Annual direct health care expenditures and employee absenteeism costs in high-risk, low-income mothers with major depression

•We determine health care and employment costs in high-risk mothers with depression.•We use data from the nationally-representative Medical Expenditure Panel Survey.•Depressed mothers had higher insurer and out-of-pocket expenses.•Depressed mothers were more likely to have been unemployed and missed work days.•Depression increased annual direct health care and indirect costs by $2.41 billion.

BackgroundTo determine the health care and labor productivity costs associated with major depressive disorder in high-risk, low-income mothers.MethodsThis study was conducted using the 1996-2011 Medical Expenditure Panel Survey (MEPS). The MEPS is a nationally-representative database that includes information on health care utilization and expenditures for the civilian, non-institutionalized population in the United States. High-risk mothers were between the ages of 18-35 years, and either unmarried, receiving Medicaid, or with incomes less than 300% of the Federal Poverty Level. Mothers were categorized as being depressed if they had an ICD-9 diagnosis code of 296 or 311 (N=2310) or not depressed (N=18,221). Insurer expenditures, out-of-pocket (OOP) expenses, and lost wage earnings were calculated.ResultsAfter controlling for comorbidities, demographics, region, and year, high-risk depressed mothers were more likely to incur insurer (0.84 vs. 0.79) and OOP expenses (0.84 vs. 0.81) and to have higher insurer ($4448 vs. $3072) and OOP expenses ($794 vs. $523). Depression significantly increased the likelihood of missing work days (OR=1.40; p<0.01). Depression increased overall direct health care expenditures by $1.89 billion (range=$1.28-$2.60 billion) and indirect costs by $523 million annually, with a range of $353-$719 million.ConclusionsIn this high-risk population, the direct and indirect aggregate costs of depression-related to health care expenditures and lost work productivity were substantial. These findings establish a quantifiable cost for policy makers and highlight the need to target this population for prevention and treatment efforts.