Methodology
To gain a broader understanding of the economic burden of mental health inequities in the United States, the School of Global Health at Meharry Medical College and the Deloitte Health Equity Institute conducted an equity-focused quantitative analysis of data from Komodo’s Healthcare Map,7 the Medical Expenditure Panel Survey from the Agency for Healthcare Research and Quality, the Centers for Disease Control and Prevention’s WONDER database, and the CDC’s National Hospital Ambulatory Medical Care Survey. This analysis expands on the methodology used within Thomas LaVeist, Darrell Gaskin, and Patrick Richard’s health disparities research described in the 2009 report, The Economic Burden of Health Inequalities in the United States.8 While previous analyses have quantified the impact of mental health on productivity, they have not attempted to quantify the cost due to inequities specifically. Quantifying productivity lost as a result of inequities in mental health outcomes by race and ethnicity enabled this analysis to achieve a nuanced view of the interconnected relationship between mental and physical health.
This report begins to quantify the disparities in outcomes—and the potential cost of mental inequity associated with those disparities—related to four different types of costs.
- Chronic physical health conditions: Potentially avoidable medical expenditures related to the intersection of mental health inequities and physical health outcomes
- Emergency department utilization: Medical expenditures related to untreated or undertreated mental health conditions that resulted in avoidable emergency department utilization
- Productivity loss: Economic cost resulting from loss of productivity in the workforce due to mental health conditions
- Premature death: Economic cost resulting from deaths due to suicide, deaths associated with substance use disorders, deaths due to inadequate mental health treatment, and deaths due to mental illness associated with comorbid illnesses
Click here to download the full version of the report, which highlights disparities experienced by three key population groups, segmented by race and ethnicity, socioeconomic status, and age. Although other populations experience inequities in mental and behavioral health like those found in this study and are deserving of similar research that focuses on their circumstances, this report can be seen as a small window into a large issue. Other population segmentations were considered, such as populations based on gender and sexual orientation, but due to data limitations they were ultimately not included as part of our initial analysis. The exclusion of other populations should not be misunderstood as an assessment of their importance, nor of the likely scale of mental health challenges among those groups. In fact, this report should be taken, in part, as a catalyst for additional research into additional populations.
Similar to the research approach utilized by Thomas LaVeist, Darrell Gaskin, and Patrick Richard in their analysis of the economic burden of health inequities, for each analysis, a “baseline population” was identified to highlight the inequities that exist across races and ethnicities, socioeconomic statuses, and ages.9 This baseline population is identified as having lower prevalence rates of chronic conditions, fewer days missed at work on average, or the lowest unemployment rates when compared across groups. This report proposes, based on the literature and original research, that, for groups experiencing higher incidence of chronic conditions compared to the “baseline population,” the gap that exists is impacted by mental health inequities. The hypothesis is that, with attention to the political and social determinants of health as well as increased access to equitable care, treatments, and supports, all prevalence rates, number of days missed from work, and unemployment would closely align with the baseline population. As a result of these lower incidences of chronic conditions, fewer missed days at work, and lower unemployment, the potential dollars that could be saved are calculated related to closing this gap.
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