Introduction to the Use of MEPS (Medical Expenditure Panel Survey)

2010 ◽  
pp. 19-56
Author(s):  
Patricia Cerrito ◽  
John Cerrito
Keyword(s):  
Medical Expenditure Panel Survey ◽  
Complete Information ◽  
Medical Expenditure ◽  
Patient Treatment ◽  
Panel Survey ◽  
Patient Privacy ◽  
Part D ◽  
Physician Visits ◽  
Medication Information ◽  
Healthcare Profession

We will begin with data from the Medical Expenditure Panel Survey and use it throughout the text. This dataset has been provided since 1996 and contains yearly information concerning every interaction with the healthcare profession for a cohort of approximately 30,000 patients and 11,000 households. Each household is included in the survey for a two-year period. It contains every inpatient and outpatient event, all physician visits, medications, and lab orders for every member of this cohort. It is usually two years behind, so that in 2008, medication information concerning Medicare, Part D from 2006 first became available for analysis. Because of patient privacy, patient treatment and diagnosis information is incomplete. However, this database contains very complete information about reimbursements from private insurers, government agencies, and individual patients. Therefore, it can be used to determine healthcare expenditures by individuals and households.

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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