Ellen Vlaeyen1, Joris Poels2, Uschi Colemonts3, Lien Peeters4, Greet Leysens5, Kim Delbaere6, Eddy Dejaeger7, Fabienne Dobbels8, Koen Milisen9. 1. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Centre of Expertise for Fall and Fracture Prevention Flanders, Leuven, Belgium. Electronic address: ellen.vlaeyen@kuleuven.be. 2. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Centre of Expertise for Fall and Fracture Prevention Flanders, Leuven, Belgium. 3. Hospital Oost-Limburg, Genk, Belgium. 4. Division of Geriatric Medicine, University Hospitals, Leuven, Belgium. 5. Department of Nursing and Midwifery, Thomas More University, College, Lier, Belgium. 6. Neuroscience Research Australia, University of New South Wales, Sydney, Australia. 7. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Centre of Expertise for Fall and Fracture Prevention Flanders, Leuven, Belgium; Division of Geriatric Medicine, University Hospitals, Leuven, Belgium. 8. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium. 9. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Centre of Expertise for Fall and Fracture Prevention Flanders, Leuven, Belgium; Division of Geriatric Medicine, University Hospitals, Leuven, Belgium. Electronic address: koen.milisen@kuleuven.be.
Abstract
OBJECTIVES: To evaluate and compare the predictive accuracy of fall history, staff clinical judgment, the Care Home Falls Screen (CaHFRiS), and the Fall Risk Classification Algorithm (FRiCA). DESIGN: Prospective multicenter cohort study with 6 months' follow-up. SETTING AND PARTICIPANTS: A total of 420 residents from 15 nursing homes participated. METHODS: Fall history, clinical judgment of staff (ie, physiotherapists, nurses and nurses' aides), and the CaHFRiS and FRiCA were assessed at baseline, and falls were documented in the follow-up period. Predictive accuracy was calculated at 1, 3, and 6 months by means of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, Youden Index, and overall accuracy. RESULTS: In total, 658 falls occurred and 50.2% of the residents had at least 1 fall with an average fall rate of 1.57 (SD 2.78, range 0-20) per resident. The overall accuracy for all screening methods at all measuring points ranged from 54.8% to 66.5%. Fall history, FRiCA, and a CaHFRiS score of ≥4 had better sensitivity, ranging from 64.4% to 80.8%, compared with the clinical judgment of all disciplines (sensitivity ranging from 47.4% to 71.2%). The negative predictive value (ranging from 92.9% at 1 month to 59.6% at 6 months) had higher scores for fall history, FRiCA, and a CaHFRiS score of ≥4. Specificity ranged from 50.3% at 1 month to 77.5% at 6 months, with better specificity for clinical judgment of physiotherapists and worse specificity for FRiCA. Positive predictive value ranged from 22.2% (clinical judgment of nurses' aides) at 1 month to 67.8% at 6 months (clinical judgment of physiotherapists). CONCLUSIONS AND IMPLICATIONS: No strong recommendations can be made for the use of any screening method. More research on identifying residents with the highest fall risk is crucial, as these residents benefit the most from multifactorial assessments and subsequent tailored interventions.
OBJECTIVES: To evaluate and compare the predictive accuracy of fall history, staff clinical judgment, the Care Home Falls Screen (CaHFRiS), and the Fall Risk Classification Algorithm (FRiCA). DESIGN: Prospective multicenter cohort study with 6 months' follow-up. SETTING AND PARTICIPANTS: A total of 420 residents from 15 nursing homes participated. METHODS: Fall history, clinical judgment of staff (ie, physiotherapists, nurses and nurses' aides), and the CaHFRiS and FRiCA were assessed at baseline, and falls were documented in the follow-up period. Predictive accuracy was calculated at 1, 3, and 6 months by means of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, Youden Index, and overall accuracy. RESULTS: In total, 658 falls occurred and 50.2% of the residents had at least 1 fall with an average fall rate of 1.57 (SD 2.78, range 0-20) per resident. The overall accuracy for all screening methods at all measuring points ranged from 54.8% to 66.5%. Fall history, FRiCA, and a CaHFRiS score of ≥4 had better sensitivity, ranging from 64.4% to 80.8%, compared with the clinical judgment of all disciplines (sensitivity ranging from 47.4% to 71.2%). The negative predictive value (ranging from 92.9% at 1 month to 59.6% at 6 months) had higher scores for fall history, FRiCA, and a CaHFRiS score of ≥4. Specificity ranged from 50.3% at 1 month to 77.5% at 6 months, with better specificity for clinical judgment of physiotherapists and worse specificity for FRiCA. Positive predictive value ranged from 22.2% (clinical judgment of nurses' aides) at 1 month to 67.8% at 6 months (clinical judgment of physiotherapists). CONCLUSIONS AND IMPLICATIONS: No strong recommendations can be made for the use of any screening method. More research on identifying residents with the highest fall risk is crucial, as these residents benefit the most from multifactorial assessments and subsequent tailored interventions.
Authors: Cristina Lavareda Baixinho; Carla Madeira; Silvia Alves; Maria Adriana Henriques; Maria Dos Anjos Dixe Journal: Int J Environ Res Public Health Date: 2022-06-21 Impact factor: 4.614
Authors: Nasir Wabe; Joyce Siette; Karla L Seaman; Amy D Nguyen; Magdalena Z Raban; Jacqueline C T Close; Stephen R Lord; Johanna I Westbrook Journal: BMC Geriatr Date: 2022-04-01 Impact factor: 3.921