Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER)

• Main Authors: Bjorn Winkens, Hugo M van der Kuy, Dennis Wong, Brigit P C van Oijen, Kim P G M Hurkens, Vanja Milosevic, Aimee Linkens, Carlota Mestres-Gonzalvo
• Format: Article
• Language: English
• Published: BMJ Publishing Group 2021-06-01
• Series: BMJ Open
• Online Access: https://bmjopen.bmj.com/content/11/5/e042941.full

Objectives To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident.Design Observational, retrospective case–control study.Setting Nursing homes.Participants A total of 1668 (824 in part I, 844 in part II) NH-residents from the Netherlands were included. Data of participants from part I were excluded in part II.Primary and secondary outcome measures Development and validation of a fall risk CR in NH-residents. Logistic regression analysis was conducted to identify the fall risk-variables in part I. With these, three CRs were developed (ie, at the day of the fall incident and 3 days and 5 days prior to the fall incident). The overall prediction quality of the CRs were assessed using the area under the receiver operating characteristics (AUROC), and a cut-off value was determined for the predicted risk ensuring a sensitivity ≥0.85. Finally, one CR was chosen and validated in part II using a new retrospective data set.Results Eleven fall risk-variables were identified in part I. The AUROCs of the three CRs form part I were similar: the AUROC for models I, II and III were 0.714 (95% CI: 0.679 to 0.748), 0.715 (95% CI: 0.680 to 0.750) and 0.709 (95% CI: 0.674 to 0.744), respectively. Model III (ie, 5 days prior to the fall incident) was chosen for validation in part II. The validated AUROC of the CR, obtained in part II, was 0.603 (95% CI: 0.565 to 0.641) with a sensitivity of 83.41% (95% CI: 79.44% to 86.76%) and a specificity of 27.25% (95% CI 23.11% to 31.81%).Conclusion Medication data and resident characteristics alone are not sufficient enough to develop a successful CR with a high sensitivity and specificity to predict fall risk in NH-residents.Trial registration number Not available.