Identifying common patterns of health services use: a longitudinal study of older Swiss adults' care trajectories.

BACKGROUND

Population ageing puts pressure on health systems initially designed to handle acute and episodic illnesses. Segmenting an ageing population based on its healthcare utilization may enable policymakers to undertake evidence-based resource planning. We aimed to derive a typology of healthcare utilization trajectories in Swiss older adults.

METHODS

Our work used data from the Lc65 + study, a population-based cohort of individuals aged 65 to 70 years at enrolment. The dimensions of healthcare utilization considered were ambulatory care, emergency care, hospitalizations, professional home care and nursing home stay. We applied the Sequence Analysis framework, within which we quantified the variation between each multidimensional pair of sequences, implemented a clustering procedure that grouped together older persons with similar profiles of health services use, and characterized clusters of individuals using selected baseline covariates.

RESULTS

Healthcare utilization trajectories were analysed for 2271 community-dwelling older adults over a period of 11 years. Six homogeneous subgroups were identified: constant low utilization (83.3% of participants), increased utilization (4.9%), late health deterioration (4.4%), ambulatory care to nursing home (1.5%), early fatal event (3.8%) and high ambulatory care (2.1%). Associations were found between cluster membership and age, sex, household composition, self-perceived health, grip strength measurement, comorbidities, and functional dependency.

CONCLUSIONS

The heterogeneous healthcare utilization profiles can be clustered into six common patterns. Different manifestations of functional decline were apparent in two distinct trajectory groups featuring regular home care use. Furthermore, a small proportion of individuals with a unique set of characteristics was related to the highest levels of ambulatory and emergency care use. New research avenues are outlined to investigate time-varying effects of health factors inside the clusters containing most unfavourable outcomes.