From Hospital Big Data to Clinical Process: A Granular Computing Approach

摘要

This paper proposes construction of clinical process plan from nursing order histories and discharge summaries stored in hospital information system. First, the system extracts subgrouping from clinical cases with the same Diagnostic Procedure Combination code (DPC) by mixture model clustering. Subgroups give different types of diseases with different temporal evolution. Then, classification models of each subgroup are constructed by the analysis of discharge summaries to capture the meaning of each subgroup. Finally, cases are classified by using the classification model and a clinical pathway is generated for each new subgroup. The proposed method was evaluated on the datasets extracted hospital information system, whose results show that plausible clinical pathways were obtained, compared with previously introduced methods.