A Development of Automatic Audit System for Written Informed Consent using Machine Learning.
In Japan, most of all the university and advanced hospitals have implemented both electronic order entry systems and electronic charting. In addition, all medical records are subjected to inspector audit for quality assurance. The record of informed consent (IC) is very important as this provides evidence of consent from the patient or patient's family and health care provider. Therefore, we developed an automatic audit system for a hospital information system (HIS) that is able to evaluate IC automatically using machine learning.
National Cerebral and Cardiovascular Center, Suita, Japan.
Hitomi
H
Yamada
Graduate School of Applied Informatics, University of Hyogo, Kobe, Japan.
Tadamasa
T
Takemura
Graduate School of Applied Informatics, University of Hyogo, Kobe, Japan.
Takahiro
T
Asai
Division of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.
Kazuya
K
Okamoto
Division of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.
Tomohiro
T
Kuroda
National Cerebral and Cardiovascular Center, Suita, Japan.
Shigeki
S
Kuwata
D057286:Electronic Health Records; D006801:Humans; D007258:Informed Consent; D000069550:Machine Learning; D008485:Medical Audit / Q000379:methods*; D016347:Medical Records Systems, Computerized