Predicting Falls in Nursing Homes: A Prospective Multicenter Cohort Study Comparing Fall History, Staff Clinical Judgment, the Care Home Falls Screen, and the Fall Risk Classification Algorithm.

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). Prospective multicenter cohort study with 6 months' follow-up. A total of 420 residents from 15 nursing homes participat...

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Publicado en:Journal of the American Medical Directors Association Vol. 22; no. 2; pp. 380 - 388
Autores principales: Vlaeyen, Ellen, Poels, Joris, Colemonts, Uschi, Peeters, Lien, Leysens, Greet, Delbaere, Kim, Dejaeger, Eddy, Dobbels, Fabienne, Milisen, Koen
Formato: research tables/charts Journal Article
Publicado: Elsevier B.V. Feb2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2021
      vid: 22
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      pub: Elsevier B.V.
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        10.1016/j.jamda.2020.06.037
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        atl: Predicting Falls in Nursing Homes: A Prospective Multicenter Cohort Study Comparing Fall History, Staff Clinical Judgment, the Care Home Falls Screen, and the Fall Risk Classification Algorithm.
      aug:
        au:
          Vlaeyen, Ellen
          Poels, Joris
          Colemonts, Uschi
          Peeters, Lien
          Leysens, Greet
          Delbaere, Kim
          Dejaeger, Eddy
          Dobbels, Fabienne
          Milisen, Koen
        affil: Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium
      sug:
        subj:
          Accidental Falls Risk Factors
          Nursing Home Residents
          Health Screening
          Judgment
          Accidental Falls Prevention and Control
          Human
          Multicenter Studies
          Prospective Studies
          Algorithms Evaluation
          Sensitivity and Specificity
          Descriptive Statistics
          Physical Therapists
      ab: 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). Prospective multicenter cohort study with 6 months' follow-up. A total of 420 residents from 15 nursing homes participated. 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. 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). 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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