Citation

Liu J, Wong ZS, Tsui KL, So HY, Kwok A. Stud. Health Technol. Inform. 2019; 264: 1526-1527.

Affiliation

New Territories East Cluster (NTEC), Quality and Safety Division Prince of Wales Hospital, New Territories, Hong Kong, China.

Copyright

(Copyright © 2019, IOS Press)

DOI

10.3233/SHTI190517

PMID

31438214

Abstract

Retrospective analysing of fall incident reports can uncover hidden information, identify potential risk factors, and improve healthcare quality. This study explores potential fall incident clusters using word embeddings and hierarchical clustering. Fall incident reports from 7 local hospitals in Hong Kong were catalogued into 5 potential clusters with significantly different fall severity, gender, reporting department, and keywords. This study demonstrates the feasibility of using text clustering methods on real-world fall incident reports mining.

Language: en

Keywords

Unsupervised machine learning; natural language processing; patient safety