Variation in service utilisation among the frail community dwelling elderly: implications for the design of integrated models of care

Abstract

Introduction: The challenge of healthy ageing today includes managing combinations of chronic disease, age related conditions, functional limitations and social or personal challenges. These needs are often referred in the gerontological and health sciences literature as ‘complex needs’ with multiple interacting problems. One way of examining those with complex needs is through the lens of the frail population. Frail individuals experience an accumulation of health problems placing them at a higher risk of functional and cognitive decline, and vulnerable to using hospital and nursing home services (Fried, Ferrucci et al. 2004). Consequentially a significant body of theoretical and practical literature exists relating to models of integrated care to manage frail populations and shift care from hospitals to the community (Beland and Hollander 2011; Kodner and Kyriacou 2000). However managing frailty may be more nuanced as we are beginning to understand that no two frail individuals are the same, and frail people will have different types and levels of needs and supports (British Geriatrics Society 2014). This challenges the appropriateness of designing integrated care models for frail populations based on a one-size-fits-all approach. We explored this issue by examining clusters in service use across the whole system of care among frail community-dwelling older adults in Ireland. Methods: Data were taken from The Irish Longitudinal Study on Ageing (TILDA), a prospective cohort study representing the community-dwelling population aged over 50 years in Ireland (Kenny 2013). We sampled adults aged 65 years+ in wave one (2009/11) who were classified as frail (22%) according to the Rockwood Frailty Deficit Accumulation Index(n=841). Measures of service use in the year preceding data collection included count data for six GP and hospital services and binary data for sixteen community health and social care services. We used latent class analysis (LCA) to model heterogeneity and classify individuals into homogeneous health service utilisation profiles, using the binary service use variables with the Bayesian Information Criteria (BIC) and substantive interpretability predicting the number of classes. LCA was performed using R software (version 3.1.2) with the BayesLCA package (White