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Title: Frailty assessment in acute care
Author: Soong, John
ISNI:       0000 0004 6423 712X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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Introduction For some people, ageing is associated with the experience of increased co-morbidity, functional impairment, poor resilience and heightened vulnerability to external stressors, resulting in reduced lifespan as well as health-span. This frailty phenomenon poses challenges to health care systems in the form of increased patient complexity and resource utilisation. The acute care setting, characterised by time-pressure and high patient turn-over, is under strain and struggles to recognise and subsequently reliably intervene, to prevent, reverse or halt the decline of this vulnerable cohort. Methods This mixed-methods study probes existing evidence and ‘real-world’ processes with a systematic review of frailty assessments developed or validated in the acute care setting and a survey of contemporaneous clinical practice in London Acute Medical Units. Content validation and understanding of contextual factors for ideal frailty assessment in acute care is explored using Delphi consensus and Focus Group methodology respectively. The resultant model is developed on existing retrospective national Hospital Episode Statistics data, and prospectively tested on observational data in a local Acute Medical Unit setting. Results Existing frailty scores are preponderantly biophysical in nature, and have poor predictive power for adverse outcomes in the acute care setting. In clinical practice, single-dimension assessment tools predominate. Frailty syndromes and previous high resource utilisation in the form of a simple, clinically relevant tool useful to the multidisciplinary team gain consensus as optimal assessment for the setting. Retrospective testing of the frailty model displays moderate predictive powers for adverse events (inpatient mortality, emergency readmission and institutionalisation) and prospective testing provides concurrent (Frailty Index, Age, Co-Morbidity) and comparative predictive validity (Frailty Index, Co-Morbidity, admission National Early Warning Score) with existing risk stratification models in this setting. Conclusions A risk prediction model based on frailty syndromes and previous high resource utilisation is a valid, feasible and useful for the acute care setting.
Supervisor: Bell, Derek Sponsor: Royal College of Physicians of London ; Chelsea and Westminster Hospital NHS Foundation Trust
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral