OBJECTIVES:Stroke patients with comorbid depression have a higher risk of recurrent stroke, functional impairment and increased healthcare costs. The odds of depression going undiagnosed are three times higher in stroke patients compared to non-stroke patients. This study evaluates the impact of depression diagnosis on health-related quality of life (HRQoL) and healthcare expenditures in stroke patients.

METHODS:A cross-sectional study was conducted in adults (aged≥18 years) with stroke using a pooled Medical Expenditure Panel Survey data (2016-2018). Stroke patients were classified based on their depression status using the ICD-10 CM codes of depression (“F32”) and PHQ-2 ≥3 into three groups: (i)Diagnosed depression, (ii) Undiagnosed depression (patients with PHQ-2≥3 and without ICD-10 diagnosis code of depression) and (iii) No depression. HRQoL was measured using the Physical and Mental Component Summary (PCS and MCS) scores obtained from the SF-12v2/VR-12. Other independent variables were selected using the Andersen Behavioural Model. Linear regression was used to examine the impact of depression status on the HRQoL. A generalized linear model with gamma distribution and log link function was used to analyze the healthcare expenditures. The group with “no depression” was used as a reference for the analyses.

RESULTS:Of the 2,584 adults with stroke, 12.85 % (n=332) had undiagnosed depression and 19.20% (n=496) had diagnosed depression. After adjusting for all the relevant covariates, individuals with undiagnosed (PCS=-5.27, MCS=-14.38, p<.0001) and diagnosed depression (PCS=-3.51, MCS=-9.90, p<.0001) displayed lower PCS and MCS scores. The incremental costs of stroke patients with undiagnosed and diagnosed depression were $4,409 (95% CI: -984; 9802; p=0.109) and $4,576(95% CI: -123; 9032; p=0.044) compared to stroke patients with no depression.

CONCLUSIONS:Undiagnosed depression in stroke patients is associated with lower HRQoL and higher healthcare costs. Novel interventions like personalized care and collaborative care models can be adopted in clinical settings to address these challenges.