Falls in the elderly were predicted opportunistically using a decision tree and systematically using a database-driven screening tool

• Published in: Journal of clinical epidemiology Vol. 67; no. 8; pp. 877 - 886
• Main Authors: Rafiq, Meena, McGovern, Andrew, Jones, Simon, Harris, Kevin, Tomson, Charles, Gallagher, Hugh, de Lusignan, Simon
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 01.08.2014; Elsevier; Elsevier Limited
• Subjects: Accidental Falls - statistics & numerical data; Age Factors; Aged; Aged, 80 and over; Analysis. Health state; Antidepressive Agents - administration & dosage; Antidepressive Agents - adverse effects; Biological and medical sciences; Cohort Studies; Computerised; Confidence intervals; Databases, Factual; Decision Trees; Disease prevention; Elderly; Epidemiology; Falls; Falls risk; Female; Fractures; Fractures, Bone - epidemiology; Fractures, Bone - etiology; General aspects; General practice; Heart attacks; Humans; Hypertension; Internal Medicine; Kidney diseases; Male; Medical records systems; Medical sciences; Older people; Population; Public health. Hygiene; Public health. Hygiene-occupational medicine; Risk assessment; Risk Factors; ROC Curve; Screening tool; Sex Factors; United Kingdom - epidemiology; Urinary Incontinence - epidemiology; Urinary Incontinence - physiopathology; Visual aids; British Isles; Screening tool; Fractures; Medical records systems; General practice; Elderly; Falls risk; Computerised; Diseases of the osteoarticular system; Risk; Fracture; Decision tree; Epidemiology; Database; Medical record; Computer aid; Public health; Computerization; Tool; Human; Prediction; Medical screening; Trauma; Risk factor; Fall; Predictive factor
• ISSN: 0895-4356; 1878-5921; 1878-5921
• DOI: 10.1016/j.jclinepi.2014.03.008

To identify risk factors for falls and generate two screening tools: an opportunistic tool for use in consultation to flag at risk patients and a systematic database screening tool for comprehensive falls assessment of the practice population. This multicenter cohort study was part of the quality improvement in chronic kidney disease trial. Routine data for participants aged 65 years and above were collected from 127 general practice (GP) databases across the UK, including sociodemographic, physical, diagnostic, pharmaceutical, lifestyle factors, and records of falls or fractures over 5 years. Multilevel logistic regression analyses were performed to identify predictors. The strongest predictors were used to generate a decision tree and risk score. Of the 135,433 individuals included, 10,766 (8%) experienced a fall or fracture during follow-up. Age, female sex, previous fall, nocturia, anti-depressant use, and urinary incontinence were the strongest predictors from our risk profile (area under the receiver operating characteristics curve = 0.72). Medication for hypertension did not increase the falls risk. Females aged over 75 years and subjects with a previous fall were the highest risk groups from the decision tree. The risk profile was converted into a risk score (range −7 to 56). Using a cut-off of ≥9, sensitivity was 68%, and specificity was 60%. Our study developed opportunistic and systematic tools to predict falls without additional mobility assessments.