Soonim Huh1, Thomas Rice, Susan L Ettner. 1. Korea Institute for Health and Social Affairs, San 42-14, Bulgwang-dong, Eunpyeong-gu, Seoul 122-705 Korea.
Abstract
OBJECTIVE: To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account. DATA SOURCES/STUDY SETTING: The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations. PRINCIPAL FINDINGS: Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs. CONCLUSIONS: Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.
OBJECTIVE: To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account. DATA SOURCES/STUDY SETTING: The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations. PRINCIPAL FINDINGS: Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs. CONCLUSIONS: Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.
Authors: R Tamblyn; R Laprise; J A Hanley; M Abrahamowicz; S Scott; N Mayo; J Hurley; R Grad; E Latimer; R Perreault; P McLeod; A Huang; P Larochelle; L Mallet Journal: JAMA Date: 2001 Jan 24-31 Impact factor: 56.272