@article{ref1,
title="Evaluation of a fall risk prediction tool using large-scale data",
journal="Studies in health technology and informatics",
year="2016",
author="Yokota, Shinichiroh and Tomotaki, Ai and Mohri, Ohmi and Endo, Miyoko and Ohe, Kazuhiko",
volume="225",
number="",
pages="800-801",
abstract="To support nursing care for the prevention of falls among inpatients at our institution, we developed and implemented a fall risk prediction tool. To evaluate its effectiveness, we compared the number of falls among inpatients before and after its implementation. The odds ratio for the probability of falling was 0.79 (95% confidence interval: 0.69-0.91) (p < 0.001), which was adjusted based on institutional data comprising 573,216 records from 25,039 patients in 24 general wards. Although whether nurses used the tool completely or whether the dissemination of fall prevention measures led to behavioral changes among the nurses in relation to their care remained unclear, the fall risk of inpatients appeared to be reduced after implementation of the prediction tool.<p /> <p>Language: en</p>",
language="en",
issn="0926-9630",
doi="",
url="http://dx.doi.org/"
}