RESUMEN
We evaluated predictors of the Clinical Frailty Scale (CFS) scored by an interdisciplinary team (Home FIRsT) performing comprehensive geriatric assessment (CGA) in our Emergency Department (ED). This was a retrospective observational study (service evaluation) utilising ED-based CGA data routinely collected by Home FIRsT between January and October 2020. A linear regression model was computed to establish independent predictors of CFS. This was complemented by a classification and regression tree (CRT) to evaluate the main predictors. There were 799 Home FIRsT episodes, of which 740 were unique patients. The CFS was scored on 658 (89%) (median 4, range 1-8; mean age 81 years, 61% women). Independent predictors of higher CFS were older age (p<0.001), history of dementia (p<0.001), mobility (p≤0.007), disability (p<0.001), and higher acuity of illness (p=0.009). Disability and mobility were the main classifiers in the CRT. Results suggest appropriate CFS scoring informed by functional baseline.
RESUMEN
BACKGROUND: Older people in the Emergency Department (ED) are clinically heterogenous and some presentations may be better suited to alternative out-of-hospital pathways. A new interdisciplinary comprehensive geriatric assessment (CGA) team (Home FIRsT) was embedded in our acute hospital's ED in 2017. AIM: To evaluate if routinely collected CGA metrics were associated with ED disposition outcomes. DESIGN: Retrospective observational study. METHODS: We included all first patients seen by Home FIRsT between 7th May and 19th October 2018. Collected measures were sociodemographic, baseline frailty (Clinical Frailty Scale), major diagnostic categories, illness acuity (Manchester Triage Score) and cognitive impairment/delirium (4AT). Multivariate binary logistic regression models were computed to predict ED disposition outcomes: hospital admission; discharge to GP and/or community services; discharge to specialist geriatric outpatients; discharge to the Geriatric Day Hospital. RESULTS: In the study period, there were 1,045 Home FIRsT assessments (mean age 80.1 years). For hospital admission, strong independent predictors were acute illness severity (OR 2.01, 95% CI 1.50-2.70, P<0.001) and 4AT (OR 1.26, 95% CI 1.13 - 1.42, P<0.001). Discharge to specialist outpatients (e.g. falls/bone health) was predicted by musculoskeletal/injuries/trauma presentations (OR 6.45, 95% CI 1.52 - 27.32, P=0.011). Discharge to the Geriatric Day Hospital was only predicted by frailty (OR 1.52, 95% CI 1.17 - 1.97, P=0.002). Age and sex were not predictive in any of the models. CONCLUSIONS: Routinely collected CGA metrics are useful to predict ED disposition. The ability of baseline frailty to predict ED outcomes needs to be considered together with acute illness severity and delirium.