Heterogeneity between studies indicates that the Morse Falls Scale and STRATIFY may still be useful in particular setting s , but that widespread adoption of either is unlikely to generate benefits significantly greater than that of nursing staff clinical judgment
INTRODUCTION Fall risk screening tools are frequently used as a part of falls prevention programs in hospitals .
Design -related bias in evaluations of tool predictive accuracy could lead to overoptimistic results , which would then contribute to program failure in practice .
Prediction of falls using a risk assessment tool in the acute care setting
Background The British STRATIFY tool was previously developed to predict falls in hospital . Although the tool has several strengths , certain limitations exist which may not allow generalizability to a Canadian setting . Thus , we tested the STRATIFY tool with some modification and re-weighting of items in Canadian hospitals . Methods This was a prospect i ve validation cohort study in four acute care medical units of two teaching hospitals in Hamilton , Ontario . In total , 620 patients over the age of 65 years admitted during a 6-month period . Five patient characteristics found to be risk factors for falls in the British STRATIFY study were tested for predictive validity . The characteristics included history of falls , mental impairment , visual impairment , toileting , and dependency in transfers and mobility . Multivariate logistic regression was used to obtain optimal weights for the construction of a risk score . A receiver-operating characteristic curve was generated to show sensitivities and specificities for predicting falls based on different threshold scores for considering patients at high risk . Results Inter-rater reliability for the weighted risk score indicated very good agreement ( inter-class correlation coefficient = 0.78 ) . History of falls , mental impairment , toileting difficulties , and dependency in transfer / mobility significantly predicted fallers . In the multivariate model , mental status was a significant predictor ( P < 0.001 ) while history of falls and transfer / mobility difficulties approached significance ( P = 0.089 and P = 0.077 respectively ) . The logistic regression model led to weights for a risk score on a 30-point scale . A risk score of 9 or more gave a sensitivity of 91 % and specificity of 60 % for predicting who would fall . Conclusion Good predictive validity for identifying fallers was achieved in a Canadian setting using a simple-to-obtain risk score that can easily be incorporated into practice
Heterogeneity between studies indicates that the Morse Falls Scale and STRATIFY may still be useful in particular setting s , but that widespread adoption of either is unlikely to generate benefits significantly greater than that of nursing staff clinical judgment
INTRODUCTION Fall risk screening tools are frequently used as a part of falls prevention programs in hospitals .
Design -related bias in evaluations of tool predictive accuracy could lead to overoptimistic results , which would then contribute to program failure in practice .