There is increasing evidence suggesting that Medicare beneficiaries do not make fully informed decisions when choosing among alternative Medicare health plans. To the extent that deciphering the intricacies of alternative plans consumes time and money, the Medicare health plan market is one in which search costs may play an important role. To account for this, we split beneficiaries into two groups|those who are informed and those who are uninformed. If uninformed, beneficiaries only use a subset of covariates to compute their maximum utilities, and if informed, they use the full set of variables considered. In a Bayesian framework with Markov Chain Monte Carlo (MCMC) methods, we estimate search cost coefficients based on the minimum and maximum statistics of the search cost distribution, incorporating both horizontal differentiation and information heterogeneities across eligibles. Our results suggest that, conditional on being uninformed, older, higher income beneficiaries with lower self-reported health status are more likely to utilize easier access to information.