gained from using newer drugs is $10,585. An estimate by previous investigators of the value of a statistical Australian life-year ($70,618) is 6.7 times as large. We acknowledge potential limitations of this study by discussing several reasons why our estimate of the cost per life-year gained from using newer drugs could be too high or low. The value of this paper's evidence is primarily due to the government's Pharmaceutical Benefits Scheme: Australia has much better data on drug utilization than most other countries.

An important current trend in health care is the move toward personalized medicine. Personalized medicine includes diagnostic and therapeutic interventions, with risk defined through genetics. The key paradigm shift brought about by the advent of personalized medicine is the increased use of in vitro genomic diagnostics. These tests offer the potential of being able to predict which patients are likely to respond to a particular drug, or which patients are likely to develop adverse reactions to a drug. The focus of this paper is the use of genomic diagnostics, and how the increasing development and translation into clinical practice of diagnostic – drug combination products will be adopted into health care delivery. The meaning of value and how to measure it is considered from different perspectives. A novel framework for evaluating the value of genomic diagnostics is proposed. Finally, the implications for regulatory approval and policy are discussed using an illustrative case study.