JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
RESEARCH SUPPORT, U.S. GOV'T, P.H.S.
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The insurance effect on prescription drug expenditures among the elderly: findings from the 1997 Medical Expenditure Panel Survey.

Medical Care 2004 May
BACKGROUND: Despite continuing debate over a prescription drug benefit for the Medicare program, there has been relatively little research estimating the potential cost of providing such a benefit.

OBJECTIVE: The objective of this study was to estimate the effect of prescription drug insurance on outpatient prescription drug expenditures among the elderly.

RESEARCH DESIGN: We studied respondents aged > or =65 years to the 1997 Medical Expenditure Panel Survey, a representative survey of the U.S. noninstitutionalized population. Survey-weighted linear regression models were used to estimate the probability of any expenditures and total expenditures while controlling for sociodemographic characteristics, chronic conditions, and health status.

MEASURES: We used prescription drug insurance status and outpatient prescription drug expenditures.

RESULTS: An estimated 34 million elderly people filled 630 million prescriptions in 1997. Thirty-seven percent did not have prescription drug insurance. Total prescription drug expenditures exceeded $23 billion. Persons without prescription drug insurance spent slightly less than $7 billion; those with insurance spent more than $16 billion. After controlling for health status, comorbidity, and demographic characteristics, prescription drug insurance increased expenditures by $183 per person. The marginal increase in total expenditures of extending the average observed benefit to those currently uninsured is $2.3 billion (95% confidence interval, $1.2-3.5 billion).

CONCLUSIONS: Proposals for a Medicare drug benefit provide high copayments to protect against insurance effects and to address uncertainty in cost estimates of the proposed benefit. By quantifying the insurance effect on expenditures among the elderly, the data reported here could reduce uncertainty in the budget estimation process.

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