Determinants of remote measurement-based care uptake in a safety net outpatient psychiatry department as part of learning health system transition.

Introduction: Behavioral measurement-based care (MBC) can improve patient outcomes and has also been advanced as a critical learning health system (LHS) tool for identifying and mitigating potential disparities in mental health treatment. However, little is known about the uptake of remote behavioral MBC in safety net settings, or possible disparities occurring in remote MBC implementation. Methods: This study uses electronic health record data to study variation in completion rates at the clinic and patient level of a remote MBC symptom measure tool during the first 6 months of implementation at three adult outpatient psychiatry clinics in a safety net health system. Provider-reported barriers to MBC adoption were also measured using repeated surveys at one of the three sites. Results: Out of 1219 patients who were sent an MBC measure request, uptake of completing at least one measure varied by clinic: General Adult Clinic, 38% (n = 262 of 696); Substance Use Clinic, 28% (n = 73 of 265); and Transitions Clinic, 17% (n = 44 of 258). Compared with White patients, Black and Portuguese or Brazilian patients had lower uptake. Older patients also had lower uptake. Spanish language of care was associated with much lower uptake at the patient level. Significant patient-level disparities in uptake persisted after adjusting for the clinic, mental health diagnoses, and number of measure requests sent. Providers cited time within visits and bandwidth in their workflow as the greatest consistent barriers to discussing MBC results with patients. Conclusions: There are significant disparities in MBC uptake at the patient and clinic level. From an LHS data infrastructure perspective, safety net health systems may need to address the need for possible ways to adapt MBC to better fit their populations and clinical needs, or identify targeted implementation strategies to close data gaps for the identified disparity populations.

Head Injury and Associated Sequelae in Individuals Seeking Asylum in the United States: A Retrospective Mixed-Methods Review of Medico-Legal Affidavits.

People seeking asylum are susceptible to head injury (HI) due to exposure to various forms of violence including war, torture, or interpersonal violence. Yet, the extents to which clinicians assess HI, and if so, what the associated characteristics are, are not well known. We analyzed 200 U.S.-based medico-legal affidavits using descriptive, multivariate regression, and thematic analysis. Head injury was documented in 38% of affidavits. Those who experienced physical violence were eight times likelier to experience HI than those who did not experience physical violence. Five themes emerged: (1) HI occurred commonly in the context of interpersonal violence (44%), followed by militarized violence (33%); (2) mechanisms of HI included direct blows to the head and asphyxiation, suggesting potential for both traumatic brain injury and brain injury from oxygen deprivation; (3) HI was often recurrent and concurrent with other physical injuries; (4) co-morbid psychiatric and post-concussive symptoms made it challenging to assess neurological and psychiatric etiologies; and (5) overall, there was a paucity of assessments and documentation of HI and sequelae. Among individuals assessed for asylum claims, HI is common, often recurrent, occurring in the context of interpersonal violence, and concurrent with psychological and other physical trauma. Physical violence is an important risk factor for HI, which should be assessed when physical violence is reported.

Structural racism and racial health disparities at the state level: A latent variable approach.

Introduction Structural racism is increasingly being recognized as a fundamental cause of racial health disparities. We used a novel measure of structural racism at the state level to examine the relationship between structural racism and disparities in death rates from firearm homicide, infant mortality, HIV, diabetes, stroke, hypertension, asthma, and kidney disease between non-Hispanic Black and non-Hispanic White people in the United States. Methods We used confirmatory factor analysis to measure the latent construct of structural racism for all 50 states. The model included seven indicators across the structural racism domains of residential segregation, economic status/employment, education, incarceration, political participation and representation, environmental racism, and racial equity inclusion. Weights for each of the indicators were determined by examining alternative models and selecting the model with the best fit statistics. The resulting factor scores, representing the level of structural racism in each state across the seven domains, were then used as predictor variables in a series of linear regressions with the ratio of Black to White death rates for each health outcome as the dependent variables. Results We found significant relationships between higher levels of the latent structural racism measure and greater disparities between non-Hispanic Black and non-Hispanic White people in age-adjusted death rates for firearm homicide, infant mortality, HIV, asthma, and obesity. The magnitude of this relationship was greatest for firearm homicide, with each one standard deviation increase in a state's structural racism factor score being associated with an increase of 4.54 (95% CI, 2.91-6.17) in that state's Black-White firearm homicide rate ratio. Conclusions This research provides further evidence that structural racism is a fundamental cause of racial health disparities and that to repair these inequities, macro-level changes in societal structures, institutions, resource allocation, representation, and power will be necessary.

Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level.

INTRODUCTION: Although structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population. METHODS: We used confirmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. RESULTS: There were profound differences in the magnitude of structural racism across cities. There were also striking differences in the magnitude of the racial disparity in firearm homicide across cities. Structural racism was a significant predictor of the magnitude of these racial disparities in firearm homicide. Each one standard deviation increase in the structural racism factor score increased the firearm homicide rate ratio by a factor of approximately 1.2 (95% confidence interval, 1.1-1.3). CONCLUSIONS: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.

Measuring Structural Racism and Its Association with Racial Disparities in Firearm Homicide.

INTRODUCTION: Structural racism is strongly related to racial health disparities. However, surprisingly few studies have developed empirical tools to measure structural racism. In addition, the few measures that have been employed have only considered structural racism at the neighborhood level. To expand upon previous studies, this paper uses a novel measure to measure structural racism at the county level for the non-Hispanic Black population. METHODS: We used confirmatory factor analysis to create a model to measure the latent construct of structural racism for 1181 US counties. The model included five indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status/wealth. Structural equation modeling and factor analysis were used to generate factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each county. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. RESULTS: Our calculations revealed striking geographic differences across counties in the magnitude of structural racism, with the highest values generally being observed in the Midwest and Northeast. Structural racism was significantly associated with higher Black firearm homicide rates, lower White homicide rates, and a higher Black-White racial disparity in firearm homicide. CONCLUSIONS: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the county level.