Patient Treatment Pathways Clustering

Clustering electronic medical records allows discovery of information on health care practises. Entries in such medical records are usually made of a succession of diagnostics or therapeutic steps. The corresponding processes are complex and heterogeneous since they depend on medical knowledge integrating clinical guidelines, physicians individual experience, and patient data and conditions. To analyze such data, we are first proposing to cluster medical visits, consultations, and hospital stays into homogeneous groups, and then to construct higher-level patient trajectories over these different groups. These patient trajectories are then also clustered to distill typical pathways, enabling interpretation of clusters by experts. This approach is evaluated on a real-world administrative database of elderly people in Québec suffering from health failures. Our project stems from three main observations. First, medical treatment processes consist in suc-cessions of diagnostics or therapeutic steps linked to a patient. Being able to analyze and to assess these processes have its importance in the healthcare domain. Second, administrative healthcar