Lee, V.; Appiah-Kubi, L.; Vogrin, S.; Zanker, J.; Mitropoulos, J. Current Cut Points of Three Falls Risk Assessment Tools Are Inferior to Calculated Cut Points in Geriatric Evaluation and Management Units. Muscles2023, 2, 250-270.
Lee, V.; Appiah-Kubi, L.; Vogrin, S.; Zanker, J.; Mitropoulos, J. Current Cut Points of Three Falls Risk Assessment Tools Are Inferior to Calculated Cut Points in Geriatric Evaluation and Management Units. Muscles 2023, 2, 250-270.
Lee, V.; Appiah-Kubi, L.; Vogrin, S.; Zanker, J.; Mitropoulos, J. Current Cut Points of Three Falls Risk Assessment Tools Are Inferior to Calculated Cut Points in Geriatric Evaluation and Management Units. Muscles2023, 2, 250-270.
Lee, V.; Appiah-Kubi, L.; Vogrin, S.; Zanker, J.; Mitropoulos, J. Current Cut Points of Three Falls Risk Assessment Tools Are Inferior to Calculated Cut Points in Geriatric Evaluation and Management Units. Muscles 2023, 2, 250-270.
Abstract
Background: Falls risk assessment tools are used in hospital inpatient settings to identify pa-tients at increased risk of falls (which may be related to muscle loss/sarcopenia) to guide and target interventions for falls prevention. In 2022, Western Health, Melbourne, Australia, intro-duced a new falls risk assessment tool, the Western Health St. Thomas’ Risk Assessment Tool (WH-STRATIFY), a modified version of The Northern Hospital’s risk tool (TNH-STRATIFY), which replaced the Peninsula Health Risk Screening Tool (PH-FRAT).
Aims: To determine the predictive accuracy of three falls risk assessment tools (PH-FRAT, TNH-STRATIFY and WH-STRATIFY) on admission to Geriatric Evaluation Management (GEM) units.
Method: A retrospective observational study was conducted on four GEM units. Data was col-lected on 54 consecutive patients who fell during admission and 62 randomly sampled patients who did not fall between December 2020 and June 2021. Participants were scored against three falls risk assessment tools. The event rate Youden (Youden IndexER) indices were calculated and compared using default and optimal cut points to determine which tool was most accurate for predicting falls.
Results: Using default cut points to compare falls assessment tools, TNH-STRATIFY had the highest predictive accuracy (Youden IndexER = 0.20, 95% confidence interval CI = 0.07, 0.34). The PH-FRAT (Youden IndexER = 0.01 and 95% CI = -0.04, 0.05) and WH-STRATIFY (Youden IndexER = 0.00 and 95% CI = -0.04, 0.03) were statistically equivalent and not predictive of falls compared to TNH-STRATIFY. When calculated optimal cut points were applied, predictive accuracy im-proved for PH-FRAT (Cut point 17, Youden IndexER = 0.14 and 95% CI = 0.01, 0.29) and WH-STRATIFY (Cut point 7, Youden IndexER = 0.18 and 95% CI = 0.00, 0.35). Overall, all tools had low predictive accuracy for falls.
Conclusion: TNH-STRATIFY had the highest predictive accuracy for falls. The predictive accu-racy of WH-STRATIFY improved and was significant when the calculated optimal cut point was applied. The optimal cut points of falls risk assessment tools should be determined and validated in different clinical settings to optimise local predictive accuracy, enabling targeted falls risk mitigation strategies and resource allocation.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
