Home FIRsT: interdisciplinary geriatric assessment and disposition outcomes in the Emergency Department.

European journal of internal medicine(2020)

引用 7|浏览12
暂无评分
摘要
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.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要