Population-Level Disparities in Exposure to COVID-19 Mitigation Policies, April 2020-April 2021.

CONTEXT: Studies have found that COVID-19 stay-at-home orders (SHOs) and face mask policies (FMPs) were associated with reduced COVID-19 transmission and deaths. But it is unknown whether exposure to these policies varied by sociodemographic characteristics across the US population. OBJECTIVE: The goal of this study was to quantify and characterize the sociodemographic characteristics and geographic distribution of populations exposed to evidence-based COVID-19 mitigation policies. DESIGN: We obtained statewide SHOs and FMPs for all US counties from April 10, 2020, to April 10, 2021, calculated median policy lengths, and categorized counties into 4 groups based on length of policy exposure: low SHO-low FMP, high SHO-low FMP, low SHO-high FMP, and high SHO-high FMP. We described exposure groups by COVID-19 cumulative case/death and vaccination rates and county sociodemographic characteristics. SETTING: In total, 3142 counties from all 50 states and Washington, District of Columbia, were included in the analysis. MAIN OUTCOME MEASURES: County-level sociodemographic factors and county cumulative rates for COVID-19 cases, deaths, and vaccinations. RESULTS: The largest percentage of the US population lived in counties with high exposure to SHOs and FMPs. However, populations living in high SHO-high FMP counties had the lowest percent non-Hispanic Black (NHB) and highest percent non-Hispanic White (NHW) populations. Populations living in high SHO-low FMP counties had the highest percent NHB and Hispanic populations and the lowest percent NHW population. CONCLUSION: This study identified county-level racial, ethnic, and sociodemographic disparities in exposure to evidence-based statewide COVID-19 mitigation policies. POLICY IMPLICATIONS: Exposure to evidence-based policies is an important consideration for studies evaluating the root causes of health inequities.

Opportunities and Challenges to Advance Health Equity Using Digital Health Tools in Underserved Communities in Southeast US: A Mixed Methods Study.

INTRODUCTION: Over the last 30 years, the adoption of health information technology and digital health tools (DHTs) into the US health system has been instrumental to improving access to care, especially for people living in rural, underserved, and underrepresented communities. Despite widespread adoption of DHTs by primary care clinicians, documented challenges have contributed to inequitable use and benefit. The COVID-19 pandemic necessitated rapid adoption of DHTs, accelerated by state and federal policy changes, in order to meet patient needs and ensure access to care. METHODS: The Digital Health Tools Study employed a mixed methods approach to assess adoption and use of DHTs by primary care clinicians in southeastern states and identify individual- and practice-level barriers and facilitators to DHT implementation. A survey was conducted using a multi-modal recruitment strategy: newsletters, meeting/conference presentations, social media, and emails/calls. Focus groups were conducted to assess priorities, barriers, and facilitators and were recorded/transcribed verbatim. Descriptive statistics were calculated for survey results, produced for the whole sample, and stratified by state. Thematic analysis was conducted of focus group transcripts. RESULTS: There were 1215 survey respondents. About 55 participants who had missing demographic information were excluded from the analysis. About 99% of clinicians used DHTs in the last 5 years, modalities included: telehealth (66%), electronic health records (EHRs; 66%), patient portals (49%), health information exchange (HIE; 41%), prescription drug monitoring programs (39%), remote/home monitoring (27%), and wearable devices (22%). Time (53%) and cost (51%) were identified as barriers. About 61% and 75% of clinicians reported being "satisfied" to "very satisfied" with telemedicine and EHRs, respectively. Seven focus groups with 25 clinicians were conducted and indicated COVID-19 and the use of supplemental tools/apps to connect patients to resources as major motivators for adopting DHTs. Challenges included incomplete and difficult-to-utilize HIE interfaces for providers and internet/broadband access and poor connectivity for patients. CONCLUSIONS: This study describes the impact adopting DHTs by primary care clinicians has on expanded access to healthcare and reducing health disparities in regions with longstanding health and social inequities. The findings identify opportunities to leverage DHTs to advance health equity and highlight opportunities for policy improvement.

Interpersonal Primary Care Continuity for Chronic Conditions Is Associated with Fewer Hospitalizations and Emergency Department Visits Among Medicaid Enrollees.

BACKGROUND: Interpersonal primary care continuity or chronic condition continuity (CCC) is associated with improved health outcomes. Ambulatory care-sensitive conditions (ACSC) are best managed in a primary care setting, and chronic ACSC (CACSC) require management over time. However, current measures do not measure continuity for specific conditions or the impact of continuity for chronic conditions on health outcomes. The purpose of this study was to design a novel measure of CCC for CACSC in primary care and determine its association with health care utilization. METHODS: We conducted a cross-sectional analysis of continuously enrolled, nondual eligible adult Medicaid enrollees with a diagnosis of a CACSC using 2009 Medicaid Analytic eXtract files from 26 states. We conducted adjusted and unadjusted logistic regression models of the relationship between patient continuity status and emergency department (ED) visits and hospitalizations. Models were adjusted for age, sex, race/ethnicity, comorbidity, and rurality. We defined CCC for CACSC as at least 2 outpatient visits with any primary care physician for a CACSC in the year, and (2) more than 50% of outpatient CACSC visits with a single PCP. RESULTS: There were 2,674,587 enrollees with CACSC and 36.3% had CCC for CACSC visits. In fully adjusted models, enrollees with CCC were 28% less likely to have ED visits compared with those without CCC (aOR = 0.71, 95% CI = 0.71 - 0.72) and were 67% less likely to have hospitalization than those without CCC (aOR = 0.33, 95% CI = 0.32-0.33). CONCLUSIONS: CCC for CACSCs was associated with fewer ED visits and hospitalizations in a nationally representative sample of Medicaid enrollees.

Creation of a Longitudinal Legal Data Set to Support Legal Epidemiology Studies of Mental Health Insurance Legislation.

OBJECTIVE: This article describes policy surveillance methodology used to track changes in the comprehensiveness of state mental health insurance laws over 23 years, resulting in a data set that supports legal epidemiology studies measuring effects of these laws on mental health outcomes. METHODS: Structured policy surveillance methods, including a coding protocol, blind coding of laws in 10% of states, and consensus meetings, were used to track changes in state laws from 1997 through 2019-2020. The legal database Westlaw was used to identify relevant statutes. The legal coding instrument included six questions across four themes: parity, mandated coverage, definitions of mental health conditions, and enforcement-compliance. Points (range 0-7) were assigned to reflect the laws' comprehensiveness and aid interpretation of changes over time. RESULTS: The search resulted in 147 coding time periods across 51 jurisdictions (50 states, District of Columbia). Intercoder consensus rates increased from 89% to 100% in the final round of blinded duplicate coding. Since 1997, average comprehensiveness scores increased from 1.31 to 3.82. In 1997, 41% of jurisdictions had a parity law, 28% mandated coverage, 31% defined mental health conditions, and 8% required state agency enforcement. In 2019-2020, 94% of jurisdictions had a parity law, 63% mandated coverage, 75% defined mental health conditions, and 29% required state enforcement efforts. CONCLUSIONS: Comprehensiveness of state mental health insurance laws increased from 1997 through 2019-2020. The State Mental Health Insurance Laws Dataset will enable evaluation research on effects of comprehensive legislation and cumulative impact.

Impact of Mental Health Insurance Legislation on Mental Health Treatment in a Longitudinal Sample of Adolescents.

BACKGROUND: Mental health insurance laws are intended to improve access to needed treatments and prevent discrimination in coverage for mental health conditions and other medical conditions. OBJECTIVES: The aim was to estimate the impact of these policies on mental health treatment utilization in a nationally representative longitudinal sample of youth followed through adulthood. METHODS: We used data from the 1997 National Longitudinal Survey of Youth and the Mental Health Insurance Laws data set. We specified a zero-inflated negative binomial regression model to estimate the relationship between mental health treatment utilization and law exposure while controlling for other explanatory variables. RESULTS: We found that the number of mental health treatment visits declined as cumulative exposure to mental health insurance legislation increased; a 10 unit (or 10.3%) increase in the law exposure strength resulted in a 4% decline in the number of mental health visits. We also found that state mental health insurance laws are associated with reducing mental health treatments and disparities within at-risk subgroups. CONCLUSIONS: Prolonged exposure to comprehensive mental health laws across a person's childhood and adolescence may reduce the demand for mental health visitations in adulthood, hence, reducing the burden on the payors and consumers. Further, as the exposure to the mental health law strengthened, the gap between at-risk subgroups was narrowed or eliminated at the highest policy exposure levels.

Variation in Reporting of the Race and Ethnicity of COVID-19 Cases and Deaths Across US States: April 12, 2020, and November 9, 2020.

Despite growing evidence that COVID-19 is disproportionately affecting communities of color, state-reported racial/ethnic data are insufficient to measure the true impact.We found that between April 12, 2020, and November 9, 2020, the number of US states reporting COVID-19 confirmed cases by race and ethnicity increased from 25 to 50 and 15 to 46, respectively. However, the percentage of confirmed cases reported with missing race remained high at both time points (29% on April 12; 23% on November 9). Our analysis demonstrates improvements in reporting race/ethnicity related to COVID-19 cases and deaths and highlights significant problems with the quality and contextualization of the data being reported.We discuss challenges for improving race/ethnicity data collection and reporting, along with opportunities to advance health equity through more robust data collection and contextualization. To mitigate the impact of COVID-19 on racial/ethnic minorities, accurate and high-quality demographic data are needed and should be analyzed in the context of the social and political determinants of health.

Population-Level Disparities in COVID-19: Measuring the Independent Association of the Proportion of Black Population on COVID-19 Cases and Deaths in US Counties.

CONTEXT: There is a need to understand population race and ethnicity disparities in the context of sociodemographic risk factors in the US experience of the COVID-19 pandemic. OBJECTIVE: Determine the association between county-level proportion of non-Hispanic Black (NHB) on county COVID-19 case and death rates and observe how this association was influenced by county sociodemographic and health care infrastructure characteristics. DESIGN AND SETTING: This was an ecologic analysis of US counties as of September 20, 2020, that employed stepwise construction of linear and negative binomial regression models. The primary independent variable was the proportion of NHB population in the county. Covariates included county demographic composition, proportion uninsured, proportion living in crowded households, proportion living in poverty, population density, state testing rate, Primary Care Health Professional Shortage Area status, and hospital beds per 1000 population. MAIN OUTCOME MEASURES: Outcomes were exponentiated COVID-19 cases per 100 000 population and COVID-19 deaths per 100 000 population. We produced county-level maps of the measures of interest. RESULTS: In total, 3044 of 3142 US counties were included. Bivariate relationships between the proportion of NHB in a county and county COVID-19 case (Exp ß = 1.026; 95% confidence interval [CI], 1.024-1.028; P < .001) and death rates (rate ratio [RR] = 1.032; 95% CI, 1.029-1.035; P < .001) were not attenuated in fully adjusted models. The adjusted association between the proportion of NHB population in a county and county COVID-19 case was Exp ß = 1.025 (95% CI, 1.023-1.027; P < .001) and the association with county death rates was RR = 1.034 (95% CI, 1.031-1.038; P < .001). CONCLUSIONS: The proportion of NHB people in a county was positively associated with county COVID-19 case and death rates and did not change in models that accounted for other socioecologic and health care infrastructure characteristics that have been hypothesized to account for the disproportionate impact of COVID-19 on racial and ethnic minority populations. Results can inform efforts to mitigate the impact of structural racism of COVID-19.

Applying a Health Equity Lens to Evaluate and Inform Policy.

Health disparities have persisted despite decades of efforts to eliminate them at the national, regional, state and local levels. Policies have been a driving force in creating and exacerbating health disparities, but they can also play a major role in eliminating disparities. Research evidence and input from affected community-level stakeholders are critical components of evidence-based health policy that will advance health equity. The Transdisciplinary Collaborative Center (TCC) for Health Disparities Research at Morehouse School of Medicine consists of five subprojects focused on studying and informing health equity policy related to maternal-child health, mental health, health information technology, diabetes, and leadership/workforce development. This article describes a "health equity lens" as defined, operationalized and applied by the TCC to inform health policy development, implementation, and analysis. Prioritizing health equity in laws and organizational policies provides an upstream foundation for ensuring that the laws are implemented at the midstream and downstream levels to advance health equity.

Health Policy Engagement Strategy for the Health Information Technology Policy Project of the Transdisciplinary Collaborative Center for Health Disparities Research.

Rulemaking is one of the most important ways the federal government makes public policy. It frequently has significant impact on individuals, communities, and organizations. Yet, few of those directly affected are familiar with the rulemaking process, and even fewer understand how it works. This article describes a case study of the Transdisciplinary Collaborative Center for Health Disparities Research Health Information Technology (TCC HIT) Policy Project's approach to health-policy engagement using: 1) social media; and 2) a webinar to educate stakeholders on the rulemaking process and increase their level of meaningful engagement with the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) proposed rule public comment submission. The webinar "Paying for Quality: What Is the Impact on Health Equity" was promoted through Twitter and held in June 2016. In total, we posted 19 tweets using two distinct hashtags (#MACRA4Equity, #MACRA2Equity) to raise awareness of the upcoming MACRA proposed rule and its possible effects on health equity. Overall, 252 individuals registered for the webinar, and more than half participated (n=133). Most (67%) registrants reported that health policy was not the primary focus of their current position. Based on information provided in the webinar, 95% agreed that their understanding of the topic improved. By the end of the webinar, 44% of participants indicated that they planned to submit public comments for MACRA, a 12% increase compared with those who planned to submit at the time of registration. The TCC health-policy engagement strategy demonstrates the feasibility of engaging a diverse audience around health policy issues, particularly those who are not typically engaged in policy work.

Analyzing State Autism Private Insurance Mandates for Allied Health Services: A Pilot Study.

Due to the prevalence, severity, and costs associated with autism spectrum disorders (ASDs), it has become a public health issue. In response, state governments have adopted ASD-specific private insurance mandates requiring coverage of ASD screening, diagnosis, and treatment. Despite rapid uptake of these laws, differences exist in the type and levels of coverage, especially for allied health services including occupational therapy. We piloted a structured legal research methodology to code ASD insurance mandates that impact allied health service provisions. State private insurance mandates were obtained from WestlawNext. A coding methodology was piloted on 14 states and included variables for age and service limits, treatments covered, and medical necessity. Coding methods were feasible and highly reliable among raters. Ten of 12 states had a coverage mandate, many with specific provisions for allied health providers. A full analysis of all 50 states is warranted to identify provisions affecting allied health providers serving individuals with ASD.