Depression, Healthcare Utilization, and Death in Heart Failure

Abstract

Background— The increasing prevalence of heart failure (HF) and high associated costs have spurred investigation of factors leading to adverse outcomes in patients with HF. Studies to date report inconsistent evidence on the link between depression and outcomes with only limited data on emergency department and outpatient visits. Methods and Results— Olmsted, Dodge, and Fillmore county, Minnesota residents with HF were prospectively recruited between October 2007 and December 2010 and completed a 1-time 9-item Patient Health Questionnaire for depression categorized as: none to minimal (Patient Health Questionnaire score, 0–4), mild (5–9), or moderate to severe (≥10). Andersen-Gill models were used to determine whether depression predicted hospitalizations and emergency department visits, whereas negative binomial regression models explored the association of depression with outpatient visits. Cox proportional hazards regression characterized the relationship between depression and all-cause mortality. Among 402 patients with HF (mean age, 73±13 years; 58% men), 15% had moderate to severe depression, 26% mild, and 59% none to minimal depression. During a mean follow-up of 1.6 years, 781 hospitalizations, 1000 emergency department visits, 15 515 outpatient visits, and 74 deaths occurred. After adjustment, moderate to severe depression was associated with nearly a 2-fold increased risk of hospitalization (hazard ratio, 1.79; 95% confidence interval, 1.30–2.47) and emergency department visits (hazard ratio, 1.83; 95% confidence interval, 1.34–2.50), a modest increase in outpatient visits (rate ratio, 1.20; 95% confidence interval, 1.00–1.45), and a 4-fold increase in all-cause mortality (hazard ratio, 4.06; 95% confidence interval, 2.35–7.01). Conclusions— In this prospective cohort study, depression independently predicted an increase in the use of healthcare resources and mortality. Greater recognition and management of depression in HF may optimize clinical outcomes and resource utilization.