By the wide range of researches on Wireless Sensor Networks (WSNs), various routing schemes with diverse criterion have been introduced. However, techniques that consider the characteristics of the sensed data as definitive parameters in determining the behavior of WSNs are extremely rare. In most monitoring applications, sampled data are not equal in their importance. Unexpected data is more likely to be important. That is, data collected during abrupt changes in the environment are more critical than the others. In this paper, we propose Priority-Based Hybrid Routing (PHR) that provides functions ranging from data priority verification to differentiated services according to different priorities. Data priorities, or importance, are determined by their distinctiveness in relation to past data. Dixon's Test, a hypothesis testing method, is adopted for the process. To provide more reliable routing method for high priority data, PHR offers them a novel, diffusion-based forwarding scheme, referred to as Geographic Diffusion. On the other hand, low priority data are delivered by a famous single path routing algorithm, Ad hoc On-demand Distance Vector (AODV). Furthermore, AODV is revised to compensate with the increased traffic caused by Geographic Diffusion. The performance of PHR is evaluated through various simulations.