The Impact of the Medicare Prescription Drug Bill


To fill a gap by quantifying the effects of the policy change on the general health status, life expectancy, and medical care consumption of Medicare beneficiaries.


Medicare, the main health insurer for the elderly, has recently experienced the biggest reform since its inception: the inclusion of prescription drug coverage for its beneficiaries. Most discussion of the Medicare Prescription Drug, Improvement and Modernization Act of 2003 has focused on the cost of implementing this new policy, leaving unexplored the quantification of its benefits. In fact, very little is known about the effect this policy will have on health outcomes, life expectancy and the substitution from more expensive modes of medical care, such as inpatient care. If prescription drugs are a substitute for other forms of medical care, an increase in prescription drug utilization may improve health outcomes and reduce the utilization of inpatient and/or outpatient care; however, it may also increase life expectancy and make the population eligible for Medicare benefits larger in the future, increasing Medicare's expenditure. The previous literature on this policy issue has failed to consider the dynamic effects that increased access to prescription drugs may have on future health and medical care utilization. Moreover, the debate has been mostly based on rough approximations to the actual policy without taking into account its unique actuarial design. This project will analyze the impact of the Medicare prescription drug bill by constructing a dynamic stochastic model that is able to also quantify the long-run effects of the enacted policy.The structural parameters of the model are estimated using longitudinal data from the Medicare Current Beneficiary Survey 1994-1999 carried by the Center for Medicare and Medicaid Services (CMS). Given the fact that the policy has not been implemented yet, and therefore, no post-policy information is available, the structural approach becomes specially appealing for this analysis, because it allows an analysis of the effect of the policy as counterfactual experiments once the behavioral model is estimated.

Funded By: 
Funded By: 
Award Dates: 
July 1, 2005 - June 30, 2006
PARC Grant Year: 
Year 12