Abstract
Recently, Electronic Medical Record (EMR) systems have become popular in Japan, and numerous discharge summaries are being stored electronically, although they have not yet been reutilized. We performed text mining by using the term frequencyinverse document frequency method along with a morphological analysis of the discharge summaries from 3 hospitals (the Chiba University Hospital, St. Luke’s International Hospital, and the Saga University Hospital). We found differences in the styles of the summaries between hospitals, while the rates of properly classified Diagnosis Procedure Combination (DPC) codes were almost the same. Beyond the different styles for the discharge summaries, the text mining method was able to obtain appropriate extracts of the proper DPC codes. An improvement was observed by using the integrated model data between the hospitals. It appeared that a large database containing data from many hospitals could improve the precision of text mining.
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