Leonard E Egede1, Kinfe G Bishu2, Rebekah J Walker3, Clara E Dismuke4. 1. Center for Health Disparities Research, Department of Medicine, Medical University of South Carolina, Charleston, SC, United States; Department of Medicine, Division of General Internal Medicine and Geriatrics, Medical University of South Carolina, Charleston, SC, United States; Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson Veterans Affairs Medical Center, Charleston, SC, United States. Electronic address: egedel@musc.edu. 2. Center for Health Disparities Research, Department of Medicine, Medical University of South Carolina, Charleston, SC, United States; Department of Medicine, Division of General Internal Medicine and Geriatrics, Medical University of South Carolina, Charleston, SC, United States. 3. Center for Health Disparities Research, Department of Medicine, Medical University of South Carolina, Charleston, SC, United States; Department of Medicine, Division of General Internal Medicine and Geriatrics, Medical University of South Carolina, Charleston, SC, United States; Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson Veterans Affairs Medical Center, Charleston, SC, United States. 4. Center for Health Disparities Research, Department of Medicine, Medical University of South Carolina, Charleston, SC, United States; Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson Veterans Affairs Medical Center, Charleston, SC, United States.
Abstract
OBJECTIVE: This study used the Medical Expenditures Panel Survey (MEPS) to estimate the cost of diabetes, depression, and comorbid diabetes and depression over 8 years. METHODS: An 8-year pooled dataset was created using the household and medical provider components of MEPS. Medical expenditures were adjusted to a common 2014 dollar value. Analyses used responses of 147,095 individuals ≥18 years of age for the years 2004-2011. The dependent variable in this study was total healthcare expenditure and the primary independent variables were diabetes and depression status. A two-part (probit/GLM) model was used to estimate the annual medical spending and marginal effects were calculated for incremental cost. RESULTS: In the pooled sample, after adjusting for socio-demographic factors, comorbidities and time trend covariates, the incremental cost of depression only was $2654 (95% CI 2343-2966), diabetes was $2692 (95% CI 2338-3046), and both was $6037 (CI 95% 5243-6830) when compared to patients with none. Based on the unadjusted mean, annual average aggregate cost of depression only was estimated at $238.3 billion, diabetes only $150.1 billion and depression and diabetes together was $77.6 billion. CONCLUSION: Costs at both the individual and aggregate level are significant, with comorbid diagnoses resulting in higher incremental costs than the sum of the costs for each diagnosis alone. In addition, while the cost of depression increased over time, the cost of diabetes decreased over time, much due to decreased inpatient costs. This study highlights the tremendous cost savings possible through more aggressive screening, diagnosis, and treatment of depression.
OBJECTIVE: This study used the Medical Expenditures Panel Survey (MEPS) to estimate the cost of diabetes, depression, and comorbid diabetes and depression over 8 years. METHODS: An 8-year pooled dataset was created using the household and medical provider components of MEPS. Medical expenditures were adjusted to a common 2014 dollar value. Analyses used responses of 147,095 individuals ≥18 years of age for the years 2004-2011. The dependent variable in this study was total healthcare expenditure and the primary independent variables were diabetes and depression status. A two-part (probit/GLM) model was used to estimate the annual medical spending and marginal effects were calculated for incremental cost. RESULTS: In the pooled sample, after adjusting for socio-demographic factors, comorbidities and time trend covariates, the incremental cost of depression only was $2654 (95% CI 2343-2966), diabetes was $2692 (95% CI 2338-3046), and both was $6037 (CI 95% 5243-6830) when compared to patients with none. Based on the unadjusted mean, annual average aggregate cost of depression only was estimated at $238.3 billion, diabetes only $150.1 billion and depression and diabetes together was $77.6 billion. CONCLUSION: Costs at both the individual and aggregate level are significant, with comorbid diagnoses resulting in higher incremental costs than the sum of the costs for each diagnosis alone. In addition, while the cost of depression increased over time, the cost of diabetes decreased over time, much due to decreased inpatient costs. This study highlights the tremendous cost savings possible through more aggressive screening, diagnosis, and treatment of depression.
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