Objective This study compared trends in racial-ethnic disparities in mental health care access among whites, blacks, Hispanics, and Asians by using the Institute of Medicine definition of disparities as all differences except those due to clinical appropriateness, clinical need, and patient preferences. Methods Racial-ethnic disparities in mental health care access were examined by using data from a nationally representative sample of 214,597 adults from the 2004–2012 Medical Expenditure Panel Surveys. The main outcome measures included three mental health care access measures (use of any mental health care, any outpatient care, and any psychotropic medication in the past year). Results Significant disparities were found in 2004-05 and in 2011-12 for all three racial-ethnic minority groups compared with whites in all three measures of access. Between 2004 and 2012, black-white disparities in any mental health care and any psychotropic medication use increased, respectively, from 8.2% to 10.8% and from 7.6% to 10.0%. Similarly, Hispanic-white disparities in any mental health care and any psychotropic medication use increased, respectively, from 7.9% to 10.2% and 6.7% to 9.4%. Conclusions No reductions in racial-ethnic disparities in access to mental health care were identified between 2004 and 2012. For blacks and Hispanics, disparities were exacerbated over this period. Clinical interventions that improve identification of symptoms of mental illness, expansion of health insurance, and other policy interventions that remove financial barriers to access may help to reduce these disparities.

Natural language processing (NLP) and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain. Participants responded to structured mental and physical health instruments at multiple follow-up points. Outcome variables of interest were suicidal ideation and psychiatric symptoms (GHQ-12). Predictor variables included structured items (e.g., relating to sleep and well-being) and responses to one unstructured question, “how do you feel today?” We compared NLP-based models using the unstructured question with logistic regression prediction models using structured data. The PPV, sensitivity, and specificity for NLP-based models of suicidal ideation were 0.61, 0.56, and 0.57, respectively, compared to 0.73, 0.76, and 0.62 of structured data-based models. The PPV, sensitivity, and specificity for NLP-based models of heightened psychiatric symptoms (GHQ-12 ≥ 4) were 0.56, 0.59, and 0.60, respectively, compared to 0.79, 0.79, and 0.85 in structured models. NLP-based models were able to generate relatively high predictive values based solely on responses to a simple general mood question. These models have promise for rapidly identifying persons at risk of suicide or psychological distress and could provide a low-cost screening alternative in settings where lengthy structured item surveys are not feasible.

Health care utilization patterns for gender minority Medicare beneficiaries (those who are transgender or gender nonbinary people) are largely unknown. We identified gender minority beneficiaries using a diagnosis-code algorithm and compared them to a 5 percent random sample of non-gender minority beneficiaries from the period 2009-14 in terms of mental health and chronic diseases, use of preventive and mental health care, hospitalizations, and emergency department (ED) visits. Gender minority beneficiaries experienced more disability and mental illness. When we adjusted for age and mental health, we found that they used more mental health care. And when we adjusted for age and chronic conditions, we found that they were more likely to be hospitalized and to visit the ED. There were several small but significant differences in preventive care use. Findings were similar for disabled and older cohorts. These findings underscore the need to capture gender identity in health data to better address this population's health needs.

Racial/ethnic minorities in the United States are more likely than Whites to have severe and persistent mental disorders and less likely to access mental health care. This comprehensive review evaluates studies of mental health and mental health care disparities funded by the National Institute of Mental Health (NIMH) to provide a benchmark for the 2015 NIMH revised strategic plan. A total of 615 articles were categorized into five pathways underlying mental health care and three pathways underlying mental health disparities. Identified studies demonstrate that socioeconomic mechanisms and demographic moderators of disparities in mental health status and treatment are well described, as are treatment options that support diverse patient needs. In contrast, there is a need for studies that focus on community- and policy-level predictors of mental health care disparities, link discrimination- and trauma-induced neurobiological pathways to disparities in mental illness, assess the cost effectiveness of disparities reduction programs, and scale up culturally adapted interventions.