2008 年 29 巻 Special_Issue_2 号 p. S155-S176
Hosptial information system (HIS) collects all the data from all the branches of departments in a hospital, including laboratory tests, physiological tests, electronic patient records. Thus, HIS can be viewed as a large heterogenous database, which stores chronological changes in patients' status. This paper overviews three applications of data mining and statistical methods to HIS. First, clustering of temporal sequences based on multiscale matching was applied for grouping chronic hepatitis. Second, decision tree method was used for detection of risk factors, which was successfully used to prevent nursing medication errors. Finally, several linear models were applied for hospital management data. These results show that data mining methods, including decision tree mining, temporal data mining, are useful for detection of risk factors from large distributed data such as HIS, whose process can be called risk mining.