Access to Adequate Outpatient Depression Care for Mothers in the USA: A Nationally Representative Population-Based Study

The Journal of Behavioral Health Services & Research (Impact Factor: 1.37). 01/2010; 38(2):191-204. DOI: 10.1007/s11414-009-9194-y


Maternal depression is often untreated, resulting in serious consequences for mothers and their children. Factors associated
with receipt of adequate treatment for depression were examined in a population-based sample of 2,130 mothers in the USA with
depression using data from the 1996–2005 Medical Expenditure Panel Survey. Chi-squared analyses were used to evaluate differences
in sociodemographic and health characteristics by maternal depression treatment status (none, some, and adequate). Multivariate
regression was used to model the odds of receiving some or adequate treatment, compared to none. Results indicated that only
34.8% of mothers in the USA with depression received adequate treatment. Mothers not in the paid workforce and those with
health insurance were more likely to receive treatment, while minority mothers and those with less education were less likely
to receive treatment. Understanding disparities in receipt of adequate treatment is critical to designing effective interventions,
reducing treatment inequities, and ultimately improving the mental health and health of mothers and their families.

Keywordsmaternal depression–access to treatment for depression–adequacy of treatment for depression–disparities in treatment for depression–population-based study–Medical Expenditure Panel Survey (MEPS)

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    • "Although major depressive disorder is the most common diagnosis in these ICD-9 codes, other variants of depression including bipolar disorder are included. We note that 92% of the sample have the 311 code reflecting major depressive disorder, a rate that compares favorably (i.e., 94%) to other studies of depression using the MEPS (Witt et al., 2011). Moreover, using both the 296 and 311 codes is a common strategy in studies of depression using the MEPS (Agency for Healthcare Research and Quality, 2012). "
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    ABSTRACT: Background: To determine the health care and labor productivity costs associated with major depressive disorder in high-risk, low-income mothers. Methods: This 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. Results: After 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. Conclusions: In 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.
    Full-text · Article · Oct 2015 · Journal of Affective Disorders
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    • "Furthermore, timely and effective treatment for mental health problems will be necessary to 'break the chain' of women's poor mental health. Many women may not be receiving adequate treatment (Witt et al., 2009) based on currently accepted guidelines, which may, in part, be caused by barriers to care. Accordingly, it is essential that health insurance policies include coverage for both mental health screening and treatment to ensure that these barriers do not prevent women from receiving adequate treatment. "
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    ABSTRACT: Mental health problems disproportionately affect women, particularly during the childbearing years. However, there is a paucity of research on the determinants of postpartum mental health problems using representative US populations. Taking a life course perspective, we determined the potential risk factors for postpartum mental health problems, with a particular focus on the role of mental health before and during pregnancy. We examined data on 1,863 mothers from 11 panels of the 1996-2006 Medical Expenditure Panel Survey. Poor postpartum mental health was defined using self-reports of mental health conditions, symptoms of mental health conditions, or global mental health ratings of "fair" or "poor." Of the women included, 9.5% reported experiencing postpartum mental health problems, with over half of these women reporting a history of poor mental health. Poor prepregnancy mental health and poor antepartum mental health both independently increased the odds of having postpartum mental health problems. Staged multivariate analyses revealed that poor antepartum mental health attenuated the relationship between prepregnancy and postpartum mental health problems. Additionally, significant disparities exist in women's report of postpartum mental health status. Although poor antepartum mental health is the strongest predictor of postpartum mental health problems, prepregnancy mental health is also important. Accordingly, health care providers should identify, treat, and follow women with a history of poor mental health because they are particularly susceptible to postpartum mental health problems. This will ensure that women and their children are in the best possible health and mental health during the postpartum period and beyond.
    Full-text · Article · Feb 2011 · Women s Health Issues
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    ABSTRACT: This paper treats the problem of estimating the baud rate of digital communication signals with application to automatic signal recognition. We estimate the baud rate from short-duration data segments by seeking the baud period that is “most” commensurate with a set of transition measurements. A technique for generating a set of candidate baud periods is described. Next, the modified Euclidean algorithm is used to find the greatest common factor of this set. The greatest common factor is another candidate for the baud period and is appended to the set. Then a quality factor is calculated for each candidate baud period. Optimality is achieved by choosing the baud period with the maximum quality factor. The algorithm's performance is investigated by numerical simulations
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