We consider the problem of efficient information retrieval in asymmetric communication environments where multiple clients with limited resources retrieve information from a powerful server who periodically broadcasts its information repository over a communication medium. The cost of a retrieving client consists of two components: (a) access time, defined as the total amount of time spent by a client in retrieving the information of interest, and (b) tuning time, defined as the time spent by the client in actively listening to the communication medium, measuring a certain efficiency in resource usage. A probability distribution is associated with the data items in the broadcast, representing the likelihood of a data item's being requested at any point of time. The problem of indexed data broadcast is to schedule the data items interleaved with certain indexing information in the broadcast so as to minimize simultaneously the mean access time and the mean tuning time. Prior work on this problem thus far has focused only on some special cases. In this paper we study the indexed data broadcast problem in its full generality and design a broadcast scheme that achieves a mean access time of at most (1.5+=) times the optimal and a mean tuning time bounded by O(log n).