Catherine Sherrington, Stephen R. Lord, Jacqueline CT Close, Elizabeth Barraclough, Morag Taylor , Sandra O’Rourke , Susan Kurrle, Anne Tiedemann , Robert G Cumming, Robert D. Herbert
DOI: 10.2340/16501977-0550

Objective: To develop and internally validate a simple falls prediction tool for rehabilitation settings.
Design: Prospective cohort study.
Participants: A total of 533 inpatients.
Methods: Possible predictors of falls were collected from medical records, interview and physical assessment. Falls during inpatient stays were monitored.
Results: Fourteen percent of participants fell. A multivariate model to predict falls included: male gender (odds ratio (OR) 2. 70, 95% confidence interval (CI) 1. 57–4. 64), central nervous system medications (OR 2. 50, 95% CI 1. 47–4. 25), a fall in the previous 12 months (OR 2. 21, 95% CI 1. 07–4. 56), frequent toileting (OR 2. 14, 95% CI 1. 27–3. 62) and tandem stance inability (OR 2. 00, 95% CI 1. 11–3. 59). The area under the curve for this model was 0. 74 (95% CI 0. 68–0. 80). The Predict_FIRST tool is a unit weighted adaptation of this model (i. e. 1 point allocated for each predictor) and its area under the curve was 0. 73 (95% CI 0. 68–0. 79). Predicted and actual falls risks corresponded closely.
Conclusion: This tool provides a simple way to quantify the probability with which an individual patient will fall during a rehabilitation stay.