We know that health status in older people is heterogeneous and that many need complex care. What is now required is a comprehensive description of this heterogeneity and the estimation of its effects on patterns of service utilization.
This study examines the possibility of classifying older people according to their complex health conditions and whether the way in which they consume services differs based on these classes.
We used latent class analysis to model heterogeneity and classify community living elderly into homogenous health state categories (ie, health profiles). The number of health profiles present in the sample was revealed using 17 health indicators collected at baseline in the demonstration project of SIPA (French acronym for System of Integrated Care for the frail elderly), a system of integrated care for frail older people (n = 1164). These profiles were then used in 2-part econometric models to study access and costs of several measures of services using data collected prospectively over the 22-months of the SIPA trial.
We identified 4 substantially meaningful health profiles (prevalence: 23%, 11%, 36%, 30%) characterized by differences along the physical, cognitive, and disability dimensions of health. Subsequent econometric modeling showed a differential effect of health profiles on use and costs along the continuum of health and social services.
For older people with complex care needs, classification into homogeneous health subgroups unmasks differences in utilization patterns that can be used by decision makers in their attempt to improve the trajectory of care and adjust the distribution of resources to the needs of older people.