Analysis of Hospitalizing Behaviors Based on Big Trajectory Data

With the improvement of living standards, people pay more attention to health, which is significant to analyze people's hospitalizing behaviors. The wide use of mobile devices generates a great deal of data, which contains a lot of travel information about residents. Many people would like to see a doctor through calling an online car hailing for its convenience. Thus, based on big trajectory data generated by the online car hailing, the hospitalizing behaviors of residents are analyzed in this paper. The hospitalizing behaviors are analyzed from two aspects. One is performed from the temporal aspect, in which the daily numbers of trips of hospitalizing behaviors under different modes are analyzed. The other one is performed from the spatial aspect, in which the hot hospitals, popularity, and gravity distribution of hospitals are analyzed. Based on the spatial analysis, the network constructed by the hot hospitals is also analyzed. The results show that the hospitalizing behavior analysis can reflect the hospitalizing behaviors in detail, which can make contributions to the decision-making of infrastructure configuration for institutions, such as urban planning departments and hospitals.