scholarly journals The Effect of Pharmaceutical Innovation on Longevity: Patient-Level Evidence from the 1996-2002 Medical Expenditure Panel Survey and Linked Mortality Public-Use Files

2012 ◽  
Author(s):  
Frank Lichtenberg
Keyword(s):  
Medical Expenditure Panel Survey ◽  
Pharmaceutical Innovation ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Patient Level ◽  
Public Use Files

scholarly journals The Effect of Pharmaceutical Innovation on Longevity: Patient Level Evidence from the 1996–2002 Medical Expenditure Panel Survey and Linked Mortality Public-use Files

2013 ◽  
Vol 16 (1) ◽  
pp. 1-33 ◽  
Author(s):  
Frank R. Lichtenberg
Keyword(s):  
Cost Effectiveness ◽  
Life Expectancy ◽  
Prescription Drugs ◽  
Medical Expenditure Panel Survey ◽  
Pharmaceutical Innovation ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Patient Level ◽  
The Mean ◽  
Public Use Files

Abstract This study uses patient-level data to analyze the effect of technological change embodied in pharmaceuticals on the longevity of elderly Americans. Previous patient-level studies could not control for important patient attributes such as education, income, and race; they did not provide estimates of the effect of using newer drugs on life expectancy, or of the overall cost-effectiveness of new drugs relative to old drugs; and they were not based on nationally representative samples of individuals. Our data, primarily derived from the Medical Expenditure Panel Survey and the Linked Mortality Public-use Files, enable us to overcome those limitations. We investigate the effect of the vintage (year of U.S. Food and Drug Administration approval) of the prescription drugs used by an individual on his or her survival and medical expenditure, controlling for a number of demographic characteristics and indicators and determinants of health status. When we control only for age, sex, and interview year, we estimate that a 1-year increase in drug vintage increases life expectancy by 0.52%. Controlling for a much more extensive set of other attributes (the mean year the person started taking his or her medications, and dummy variables for activity limitations, race, education, family income as a percent of the poverty line, insurance coverage, Census region, body mass index, smoking, and more than 100 medical conditions) has virtually no effect on the estimate of the effect of drug vintage on life expectancy. Between 1996 and 2003, the mean vintage of prescription drugs increased by 6.6 years. This is estimated to have increased the life expectancy of elderly Americans by 0.41–0.47 years. This suggests that not less than two-thirds of the 0.6-year increase in the life expectancy of elderly Americans during 1996–2003 was due to the increase in drug vintage. The 1996–2003 increase in drug vintage is also estimated to have increased annual drug expenditure per elderly American by $207, and annual total medical expenditure per elderly American by $218. This implies that the incremental cost-effectiveness ratio (cost per life-year gained) of pharmaceutical innovation was about $12,900. This estimate of the cost per life-year gained from the use of newer drugs is a small fraction of leading economists’ estimates of the value of (willingness to pay for) an additional year of life. It is also consistent with estimates from clinical trials.

scholarly journals Modeling the Conditional Dependence between Discrete and Continuous Random Variables with Applications in Insurance

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 45
Author(s):  
Emilio Gómez-Déniz ◽  
Enrique Calderín-Ojeda
Keyword(s):  
Structural Model ◽  
Medical Expenditure Panel Survey ◽  
Health Care Use ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Conditional Distributions ◽  
Conditional Dependence ◽  
Outpatient Visits ◽  
Conditional Expectations ◽  
The U.S

We jointly model amount of expenditure for outpatient visits and number of outpatient visits by considering both dependence and simultaneity by proposing a bivariate structural model that describes both variables, specified in terms of their conditional distributions. For that reason, we assume that the conditional expectation of expenditure for outpatient visits with respect to the number of outpatient visits and also, the number of outpatient visits expectation with respect to the expenditure for outpatient visits is related by taking a linear relationship for these conditional expectations. Furthermore, one of the conditional distributions obtained in our study is used to derive Bayesian premiums which take into account both the number of claims and the size of the correspondent claims. Our proposal is illustrated with a numerical example based on data of health care use taken from Medical Expenditure Panel Survey (MEPS), conducted by the U.S. Agency of Health Research and Quality.

scholarly journals Are There Racial Disparities in Psychotropic Drug Use and Expenditures in a Nationally Representative Sample of Men in the United States? Evidence From the Medical Expenditure Panel Survey

2013 ◽  
Vol 8 (1) ◽  
pp. 82-90 ◽  
Author(s):  
Geraldine Pierre ◽  
Roland J. Thorpe ◽  
Gniesha Y. Dinwiddie ◽  
Darrell J. Gaskin
Keyword(s):  
United States ◽  
Drug Use ◽  
Racial Disparities ◽  
Psychotropic Drug ◽  
Medical Expenditure Panel Survey ◽  
The United States ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Psychotropic Drug Use ◽  
Nationally Representative

This article sought to determine whether racial disparities exist in psychotropic drug use and expenditures in a nationally representative sample of men in the United States. Data were extracted from the 2000-2009 Medical Expenditure Panel Survey, a longitudinal survey that covers the U.S. civilian noninstitutionalized population. Full-Year Consolidated, Medical Conditions, and Prescribed Medicines data files were merged across 10 years of data. The sample of interest was limited to adult males aged 18 to 64 years, who reported their race as White, Black, Hispanic, or Asian. This study employed a pooled cross-sectional design and a two-part probit generalized linear model for analyses. Minority men reported a lower probability of psychotropic drug use (Black = −4.3%, 95% confidence interval [CI] = [−5.5, −3.0]; Hispanic = −3.8%, 95% CI = [−5.1, −2.6]; Asian = −4.5%, 95% CI = [−6.2, −2.7]) compared with White men. After controlling for demographic, socioeconomic, and health status variables, there were no statistically significant race differences in drug expenditures. Consistent with previous literature, racial and ethnic disparities in the use of psychotropic drugs present problems of access to mental health care and services.

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