LAUSR

AIMS This study was to assess the predictive ability of the Johns Hopkins Fall Risk Assessment Tool (Chinese Version) in inpatient settings. DESIGN A case-control study. METHODS This study was conducted in a tertiary hospital based on 2019 data. With a case-control design in a 1:2 ratio, the predictive ability of the Johns Hopkins Fall Risk Assessment Tool (Chinese Version) was determined by ROC curve. The best cut point was identified based on sensitivity, specificity, positive predict value and negative predict value. Conditional logistical regression analysis was conducted to test the predictive ability of each indicator. RESULTS The study included 309 patients, with 103 in the case group and 206 in the control groups. Generally, the predictive ability was acceptable with the area under ROC curve value at 0.73 (95% CI: 0.67-0.79). Positive predict value and negative predict value performed best at the cut point of 13. Sensitivity at cut point 6 was much higher than that at cut point 13, though specificity was lower. Except for age, all indicators in the Johns Hopkins Fall Risk Assessment Tool (Chinese Version) demonstrated significant predictive ability as to occurrence of fall. CONCLUSION The Johns Hopkins Fall Risk Assessment Tool (Chinese Version) is a reliable assessment instrument in the inpatient settings. IMPACT This is the first study that evaluated the predictive ability of the Johns Hopkins Fall Risk Assessment Tool (Chinese version) in the inpatient settings, and proved that the instrument is reliable for assessing inpatient fall risks. Further studies could be carried out to assess the predict ability of Johns Hopkins Fall Risk Assessment Tool (Chinese version) among specific populations.