Auto-Selection of DPC Codes from Discharge Summaries by Text Mining in Several Hospitals and Analysis of Differences in Discharge Summaries-Reference-Cited by-同舟云学术

Auto-Selection of DPC Codes from Discharge Summaries by Text Mining in Several Hospitals and Analysis of Differences in Discharge Summaries

Published:2012-01-20 Issue:1 Volume:16 Page:48-54
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Doi Shunsuke, ,Suzuki Takahiro,Shimada Gen,Takasaki Mitsuhiro,Fujita Shinsuke,Tamura Toshiyo,Takabayashi Katsuhiko, , , ,

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.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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