Objectives: Whether and how symptom clusters are associated with care utilization remains understudied. This study aims to investigate the economic impact of symptom clusters.
Methods: We conducted cross-sectional analyses of data collected from 3255 older adults aged 60 years and over in Hong Kong using the Patient Health Questionnaire-9 and the Client Service Receipt Inventory to measure depressive symptoms and service utilization to calculate 1-year care expenditure. Based on Research Domain Criteria framework, we categorized depressive symptoms into four clusters: Negative Valance Systems and Externalizing (NVSE; anhedonia and depression), Negative Valance Systems and Internalizing (guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue, and appetite), and Cognitive and Sensorimotor Systems (CSS; concentration and psychomotor). Two-part models were used with four symptom clusters to estimate economic impacts on care utilization.
Results: Core affective symptoms had the largest economic impact on non-psychiatric care expenditure; a one-point increase in NVSE was associated with USD$ 571 additional non-psychiatric care expenditure. The economic impacts of CSS on non-psychiatric care expenditure was attenuated when the severity level of NVSE was higher.
Conclusions: Our findings highlight the importance of understanding economic impacts on care utilization based on symptom profiles with a particular emphasis on symptom combinations. Policymakers should optimize care allocation based on older adults' depressive symptom profiles rather than simply considering their depression sum-score or the severity defined by cut-off points.
Keywords: depression; health economics; health service research; mental health.
© 2021 John Wiley & Sons Ltd.