PHARMACEUTICAL INNOVATION: Model specification and estimation 5

The dependent variable in eq. (1) is the log-change (growth rate) of mortality, In (MORTf.k / MORTf). The variance of the dependent variable is strongly inversely related to the average size of the disease, (MORTt_k + MORTf) / 2. The growth rates of diseases affecting a relatively small number of people are likely to be much farther away (in both directions) from the mean than those of major diseases. To correct for heteroskedasticity, the equation is estimated via weighted least squares, where the weight is (MORT^j^ + MORTf) / 2. Diseases that are responsible for larger average numbers of deaths or life-years lost are given more weight.
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PHARMACEUTICAL INNOVATION: Model specification and estimation 4

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In the course of the approval process, the FDA classifies drugs into two categories: “priority review drugs”—drugs that appear to represent an advance over available therapy—and “standard review drugs”—drugs that appear to have therapeutic qualities similar to those of already marketed drugs.  One might reasonably hypothesize that it is only new priority drugs that have a significant impact on mortality, or at least that their effect is much larger than that of new standard drugs. We estimate versions of eq. (1) in which DRUGSt_k,t’s defined as the number of priority drugs prescribed in year t that received FDA approval in year t-k or later, as well as versions in which DRUGS{-k,t is defined as the total number of (priority plus standard) drugs prescribed in year t that received FDA approval in year t-k or later. (In both cases DRUGS tls defined as the total number of drugs (priority plus standard) prescribed in year t.)

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PHARMACEUTICAL INNOVATION: Model specification and estimation 2

We will estimate the model for several alternative definitions of MORT and of DRUGSj-кд, and two sample periods. The mortality variables we will analyze are^: mean age at death, life-years lost before age 65 by all decedents under 65, and by decedents in three age categories: age 0-1, age 1-25, and age 25-65. Disaggregation of total LYL into three age categories enables us to distinguish the impact of pharmaceutical innovation on infant mortality from its impact on other premature mortality. Each record in the Mortality Detail file includes a single International Classification of Diseases, Ninth Revision (ICD9) code to indicate the cause of death. We used this code to calculate the various mortality statistics by 2-digit ICD9 disease, by year.
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PHARMACEUTICAL INNOVATION: Model specification and estimation 3

To calculate the fraction of drugs that were approved by the FDA after a certain date, we linked these data to a list of all New Drug Applications since 1939 provided by the FDA. Both files included the scientific name of the drug, and the FDA file included the date the drug was first approved as a new molecular entity (NME).
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PHARMACEUTICAL INNOVATION: Previous evidence 3

Per capita medical expenditures vary considerably across regions. For example, average Medicare expenditures on elderly patients in the last six months of life are twice as high in Miami as they are in Minneapolis, and the average number of visits to specialists is five times as high. However intensive econometric analysis provided “no evidence that higher levels of spending translates into extended survival.
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PHARMACEUTICAL INNOVATION: Previous evidence 2

Bioscience research
Since 1960, vaccines have greatly reduced the incidence of childhood diseases— many of which once killed or disabled thousands of American children. Likewise, vaccines for Hepatitis В introduced during the 1980s now protect a new generation of American children from a leading cause of liver disease.
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PHARMACEUTICAL INNOVATION: Previous evidence

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PhARMA (1998) provides an informal, anecdotal account of the contribution of drug innovation to medical progress in this century. We simply quote their account here:

Antibiotics and vaccines played a major role in the near eradication of major diseases of the 1920s, including syphilis, diphtheria, whooping cough, measles, and polio. Since 1920, the combined death rate from influenza and pneumonia has been reduced by 85 percent. Despite a recent resurgence of tuberculosis (ТВ) among the homeless and immuno-suppressed populations, antibiotics have reduced the number of ТВ deaths to one tenth the levels experienced in the 1960s. Before antibiotics, the typical ТВ patient was forced to spend three to four years in a sanitarium and faced a 30 to 50 percent chance of death. Today most patients can recover in 6 to 12 months given the full and proper course of antibiotics.
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PHARMACEUTICAL INNOVATION: Introdution 4

We obtain data on the utilization (market shares) of various drugs from the 1980 and 1991 National Ambulatory Medical Care Surveys (NAMCS), which survey doctor-office visits, and the 1993 National Hospital Ambulatory Medical Care Survey (NHAMCS), which surveys visits to hospital outpatient departments and emergency departments.^ These surveys enable us to estimate the number of drug “mentions” (prescriptions), by molecule, in 1980 and subsequent years. By combining the FDA and NAMCS data, 1 can calculate disease-specific measures of pharmaceutical innovation, i.e. quantify the amount of innovation relevant to each disease, since NAMCS reveals the relative frequency with which each drug is used for each disease.
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PHARMACEUTICAL INNOVATION: Introdution 3

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The purpose of this paper is to perform detailed econometric tests of the hypothesis that the decline in mortality documented above is due, to an important extent, to the introduction and use of new drugs, i.e. to “changes in pharmaceutical technology.” The creation and Food and Drug Administration approval of new drugs requires substantial investment in research and development (R&D): the Pharmaceutical Research and Manufacturers Association (PhARMA) estimates that the average pre-tax R&D cost of developing a new molecular entity was $359 million in 1990. Numerous econometric studies have shown that R&D investment has a significant positive impact on the growth in annual per capita income (уд), or on total factor productivity growth.3 And while there is considerable anecdotal and case-study evidence suggesting that pharmaceutical innovation has made important contributions to the other source of lifetime income growth—increases in life expectancy—there is little systematic econometric evidence on this issue. This paper is an attempt to fill this gap in the literature. payday loans with no credit check
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