Racial and Ethnic Disparities in Treatment and Treatment type for Depression Among a 29 State Sample of Medicaid Recipients

Abstract

Objective

The purpose of this secondary data analysis was to describe disparities in depression treatment and treatment modality among adult Medicaid beneficiaries with depression from a nationally representative sample of Medicaid claims data, which includes 28 states and the District of Columbia.

Methods

This study uses Medicaid claims data extracted from the full 2008–2009 Medicaid Analytic Extract (MAX) file obtained from the Centers for Medicare and Medicaid Services (CMS) that includes 28 states and Washington DC. The primary outcome of this study was type of treatment for depression which consisted of 4 categories: Medication only, therapy only, medication and therapy, and no depression treatment. The secondary outcome was treatment for depression (Yes/No). Crude and adjusted odds ratios (cOR/aOR) were generated for univariate and multivariate models respectively; 95% confidence intervals (CI) of odds ratios and p-values were calculated.

Results

Depression treatment rates were lower for African Americans and Hispanics compared to whites, and the odds of African Americans were half that of whites for receiving depression treatment. A higher percentage of African Americans and Hispanics had no record of treatment compared to whites. Whites were more likely to have medication alone as a treatment option.

Conclusions

This study contributes to evidence on intersections of social factors and health outcomes and discusses healthcare engagement, stigma, and policy drivers of racial/ethnic disparities. The findings are important because they are the first to identify these disparities in rates and types of treatment among racial subgroups among Medicaid beneficiaries in this nationally representative sample.

Introduction

Access to mental health care services is critically important to timely and accurate diagnosis and efficacious treatment of depression. This is particularly true for Medicaid populations, the majority of whom have low income and are more likely to experience economic barriers to mental health care than individuals from higher socioeconomic strata¹. Further, a disproportionate number of African Americans and other minorities in the United States are Medicaid beneficiaries. African Americans and other ethnic minorities have worse access to mental health care and receive lower quality mental health care compared to whites. Among adult Medicaid beneficiaries, racial disparities in treatment rates for depression and treatment modalities for depression are understudied¹.

One six state analysis of racial/ethnic differences in Medicaid funded mental health services found lower utilization of services among African Americans and Hispanics¹. Also, whites were more likely to receive their treatment in community-based settings, while African Americans and Hispanics were more likely to receive their care in inpatient settings, emergency departments, and outpatient settings¹. Some studies have found that follow-up care after emergency mental health services is lower than for other ethnic groups, which further exacerbates mental health disparities among African Americans². Explanations for this disparity are unclear due to limitations of Medicaid claims research, however socioeconomic factors, including justice system involvement should be explored. These findings suggest that racial/ethnic disparities in mental health treatment found in the general population also exist among Medicaid beneficiaries. Medicaid plays a significant role in the lives of adults diagnosed with depression, which is responsible for approximately half of state expenditures on mental health³. Further work is needed to understand potential variations in depression treatment by race in order to effectively achieve racial/ethnic equity in mental health outcomes.

Medicaid beneficiaries with depression have more severe symptoms, are more likely to receive minimally adequate care, and are more expensive to treat due to related medical co-morbidities compared to patients with other health care coverage ^4,5. A 2010 study examining the quality of counseling and drug therapy received by Medicaid beneficiaries diagnosed and treated in specialty mental health care settings found that African Americans received lower rates of minimally adequate depression care than their White counterparts⁴. Thus, while the Medicaid population includes many low socioeconomic status (SES), high risk individuals, race may operate as an additional risk factor for inadequate depression treatment in this high-risk population.

The purpose of this secondary data analysis was to describe disparities in depression treatment and treatment modality among adult Medicaid beneficiaries with depression from a nationally representative sample of Medicaid claims data, which includes 28 states and the District of Columbia. Additionally, we explored secondary factors including income, neighborhood level variables, and medical co-morbidities. Further work is needed to understand the mechanisms for these disparities. There have been no previous studies of racial disparities in depression treatment in the Medicaid population in a nationally representative sample, which may help inform national trends. We hypothesized that there will be disparities in treatment by racial subgroups and that minorities will be less likely than whites to receive treatment for depression.

Methods

Study Population

We conducted a cross-sectional secondary analysis to examine racial disparities in depression treatment and treatment modality among adults with depression. The study population was drawn from 2008–2009 Medicaid Analytic eXtract (MAX) files from 28 states (Alabama, Arizona, Arkansas, California, Colorado, Connecticut, Florida, Georgia, Illinois, Indiana, Louisiana, Maryland, Massachusetts, Michigan, Mississippi, Missouri, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, and Washington) and the District of Columbia. Medicaid enrollees were included in this study based on the following criteria: 24 months of continuous enrollment or until death from 1/1/2008 to 12/31/2009, 18 to 64 years of age, have at least 1 billed claim from inpatient file or at least 2 billed claims from the outpatient file with diagnosis of depression using International Classification of Diseases, Ninth Revision (ICD-9), Clinical Modification codes of 296.20–296.25, 296.30–296.35, 298.0, and 311. The codes were chosen based on codes used in previous studies of depression using administrative claims data⁶. The diagnoses corresponding to these codes are provided in appendix B. MAX files provide the primary and secondary diagnosis codes for outpatient claims and all diagnosis codes for inpatient claims. Institutional Review Board approval for this study was obtained from Morehouse School of Medicine, and all patient records/information were anonymized and de-identified.

Measures

The primary outcome of this study was type of treatment for depression which consisted of 4 categories: Medication only, therapy only, medication and therapy, and no treatment for depression. The secondary outcome was treatment for depression (Yes/No), which was based on the primary outcome. The National Drug Code (NDC) variable from prescription claims was used to identify medication for depression (Appendix 1). Therapy for depression was identified by any of the following Current Procedural Terminology (CPT) codes in inpatient or outpatient claims: 90832, 90834, 90837, 90847, 90853, 96101–96103, 96105, 96111, 96116, 96118–96120, 96150–96155, 90785, 90839 and 90840.

The main predictor was race/ethnicity which was categorized into four groups: white, black, Hispanic and other (Asian, American Indian, Alaska Native, Pacific Islander, multiple races or unknown).

Covariates were sex, age, comorbidity and 5 zip-code-level variables of residence (median annual personal income, proportion of black residents, proportion of Hispanic residents, proportion of residents with less than high school diploma, and Gini coefficient). We categorized age into 4 groups (18–24, 25–39, 40–54, and 55–64). Comorbidity was calculated using the Elixhauser Comorbidity Index, a validated approach that summarizes disease burden and predicts risks by using administrative claims data⁷. Comorbidity index was categorized into 4 groups (0, 1, 2, and >=3). Zip-code-level covariates were acquired from 2010 U.S. Census data. We categorized median annual personal income into 4 groups (<20k dollars, 20k to <30k dollars, 30k to <40k dollars, and >=40k dollars), proportion of black residents into 3 groups (<10%, 10–20%, and >20%), proportion of Hispanic residents into 3 groups (<10%, 10–20%, and >20%), proportion of residents with less than high school diploma into 3 groups (<15%, 15–30%, and >30%), and Gini coefficient into 3 groups (<0.4, 0.4–0.5, and >0.5). In this study, Gini coefficient was used as a measure for inequality of income, and a value of 0 expressed perfect equality.

Statistical Analysis

Descriptive statistics analyses were performed for overall population and each of the race/ethnicity groups. Using type of treatment for depression as primary outcome, we performed univariate and multivariate multinomial logistic regression with ‘no treatment’ as the reference group. Using treatment for depression (Yes/No) as secondary outcome, we performed univariate and multivariate binomial logistic regression. Crude odds ratios (cOR) and adjusted odds ratios (aOR) were generated for univariate and multivariate models respectively; 95% confidence intervals (CI) of odds ratios and p-values were also calculated. Multivariate logistic regression was conducted based on 3 different models: race/ethnicity, sex and age were adjusted in Model 1; race/ethnicity, sex, age, and comorbidity were adjusted in Model 2; race/ethnicity, sex, age, comorbidity, and Zip-code-level covariates were adjusted in Model 3. Covariates were selected based on known associations with the outcome of interest, treatment or type of treatment of depression. There are established differences in treatment of depression by age⁸, gender⁹ and race/ethnicity^{10, 11, 12}. Additionally, the presence of comorbid conditions¹³ and neighborhood level social deprivation^14,15 have been associated with differences in depression treatment¹⁶. All p-values were two-sided and a p-value < 0.05 was considered statistically significant. SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA) was used to perform all analyses.

Results

In this secondary data analysis of a nationally representative sample of Medicaid claims data in 29 states that encompasses 80% of all Medicaid beneficiaries and 90% of minority Medicaid beneficiaries, there were a total of 599,421 beneficiaries with a diagnosis of depression in our final sample. Characteristics of the sample population and their zip codes of residence are shown in Table 1. Overall, the sample was 23.1% African American, 52.7% white, 9.0% Hispanic, and 15.1% from other Race/Ethnic groups. 75.7% of the study population was female and distributed across the age spectrum with the bulk of participants between ages 25 and 54, comorbidities were common as shown by the Elixhauser comorbidity Index. 58.2 % of the sample were from zip codes with a median income of $20,000 to $29,999, 43.4% were from zip codes that were<10% black, and the largest percentage (47.5%) lived in zip codes where 15–30% had less than a high school education, most (68.1%) lived in zip codes with a Gini Index between 0.4 and 05. There were notable differences between racial subgroups. blacks tended to have more comorbidities, live in poorer zip codes with a higher proportion of black, less educated residents and higher amount of income inequality when compared to whites. Hispanics were more likely to live in zip codes with poorer and less educated residents than whites. Hispanics tended to live in zip codes with more poor, uneducated, and Hispanic residents than whites.

Table 1.

Characteristics of 2008–2009 Medicaid Beneficiaries with a Diagnosis of Depression in 28 States and District of Columbia by Race (N=599,421)

	Overall (n=599421)		African American (n=138728)		Caucasian (n=316012)		Hispanic (n=53974)		Other1 (n=90707)
	N	%	N	%	N	%	N	%	N	%
Individual Level Variables
Any treatment for depression
Yes	513,907	85.7	111,187	80.1	278,404	88.1	45,758	84.8	78,558	86.6
No	85,514	14.3	27,541	19.9	37,608	11.9	8,216	15.2	12,149	13.4
Treatment type for depression
Medication alone	505424	84.3	108020	77.9	274858	87.0	45225	83.8	77321	85.2
Therapy alone	1317	0.2	619	0.5	416	0.1	76	0.1	206	0.2
Medication and therapy	7166	1.2	2548	1.8	3130	1.0	457	0.9	1031	1.1
No treatment	85514	14.3	27541	19.8	37608	11.9	8216	15.2	12149	13.4
Sex
Female	453,490	75.7	103,970	74.9	239,310	75.7	42,359	78.5	67,851	74.8
Male	145,931	24.3	34,758	25.1	76,702	24.3	11,615	21.5	22,856	25.2
Age group
18–24	81,335	13.6	19,870	14.3	44,536	14.1	8,358	15.5	8,571	9.4
25–39	188,803	31.5	42,888	30.9	107,784	34.1	17,375	32.2	20,756	22.9
40–54	225,158	37.6	55,969	40.3	112,418	35.6	19,215	35.6	37,556	41.4
55–64	104,125	17.4	20,001	14.4	51,274	16.2	9,026	16.7	23,824	26.3
Elixhauser comorbidity Index
0	200,702	33.5	39,428	28.4	108,650	34.4	19,996	37.0	32,628	36.0
1	136,072	22.7	28,708	20.7	72,465	22.9	13,060	24.2	21,839	24.1
2	90,271	15.1	21,062	15.2	47,669	15.1	8,085	15.0	13,455	14.8
>=3	172,376	28.8	49,530	35.7	87,228	27.6	12,833	23.8	22,785	25.1
Zip Code Level Variables
Median Personal Income
<20k	71,505	11.9	22,825	16.5	25,379	8.0	11,267	20.9	12,034	13.3
20k – <30k	349,110	58.2	80,220	57.8	188,781	59.7	30,544	56.6	49,565	54.6
30k– <40k	131,116	21.9	26,408	19.0	75,981	24.0	9,181	17.0	19,546	21.5
>=40k	47,690	8.0	9,275	6.7	25,871	8.2	2,982	5.5	9,562	10.5
Proportion of black residents
<10%	319,974	53.4	19,449	14.0	219,166	69.3	39,190	72.6	42,169	46.5
10–20%	84,132	14.0	18,060	13.0	44,515	14.1	7,198	13.3	14,359	15.8
>20%	195,315	32.6	101,219	73.0	52,331	16.6	7,586	14.1	34,179	37.7
Proportion of Hispanic residents
<10%	310,507	51.8	80,207	57.8	207,708	65.7	3,144	5.8	19,448	21.4
10–20%	84,716	14.1	20,677	14.9	45,348	14.4	4,591	8.5	14,100	15.5
>20%	204,198	34.1	37,844	27.3	62,956	19.9	46,239	85.7	57,159	63.0
Proportion with less than high school diploma
<15%	218,218	36.4	34,616	25.0	151,079	47.8	10,310	19.1	22,213	24.5
15–30%	284,691	47.5	82,561	59.5	140,965	44.6	21,422	39.7	39,743	43.8
>30%	96,512	16.1	21,551	15.5	23,968	7.6	22,242	41.2	28,751	31.7
Gini coefficient2 (0–1)
<0.4	122,237	20.4	17,253	12.4	79,973	25.3	12,201	22.6	12,810	14.1
0.4 – 0.5	408,478	68.1	94,581	68.2	213,563	67.6	36,849	68.3	63,485	70.0
>0.5	68,706	11.5	26,894	19.4	22,476	7.1	4,924	9.1	14,412	15.9

Values were presented as frequency (proportion).

¹Other races include Asian, american Indian, Alaska Native, Pacific Islander, multiple races or unknown.

²The Gini coefficient was used as a measure for inequality of income, and a value of 0 expressed perfect equality.

Overall 14.3% of depressed Medicaid beneficiaries had no record of treatment. 19.9% of blacks and 15.2% of Hispanics had no record of treatment compared only 11.9% of whites (table 1). Table 2 shows the odds ratios from logistic regression models for race differences for receiving any treatment when adjusted for covariates. African Americans, Hispanics, and people of other Race/ Ethnicities were less likely to receive treatment for depression, these associations changed very little after adjustment for individual and zip code level covariates. After full adjustment African Americans were 48% less likely (aOR=0.52; 95% CI= 0.82–0.86), Hispanics were 29% less likely (aOR=0.71; 95% CI=0.69–0.73), and Other Races/ ethnicities were 16 % less likely (aOR=0.84; 95% CI=0.82–0.86) to receive treatment for depression than whites.

Table 2:_.

Association between Race/Ethnicity and Treatment for Depression (Yes/No) among 2008–2009 Medicaid Beneficiaries with Depression in 28 States and District of Columbia Using Binomial Logistic Regression

Race/Ethnicity	Model #	OR	95% CI
African American	Unadjusted	0.55	0.54–0.56*
	Model 1	0.54	0.53–0.55*
	Model 2	0.49	0.48–0.50*
	Model 3	0.52	0.51–0.53*
Hispanic	Unadjusted	0.75	0.73–0.77*
	Model 1	0.75	0.73–0.77*
	Model 2	0.77	0.75–0.79*
	Model 3	0.71	0.69–0.73*
Other	Unadjusted	0.87	0.86–0.89*
	Model 1	0.80	0.78–0.82*
	Model 2	0.86	0.84–0.88*
	Model 3	0.84	0.82–0.86*

OR: Odds ratio; CI: confidence Interval.

^*Denotes significant results (P-value <0.05).

White people were the reference group in logistic regression models.

Model 1: sex and age group were adjusted. Model 2: sex, age group, and Elixhauser comorbidity were adjusted. Model 3: sex, age group, Elixhauser comorbidity, and zip code level variables (median personal income, proportion of black residents, proportion of Hispanic residents, proportion with less than high school diploma, and Gini coefficient) were adjusted.

Table 3 shows the odds ratios for race/ethnic differences in type of treatment form multinomial logistic regression models. After full adjustment blacks were 48% less likely (aOR=0.52; 95% CI=0.51–0.53) to receive medication alone, 57% more likely (aOR=1.57; 95% CI=1.35–1.82) to receive therapy alone, and 24% less likely (aOR=0.76; 95% CI=0.71–0.81) to receive therapy together with medication compared to whites. Hispanics were 29% less likely (aOR=0.71; 95% CI=0.69–0.73) to receive medication alone, and 28% less likely (aOR=0.72; 95% CI=0.64–0.80) to receive therapy plus medication than whites. The difference in therapy alone for Hispanics compared to whites was not significant after full adjustment. Beneficiaries of Other Race/Ethnicity were 16% less likely (aOR=0.84; 95% CI=0.82–0.86) to receive medication alone, 45% more likely (aOR=1.45; 95% CI=1.20–1.75) to receive therapy alone, and 12% less likely (aOR=0.88; 95% CI=0.82–0.96) to receive medication and therapy after full adjustment. A substantial change in the odds ratios toward the null (from 1.98 to 1.57) for therapy alone occurred for African Americans when we adjusted for zip code level variables. The adjustment for zip code level variables led to a reduction in the odds ratio from 0.95 to 0.76 for receiving medication and therapy together as compared to whites.

Table 3:

Association between Race/Ethnicity and Treatment Type among 2008–2009 Medicaid Beneficiaries with Depression in 28 States and District of Columbia Using Multinomial Logistic Regression

Race/Ethnicity	Model #	OR	95% CI	P-value
OR for Medication Alone vs. No Treatment
African American	Unadjusted	0.54	0.53–0.55	<.001
	Model 1	0.53	0.52–0.54	<.001
	Model 2	0.48	0.47–0.49	<.001
	Model 3	0.52	0.51–0.53	<.001
Hispanic	Unadjusted	0.75	0.73–0.77	<.001
	Model 1	0.75	0.73–0.77	<.001
	Model 2	0.77	0.75–0.79	<.001
	Model 3	0.71	0.69–0.73	<.001
Other	Unadjusted	0.87	0.85–0.89	<.001
	Model 1	0.80	0.78–0.82	<.001
	Model 2	0.86	0.84–0.88	<.001
	Model 3	0.84	0.82–0.86	<.001
OR for Therapy Alone vs. No Treatment
African American	Unadjusted	2.03	1.79–2.31	<.001
	Model 1	2.00	1.76–2.27	<.001
	Model 2	1.98	1.75–2.25	<.001
	Model 3	1.57	1.35–1.82	<.001
Hispanic	Unadjusted	0.84	0.65–1.07	0.154
	Model 1	0.85	0.66–1.08	0.178
	Model 2	0.85	0.66–1.09	0.194
	Model 3	1.07	0.82–1.39	0.619
Other	Unadjusted	1.53	1.30–1.81	<.001
	Model 1	1.40	1.19–1.66	<.001
	Model 2	1.41	1.19–1.67	<.001
	Model 3	1.45	1.20–1.75	<.001
OR for Medication & Therapy vs. No Treatment
African American	Unadjusted	1.11	1.05–1.17	<.001
	Model 1	1.09	1.03–1.15	0.003
	Model 2	0.95	0.89–0.99	0.044
	Model 3	0.76	0.71–0.81	<.001
Hispanic	Unadjusted	0.67	0.60–0.74	<.001
	Model 1	0.67	0.61–0.74	<.001
	Model 2	0.70	0.63–0.77	<.001
	Model 3	0.72	0.64–0.80	<.001
Other	Unadjusted	1.02	0.95–1.10	0.603
	Model 1	0.91	0.84–0.98	0.008
	Model 2	1.00	0.93–1.08	0.995
	Model 3	0.88	0.82–0.96	0.003

OR: Odds ratio; CI: confidence interval.

White people were the reference group in logistic regression models.

Model 1: sex and age group were adjusted. Model 2: sex, age group, and Elixhauser comorbidity were adjusted. Model 3: sex, age group, Elixhauser comorbidity, and zip code level variables (median personal income, proportion of black residents, proportion of Hispanic residents, proportion with less than high school diploma, and Gini coefficient) were adjusted.

Discussion

This cross-sectional secondary data analysis of Medicaid beneficiaries identified significant racial and ethnic disparities in rates of treatment and treatment modality among adults with a diagnosis of depression despite the fact that patients in the sample had the same health care coverage through Medicaid. African Americans diagnosed with depression were about 50% less likely to have received treatment for their depression when compared to whites diagnosed with depression. Hispanics with depression were about 25% less likely to have received treatment for their depression when compared to whites with depression. Blacks that received treatment were 48% less likely to receive medication and 55% more likely to receive therapy than whites. These findings are the first to identify these disparities in rates and types of treatment among racial subgroups among Medicaid beneficiaries in this nationally representative sample; this affirms the findings of smaller, state, regional and local studies, which have found similar disparities^1,17,18 and can support the development of interventions to achieve equity in depression treatment across racial subgroups.

There are a host of potential drivers of disparities in treatment utilization that operate at multiple levels. These include cultural differences in care seeking behaviors, stigma related to mental illness, provider implicit and explicit bias, and structural factors at the health system, community, and policy level that perpetuate racial/ethnic differences in treatment for depression^19,20,21. However, it is important to note that the inequalities we found in uptake and modality of treatment for depression across racial/ethnic groups persisted when individual and neighborhood level factors that might impact access to care or treatment including medical comorbidities, neighborhood income inequality, neighborhood poverty, and neighborhood educational context were included in the models. At the patient level, there are known cultural differences associated with care seeking behavior for mental health treatment. Stigma and mistrust of mental health professionals have been shown to deter treatment^19,22 by racial and ethnic minorities. The difference in treatment modality may also be related to culture. Research suggests that racial and ethnic minorities believe antidepressant medication less acceptable than whites²³. However, a different study found that blacks and whites have similar beliefs regarding the effectiveness of medication and therapy, whereas Hispanics were less likely than whites to believe that medication and therapy were effective²⁴.

Some care models that have been successful at overcoming cultural stigma and improving access for mental health treatment include the integrated primary care/behavioral health model. In this model, behavioral health services are embedded into the primary care practice²⁵. This model helps capture the substantial number of patients with mental health conditions who receive care in primary care, but do not receive care from mental health providers,^26,27. One policy barrier to successful implementation of this model is the ability to bill Medicaid for primary care and mental health visits on the same day. While some state Medicaid policy allow same-day billing of mental health and primary care in the same location, many state Medicaid programs continue to ban this practice²⁸.

This study has several limitations. While the Medicaid beneficiaries in this sample had comparable health care coverage, there may be geographic differences in access to care with respect to the location of mental health services available to Medicaid beneficiaries in a community. For example, rural Medicaid beneficiaries have poor access to mental health services^29,30,31. Additionally, the capacity of mental health providers to care for Medicaid patients may be limited as Medicaid reimbursement for mental health services is comparably low to that of private insurance or self-pay patients, and as a result, there are narrow networks of mental health specialists serving Medicaid patients³². This study uses health care claims data, which provide information on each claim about the type of service and the diagnosis codes that support the episode of care. Prescription drug claims note the type of drug prescribed and filled by the patient. Similarly, in order for a therapy claim to be generated, the patient would have had to attend the appointment. Because of this limited information, it is not possible to include measures of care quality unless using health care utilization or prescribing patterns as a proxy for quality of care. It is also not possible to measure if a treatment like medication or therapy was recommended by a clinician but declined by a patient. Also, there was insufficient information to assess the timing of the diagnosis, which has an impact on treatment uptake and modality. It cannot be assumed that all diagnoses captured in this dataset occurred at the same time and is thus a limiting factor when interpreting findings. It is also possible that some patients in the “no treatment category” may have sought some treatment that would not have shown up in the claims data, such as the use of therapists that may not accept Medicaid or self-medication through the use of supplements. It is unknown if the use of these services would be different by race within the low SES population enrolled in Medicaid. There may be differences in the providers available to different racial/ethnic groups, such as the availability of race and/or sex concordant providers, or age and perhaps corresponding knowledge in providers. Unfortunately, we did not have access to physician demographic data to examine whether these potential differences in providers contributed to the observed disparities in treatment. Finally, this data is from 2008 – 2009, which was the most current dataset the co-authors could access at the time. It predates the Affordable Care Act (ACA) and Medicaid expansion in many states, and policy interventions that have been associated with improved mental health outcomes³³. However, many of the states that have not expanded their Medicaid programs are home to large populations of racial and ethnic minorities. Even at a national level, disparities in access to and utilization of behavioral health treatment have persisted even after implementation of the ACA³⁴, suggesting that the disparities identified in this study may remain present.

Addressing mental health access and treatment disparities at the population level requires targeted policy and practice strategies. States that expanded their Medicaid program under the Affordable Care Act have seen improvements in the overall mental health of their residents and reductions in depression diagnoses in adults with chronic conditions³³. Previous Medicaid expansion has led to improved access to mental health services and mental health outcomes among Medicaid beneficiaries³⁵. More research is needed to understand whether and to what extent these policies have impacted racial and ethnic behavioral health disparities. Health care systems as a whole must adopt evidence-based practices such as measurement-based care, to better understand the experiences of racial and ethnic minorities receiving mental health services and to inform practice improvements that may increase the uptake of service use and improve the quality of care.

Conclusions

This analysis of depression treatment rates among Medicaid beneficiaries diagnosed with depression, revealed racial and ethnic disparities across 28 states including Washington DC. When compared to whites, African Americans and Hispanics appear to access care less often and were less likely to be prescribed medication for depression. These findings may provide the basis for exploring potential drivers of these differences that can serve as points of intervention to remove barriers to care for depression, improve quality and address disparities.

Highlights.

• Among a multi-state sample of adult Medicaid beneficiaries with a diagnosis of depression, there are racial disparities with respect to any treatment for depression and type treatment modality.

• This is the only study of a large, multi-state sample of actual treatment rates among adult Medicaid enrollees with depression verified by medical claims instead of self-reported survey data.

• This cross-sectional secondary data analysis of Medicaid beneficiaries in 28 states and the District of Columbia identified significant racial and ethnic disparities in rates of treatment and treatment modality among adults with a diagnosis of depression despite equality in access to care through Medicaid coverage.

• Addressing mental health access and treatment disparities at the population level requires targeted policy strategies, which may include Medicaid expansion.