As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
The analysis of medical incident reports is indispensable for patient safety. Most incident reports are composed from freely written descriptions, but an analysis of such free descriptions is not sufficient in the medical field. In this study, we aim to conduct new findings using incident information, to clarify improvements that should be made to solve the root cause of an accident, and to ensure safe medical treatment through such improvements.
We employed natural language processing (NLP) and network analysis to identify effective classes of medical incident reports. Network analysis can find various relationships that are not only direct but also indirect. After that, we compared the clustering results between Jichi Medical University and Osaka City University Hospital. By finding the common and different parts in medical incident report' s classes, we could show new perspectives on proposing a common reporting systems in Japan for improving patient safety.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.