The predictive properties of frailty rating scales at the primary-secondary care interface

Wou, Franklin; Conroy, Simon

doi:10.1016/j.eurger.2012.07.104

Cited by 1 publication

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“…More recently, operationalised frailty scores have been used for this purpose. 14,15 These scores often rely on subjective clinician judgement, parameters of physical performance, require specialised research apparatus or large amounts of data, rendering them less suitable and feasible in the secondary care setting (particularly acute care). 16 Furthermore, validation for the scores has often been based on small single centre studies.…”

Section: Discussionmentioning

confidence: 99%

Validating a methodology to measure frailty syndromes at hospital level utilising administrative data

et al. 2020

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Background Identifying older people with clinical frailty, reliably and at scale, is a research priority. We measured frailty in older people using a novel methodology coding frailty syndromes on routinely collected administrative data, developed on a national English secondary care population, and explored its performance of predicting inpatient mortality and long length of stay at a single acute hospital. Methodology We included patient spells from Secondary User Service (SUS) data for those ≥65 years with attendance to the emergency department or admission to West Middlesex University Hospital between 01 July 2016 to 01 July 2017. We created eight groups of frailty syndromes using diagnostic coding groups. We used descriptive statistics and logistic regression to explore performance of diagnostic coding groups for the above outcomes. Results We included 17,199 patient episodes in the analysis. There was at least one frailty syndrome present in 7,004 (40.7%) patient episodes. The resultant model had moderate discrimination for inpatient mortality (area under the receiver operating characteristic curve (AUC) 0.74; 95% confi dence interval (CI) 0.72-0.76) and upper quartile length of stay (AUC 0.731; 95% CI 0.722-0.741). There was good negative predictive value for inpatient mortality (98.1%). Conclusions Coded frailty syndromes signifi cantly predict outcomes. Model diagnostics suggest the model could be used for screening of elderly patients to optimise their care.

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Section: Discussionmentioning

confidence: 99%