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Being Your Best: An innovative approach to frailty and care transitions

Research priority: Optimising health and wellbeing
Researchers: Judy Lowthian, Amber Mills, Liz Cyarto, Claudia Meyer, Marissa Dickins, Lorenna Thurgood, Fleur O’Keefe, Julie Byles, Alison Hutchinson, Frances Sutherland, Katie Walker, Lee Boyd, Michael Rose, De Villiers Smit, Harvey Newnham, Peta Forder
Research partners: Alfred Health, Cabrini Health, Monash Health, Monash University, Deakin University, University of Newcastle
Study population: At home support clients and community members
Funding support: Monash Partners Academic Health Science Centre Medical Research Future Fund (MRFF) Rapid Applied Research Translation Fund

Frailty refers to an increased vulnerability to stressors, including ill health and increases susceptibility to further decline. Approximately 50 per cent of Australians ≥65 years are frail. Frailty worsens with hospital admission and increases risk of hospitalisation. Furthermore, previous hospitalisation within 12 months is a risk factor for unplanned readmission.

The ‘Being Your Best’ program aims to build resilience and help overcome vulnerabilities arising from frailty and recent hospitalisation, using evidence-based, co-designed and patient-driven strategies. The program will be initially piloted with recently hospitalised people aged ≥65 years. Interventions will be co-designed, use needs-based assessment and be guided by participant choice to maximise compliance. They will include: physical mobility and exercise, nutritional support, cognitive stimulation and/or social support. Family members will be asked to assess their experience and the impact of the program. Program sustainability and evaluation will occur at 12 months.

We will also map frailty trajectories and hospital admissions in population data sets: the Australian Longitudinal Study of Women’s Health, 45 and Up study and Bolton Clarke Home Nursing Administrative Data Set. This data will also enable comparison of frailty and hospital readmission to population models of healthcare use.