Citation

Cho I, Jin I. Stud. Health Technol. Inform. 2019; 264: 1650-1651.

Affiliation

Department of Nursing, National Health Insurance Service Islam Hospital, Gyeonggi-do, Republic of Korea.

Copyright

(Copyright © 2019, IOS Press)

DOI

10.3233/SHTI190579

PMID

31438275

Abstract

Wide spread of electronic medical records provide an opportunity to use time-variant longuitudinal data near real time. Hospital nurses would benefit greatly from the ability to use such data to predict adverse event risks of individual patient. We have developed an clinical decision support service to predict inpatient falling using machine learning and clinical big data approach. This study reports the initial responses of nurses to the service in an acute care setting.

Language: en

Keywords

Accidental Falls; Clinical Decision Support Systems; User–Computer Interface