Mining time dependency patterns in clinical pathways

Clinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and to reduce the length of hospital stay of each patient. The development of clinical pathways is a lengthy process, and may require the collaboration among physicians, nurses and other staff in a hospital. However, individual differences cause great variance in the execution of clinical pathways. This calls for a more dynamic and adaptive process to improve the performance of clinical pathways. This paper proposes a data mining technique to discover the time-dependency patterns of clinical pathways for curing brain strokes. The purpose of mining time-dependency patterns is to discover patterns of process execution sequences and to identify the dependent relations between activities in a majority of cases. By obtaining the time-dependency patterns, we can predict the paths for new patients when they are admitted to a hospital, and, in turn, the health care procedure will then be more effective and efficient.