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A Development of Automatic Audit System for Written Informed Consent using Machine Learning
Hitomi Yamada, Tadamasa Takemura, Takahiro Asai, Kazuya Okamoto, Tomohiro Kuroda, Shigeki Kuwata
926
10.3233/978-1-61499-564-7-926
Studies in Health Technology and Informatics
Volume 216: MEDINFO 2015: eHealth-enabled Health
Abstract

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.

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