Utilisation of a suite of screening tools to determine adverse healthcare outcomes in an older frail population admitted to a community virtual ward
AffiliationRónán O'Caoimh, Department of Geriatric Medicine, Mercy University Hospital, Grenville Place, Cork, T12 WE28, Ireland.
Keywordsclinical health states
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CitationLewis, C.; O’Caoimh, R.; Patton, D.; O’Connor, T.; Moore, Z.; Nugent, L.E. Utilisation of a Suite of Screening Tools to Determine Adverse Healthcare Outcomes in an Older Frail Population Admitted to a Community Virtual Ward. Int. J. Environ. Res. Public Health 2021, 18, 5601. https://doi.org/10.3390/ijerph18115601
JournalInternational journal of environmental research and public health
AbstractRisk stratification to assess healthcare outcomes among older people is challenging due to the interplay of multiple syndromes and conditions. Different short risk-screening tools can assist but the most useful instruments to predict responses and outcomes following interventions are unknown. We examined the relationship between a suite of screening tools and risk of adverse outcomes (pre-determined clinical 'decline' i.e., becoming 'unstable' or 'deteriorating' at 60-90 days, and institutionalisation, hospitalisation and death at 120 days), among community dwellers (n = 88) after admission to a single-centre, Irish, Community Virtual Ward (CVW). The mean age of patients was 82.8 (±6.4) years. Most were severely frail, with mean Clinical Frailty Scale (CFS) scores of 6.8 ± 1.33. Several instruments were useful in predicting 'decline' and other healthcare outcomes. After adjustment for age and gender, higher frailty levels, odds ratio (OR) 3.29, (p = 0.002), impaired cognition (Mini Mental State Examination; OR 4.23, p < 0.001), lower mobility (modified FIM) (OR 3.08, p < 0.001) and reduced functional level (Barthel Index; OR 6.39, p < 0.001) were significantly associated with clinical 'decline' at 90 days. Prolonged (>30 s) TUG times (OR 1.27, p = 0.023) and higher CFS scores (OR 2.29, p = 0.045) were associated with institutionalisation. Only TUG scores were associated with hospitalisation and only CFS, MMSE and Barthel scores at baseline were associated with mortality. Utilisation of a multidimensional suite of risk-screening tools across a range of domains measuring frailty, mobility and cognition can help predict clinical 'decline' for an already frail older population. Their association with other outcomes was less useful. A better understanding of the utility of these instruments in vulnerable populations will provide a framework to inform the impact of interventions and assist in decision-making and anticipatory care planning for older patients in CVW models.
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- Issue date: 2020
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- Issue date: 2014 Sep 19
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- Authors: Chong E, Ho E, Baldevarona-Llego J, Chan M, Wu L, Tay L
- Issue date: 2017 Jul 1
- FRAILTOOLS study protocol: a comprehensive validation of frailty assessment tools to screen and diagnose frailty in different clinical and social settings and to provide instruments for integrated care in older adults.
- Authors: Checa-López M, Oviedo-Briones M, Pardo-Gómez A, Gonzales-Turín J, Guevara-Guevara T, Carnicero JA, Alamo-Ascencio S, Landi F, Cesari M, Grodzicki T, Rodriguez-Mañas L, FRAILTOOLS consortium.
- Issue date: 2019 Mar 18
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- Authors: Chong E, Ho E, Baldevarona-Llego J, Chan M, Wu L, Tay L, Ding YY, Lim WS
- Issue date: 2018 May