Ontology highlight
ABSTRACT:
SUBMITTER: Kim HJ
PROVIDER: S-EPMC6855430 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Kim Hyung-Jun HJ Min Hyun-Ju HJ Lee Dong-Seon DS Choi Yun-Young YY Yoon Miae M Lee Da-Yun DY Song In-Ae IA Cho Jun Yeun JY Park Jong Sun JS Cho Young-Jae YJ Jo You-Hwan YH Yoon Ho Il HI Lee Jae Ho JH Lee Choon-Taek CT Lee Yeon Joo YJ
PloS one 20191114 11
<h4>Background</h4>Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration.<h4>Methods</h4>Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone betw ...[more]