Abstract: How to select a suitable task scheduling strategy to accomplish the task of medical data query in scheduling and allocation inside each hospital is a important problem demanded to be dealt with in medical big data processing. In order to content the optimal medical data corresponding time and optimal cost considered in task scheduling, a improved particle swarm algorithm was proposed. The algorithm constructs the dual fitness function of optimal time and optimal cost to adjusted the inertia weight of the update of particle velocity adaptively, fasten the speed of optimal particle searching, and find out the most reasonable task scheduling scheme of data query, maximize the efficiency of medical data query in medical information sharing platform. Experiment results demonstrate the effectiveness of the proposed algorithm.