Construction of the integrated multicentre discharge summary database.
We started a multi-year project to collect discharge summaries from multiple hospitals and create a big text database to build a common document vector space, and develop various applications such as the autoselection of the disease. As the first step, we extracted discharge summary from two hospitals. Using a text mining method, we carried out a DPC selection. There was a difference in term structure and number of terms between the discharge summaries from both hospitals. Nevertheless, the selection rate of the disease is resembled closely.
Department of Medical Informatics and Management, Chiba University Hospital.
Suzuki
S
Takahiro
Doi
D
Shunsuke
Fujita
F
Shinsuke
Hatakeyama
H
Yutaka
Honda
H
Masayuki
Matsumura
M
Yasushi
Shimada
S
Gen
Takasaki
T
Mitsuhiro
Tsumoto
T
Shusaku
Yokoi
Y
Hideto
Takabayashi
T
Katsuhiko
D059019:Clinical Coding / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D057286:Electronic Health Records / Q000458:organization & administration*; D033181:Information Dissemination / Q000379:methods; D007564:Japan; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D063886:Patient Discharge Summaries / Q000145:classification*; D018511:Systems Integration; D018875:Vocabulary, Controlled