Geographic and Racial/Ethnic Differences in Access to Methamphetamine Detoxification Services, United States, 2021.

INTRODUCTION: Methamphetamine detoxification before entering formal and longer term treatment may have a positive impact on treatment retention and success. Understanding geographic distribution of methamphetamine specialty detox services and differential access by race/ethnicity is critical for establishing policies that ensure equitable access across populations. METHODS: We used the Mental health and Addiction Treatment Tracking Repository to identify treatment facilities that offered any substance use detoxification in 2021 (N=2346) as well as the census block group in which they were located. We sourced data from the US Census Bureau to identify the percentage of a census block group that was White, Black, and Hispanic. We used logistic regression to model the availability of methamphetamine-specific detox, predicted by the percentage of a block group that was Black and Hispanic. We adjusted for relevant covariates and defined state as a random effect. We calculated model-based predicted probabilities. RESULTS: Over half (60%) of detox facilities offered additional detox services specifically for methamphetamine. Sixteen states had <10 methamphetamine-specific detox facilities. The predicted probability of methamphetamine-specific detox availability was 60% in census block groups with 0%-9% Black residents versus only 46% in census block groups with 90%-100% Black residents, and was 61% in census block groups with 0%-9% Hispanic residents versus 30% in census block groups with 90%-100% Hispanic residents. CONCLUSIONS: During an unprecedented national methamphetamine crisis, access to a critical health care service was disproportionately lower in communities that were predominately Black and Hispanic. We orient our findings around a discussion of health disparities, residential segregation, and the upstream causes of the systematic exclusion of minoritized communities from health care.

Association of copayments with healthcare utilization and expenditures among Medicaid enrollees with a substance use disorder.

BACKGROUND: The purpose of this study was to examine the association between copayments and healthcare utilization and expenditures among Medicaid enrollees with substance use disorders. METHODS: This study used claims data (2020-2021) from a private insurer participating in Arkansas's Medicaid expansion. We compared service utilization and expenditures for enrollees in different Medicaid program structures with varying copayments. Enrollees with incomes above 100 % FPL (N = 10,240) had copayments for substance use treatment services while enrollees below 100 % FPL (N = 2478) did not. Demographic, diagnostic, utilization, and cost information came from claims and enrollment information. The study identified substance use and clinical comorbidities using claims from July through December 2020 and evaluated utilization and costs in 2021. Generalized linear models (GLM) estimated outcomes using single equation and two-part modeling. A gamma distribution and log link were used to model expenditures, and negative binomial models were used to model utilization. A falsification test comparing behavioral health telemedicine utilization, which had no cost sharing in either group, assessed whether differences in the groups may be responsible for observed findings. RESULTS: Substance use enrollees with copayments were less likely to have a substance use or behavioral health outpatient (-0.04 PP adjusted; p = 0.001) or inpatient visit (-0.04 PP; p = 0.001) relative to their counterparts without copayments, equal to a 17 % reduction in substance use or behavioral health outpatient services and a nearly 50 % reduction in inpatient visits. The reduced utilization among enrollees with a copayment was associated with a significant reduction in total expenses ($954; p = 0.001) and expenses related to substance use or behavioral health services ($532; p = 0.001). For enrollees with at least one behavioral health visit, there were no differences in outpatient or inpatient utilization or expenditures between enrollees with and without copayments. Copayments had no association with non-behavioral health or telemedicine services where neither group had cost sharing. CONCLUSION: Copayments serve as an initial barrier to substance use treatment, but are not associated with the amount of healthcare utilization conditional on using services. Policy makers and insurers should consider the role of copayments for treatment services among enrollees with substance use disorders in Medicaid programs.

The association between rurality, dual Medicare/Medicaid eligibility and chronic conditions with telehealth utilization: An analysis of 2019-2020 national Medicare claims.

INTRODUCTION: Telehealth services have the potential to increase healthcare access among underserved populations, such as rural residents and racial/ethnic minority groups. The COVID-19 public health emergency led to unprecedented growth in telehealth utilization, but evidence suggests the growth has not been equitable across all patient populations. This study aimed to explore whether telehealth utilization and expansion changed equitably from 2019 to 2020 among sub-groups of Medicare beneficiaries. METHODS: We conducted an analysis of telehealth utilization among a 20% random sample of 2019-2020 Medicare beneficiaries on a national level. We fit multivariable logistic regression models and calculated average marginal effects (AME) to assess the association between demographic and clinical characteristics on telehealth utilization. RESULTS: We found telehealth utilization was less likely among non-Hispanic Black/African-American (2019: adjusted odds ratio [aOR] = 0.77, AME = -0.15; 2020: aOR = 0.85, AME = -3.50) and Hispanic (2019: aOR = 0.79, AME = -0.13; 2020: aOR = 0.87, AME = -2.89) beneficiaries, relative to non-Hispanic White beneficiaries in both 2019 and 2020, with larger disparities in 2020. Rural beneficiaries were more likely to utilize telehealth than urban beneficiaries in 2019 (aOR = 2.62, AME = 0.84), but less likely in 2020 (aOR = 0.57, AME = -14.47). In both years, dually eligible Medicare/Medicaid beneficiaries were more likely than non-dually eligible beneficiaries to utilize telehealth (2019: aOR = 4.75, AME = 0.84; 2020: aOR = 1.34, AME = 2.25). However, the effects of dual eligibility and rurality changed in both models as the number of chronic conditions increased. DISCUSSION: We found evidence of increasing disparities in telehealth utilization among several Medicare beneficiary sub-groups in 2020 relative to 2019, including individuals of minority race/ethnicity, rural residents, and dually eligible beneficiaries, with disparities increasing among individuals with more chronic conditions. Although telehealth has the potential to address health inequities, our findings suggest that many of the patients in greatest need of healthcare are least likely to utilize telehealth services.

Predicting pediatric severe asthma exacerbations: an administrative claims-based predictive model.

OBJECTIVE: Previous machine learning approaches fail to consider race and ethnicity and social determinants of health (SDOH) to predict childhood asthma exacerbations. A predictive model for asthma exacerbations in children is developed to explore the importance of race and ethnicity, rural-urban commuting area (RUCA) codes, the Child Opportunity Index (COI), and other ICD-10 SDOH in predicting asthma outcomes. METHODS: Insurance and coverage claims data from the Arkansas All-Payer Claims Database were used to capture risk factors. We identified a cohort of 22,631 children with asthma aged 5-18 years with 2 years of continuous Medicaid enrollment and at least one asthma diagnosis in 2018. The goal was to predict asthma-related hospitalizations and asthma-related emergency department (ED) visits in 2019. The analytic sample was 59% age 5-11 years, 39% White, 33% Black, and 6% Hispanic. Conditional random forest models were used to train the model. RESULTS: The model yielded an area under the curve (AUC) of 72%, sensitivity of 55% and specificity of 78% in the OOB samples and AUC of 73%, sensitivity of 58% and specificity of 77% in the training samples. Consistent with previous literature, asthma-related hospitalization or ED visits in the previous year (2018) were the two most important variables in predicting hospital or ED use in the following year (2019), followed by the total number of reliever and controller medications. CONCLUSIONS: Predictive models for asthma-related exacerbation achieved moderate accuracy, but race and ethnicity, ICD-10 SDOH, RUCA codes, and COI measures were not important in improving model accuracy.

Economic Report of General Inpatient Hospice in an Academic Medical Center.

This study examined if there was difference in cost of care after implementation of scattered bed inpatient hospice, first implemented in October 2021 in an Academic Medical Center in Arkansas. This retrospective, cross-sectional study compared the cost of care during the pre-implementation phase (n = 121, July 2020-March 2021) to patients admitted to hospice care (n = 84, October 2021-June 2022). Hospice length of stay (LOS) was 4 times longer than the LOS after a Do Not Resuscitate order (DNR) was placed for patients in the pre-implementation period. The end of life costs after the implementation of inpatient hospice was 69% less than the end of life costs in the pre-implementation period.

Asthma Quality Measurement and Adverse Outcomes in Medicaid-Enrolled Children.

OBJECTIVES: To determine the association between the asthma medication ratio (AMR) quality measure and adverse outcomes among Medicaid-enrolled children with asthma in Arkansas, given concerns regarding the utility of the AMR in evaluating pediatric risk of asthma-related adverse events (AAEs). METHODS: We used the Arkansas All-Payer Claims Database to identify Medicaid-enrolled children with asthma using a nonrestrictive case definition and additionally using the standard Healthcare Effectiveness Data and Information Set (HEDIS) persistent asthma definition. We assessed the AMR using the traditional dichotomous HEDIS AMR categorization and across 4 expanded AMR categories. Regression models assessed associations between AMR and AAE including hospitalization and emergency department utilization, with models conducted overall and by race and ethnicity. RESULTS: Of the 22 788 children in the analysis, 9.0% had an AAE (6.7% asthma-related emergency department visits; 3.0% asthma-related hospitalizations). We found poor correlation between AMR and AAE, with higher rates of AAE (10.5%) among children with AMR ≥0.5 compared with AMR <0.5 (8.5%; P < .001), and similar patterns stratified by racial and ethnic subgroups. Expanded AMR categorization revealed notable differences in associations between AMR and AAEs, compared with traditional dichotomous categorization, with worse performance in Black children. CONCLUSIONS: The AMR performed poorly in identifying risk of adverse outcomes among Medicaid-enrolled children with asthma. These findings underscore concerns of the utility of the AMR in population health management and reliance on restrictive HEDIS definitions. New population health frameworks incorporating broader considerations that accurately identify at-risk children are needed to improve equity in asthma management and outcomes.

Social determinants of health and COVID-19: An evaluation of racial and ethnic disparities in attitudes, practices, and mental health.

Previous evaluations have reported racial minorities feel they are at greater risk of contracting COVID-19, but that on average, they have better preventative practices, such as wearing face masks and avoiding large gatherings. In this study, we explored associations between social determinants of health (SDOH), race and ethnicity, COVID-19 practices and attitudes, and mental health outcomes during the pandemic. We examined associations between SDOHs and practices, attitudes, and mental health symptoms by race and ethnicity using multivariable linear and logistic regressions in 8582 Arkansan pulse poll respondents (September-December, 2020). Compared to White respondents, mean attitude and practice scores were greater (indicating safer) among Black (4.90 vs. 3.45 for attitudes; 2.63 vs. 2.41 for practices) and Hispanic respondents (4.26 vs. 3.45 for attitudes; 2.50 vs. 2.41 for practices). Respondents' SDOH scores by race/ethnicity were: White (3.65), Black (3.33), and Hispanic (3.22). Overall, attitude and practice scores decreased by 0.35 and 0.09, respectively, for every one-point increase in SDOH. Overall, a one-point increase in SDOH was associated with 76% and 85% increased odds of screening negative for anxiety and depression, respectively. To conclude, underlying social inequities are likely driving safer attitudes, practices, and worse anxiety and depression symptoms in Black and Hispanic Arkansans. In terms of policy implications, our study supports the urgency of addressing SDOHs for rural states similar to Arkansas.

Application Status Among Women Enrolled in a Healthy Start Program in Arkansas for the Special Nutrition Program for Women and Children.

This study aimed to examine the demographic characteristics of pregnant women in a Healthy Start program who are presumed eligible for the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), but who have not yet applied for WIC benefits. We used a cross sectional evaluation of data collected from pregnant women (n=203) participating in a Healthy Start program. Data came from surveys administered at enrollment in the Healthy Start program from July 15th, 2019 until January 14th, 2022. The primary outcome was WIC application status, which was determined by whether the woman had applied or was receiving benefits at the time of enrollment. Covariates included race/ethnicity, marital status, insurance, education, income, age, employment, and having previous children/pregnancies. Fisher exact tests and logistic regression were used to examine associations. Approximately 65% of women had not yet applied for WIC benefits. Marshallese women (80.9%) and other NHPI women (80.0%) had the highest need for assistance. In adjusted analyses, White women (p = 0.040) and Hispanic women (p = 0.005) had lower rates of needing assistance applying for WIC than Marshallese women. There were higher rates of needing assistance in applying for women with private insurance or with no insurance and for those with higher incomes. Nearly two out of every three pregnant women who were eligible for WIC had not yet applied for benefits. The findings highlight the need for outreach for all populations that may be eligible, particularly among racial/ethnic minorities and those with higher incomes.

Rates Of Preterm Birth And Low Birthweight: An Analysis Of Racial And Ethnic Populations.

Using National Center for Health Statistics data (2016-20), we evaluated variation in low birthweight and prematurity among racial and ethnic subcategories. Disparities as large as 2.3-fold among rates of low birthweight for "multiple race" subcategories underscore the need for granular data stratification and analysis by racial and ethnic subcategories to address the root causes of inequities in infant outcomes.

Identification of racial/ethnic disparities associated with severe maternal morbidity using the Arkansas All-Payer Claims Database (2013-2017).

OBJECTIVE: To evaluate the effect of maternal characteristics on the odds of severe maternal morbidity (SMM) through 42 days postpartum. STUDY DESIGN: We conducted a retrospective observational study of 77 172 births using birth certificate and insurance claims data from the Arkansas All Payers Claims Database, years 2013-2017, to identify racial disparities associated with SMM for births between April 1, 2014, and November 19, 2017. METHODS: Multiple logistic regression was used to examine the effect of sociodemographic factors and clinical comorbidities on the odds of SMM among non-Hispanic white ("white"), non-Hispanic Black ("Black"), and Hispanic women. RESULTS: The rate of SMM was 227.41 per 10 000 births, with Black women (330 per 10 000 births; 95% CI: 296.16-366.38), having a significantly higher rates than white women (197; 95% CI: 171.72-225.84) and Hispanic women (180; 95% CI: 155.86-207.54). After adjusting for maternal demographics, birth-related clinical variables, and comorbidities, SMM remained higher among Black women (aOR 1.37; 95% CI 1.11-1.70) relative to white women. CONCLUSIONS: Comorbidities, socioeconomic factors, and other factors did not fully explain the Black-white disparities in SMM. Persistent disparities in the rates of SMM throughout 42 days postpartum among Black women relative to white women points to the need for higher quality, more equitable care for women of color in the fist months postpartum.

Variation in Time Between Testing Positive for COVID-19 and Hospital Admission by Race/Ethnicity and Insurance Status.

Understanding the extent to which demographic and socioeconomic factors play a role in the disparities associated with duration between testing positive for COVID-19 and hospital admission will help in achieving equitable health outcomes. This project linked the statewide COVID-19 registry to administrative datasets to examine the variation in times between testing positive for COVID-19 and hospital admission by race/ethnicity and insurance. In 2020, there were 11,314 patients admitted for COVID-19 in Arkansas. Approximately 42.2% tested positive for COVID-19 on the same day as hospital admission. Black patients had 38% higher odds of hospitalization on the day of testing compared with White patients (p<.001). Medicaid and uninsured patients had 51% and 50% higher odds of admission on the day of testing compared with privately insured patients (both p<.001), respectively. This study highlights the implications of reduced access to testing with respect to equitable health outcomes.

Individual and Health Policy Factors Associated With Positive Heroin and Opioid Treatment Response: United States, 2018.

Objectives. To identify client- and state-level factors associated with positive treatment response among heroin and opioid treatment episodes in the United States. Methods. We used national data from 46 states using the Treatment Episode Dataset‒Discharges (2018) to identify heroin and opioid treatment episodes (n = 162 846). We defined positive treatment response as a decrease in use between admission and discharge. We used multivariable regression, stratified by race/ethnicity, to identify demographic, pain-related, and state-level factors associated with positive treatment response. Results. Lower community distress was the strongest predictor of better treatment outcomes across all racial/ethnic groups, particularly among White and American Indian/Alaska Native episodes. A primary opioid of heroin was associated with worse outcomes among White and Hispanic episodes. Legislation limiting opioid dispensing was associated with better outcomes among Hispanic episodes. Buprenorphine availability was strongly associated with better outcomes among Black episodes. Conclusions. State-level variables, particularly community distress, had greater associations with positive treatment outcomes than client-level variables. Public Health Implications. Changes in state-level policies and increased resources directed toward areas of high community distress have the potential to improve opioid use disorder treatment and reduce racial/ethnic disparities in treatment outcomes. (Am J Public Health. 2022;112(S1):S66-S76. https://doi.org/10.2105/AJPH.2021.306503).

Motherhood Together: Effects of an Adapted Prenatal Curriculum on Mother and Infant Outcomes.

Background: Research shows that pregnant women experiencing housing insecurity are more likely to face barriers to prenatal care that can lead to negative health outcomes for both mother and infant. Previous studies have also shown that prenatal education programs provide pregnant mothers with the knowledge and resources that increase the likelihood of positive health outcomes. An interprofessional healthcare team in Central Arkansas modified an existing prenatal education program to create Motherhood Together, a program specifically tailored for pregnant women facing house insecurity. Methods: The purpose of this initial evaluation of the Motherhood Together program was to identify the feasibility of the program and preliminary outcomes. This evaluation sought to better understand the demographic composition of the population participating in Motherhood Together (n = 19), as well as the effect of the program on infant outcomes, health literacy, and maternal self-care. The overall participant experience and feedback to enhance the program was also obtained. Results: The average age of participants was 24.6 years old and 77.8% reported high school as their highest level of educational attainment. The majority of participants identified as Black/African American (77.8%) and 22.2% identified as White. Participants scored the experience of Motherhood Together sessions positively with an overall score of 3.75/4.00. Participants reported an average gestational age at delivery being 36.9 weeks with 25% reporting preterm births following the program. Multivitamins were reported as being taken by 100% of participants following participation. Conclusion: Tailoring the pre-existing educational program to create the Motherhood Together program was clearly feasible and continues to serve as a critical resource for improving equity in infant and maternal outcomes in central Arkansas.

Mental Health Conditions Increase Severe Maternal Morbidity By 50 Percent And Cost $102 Million Yearly In The United States.

Perinatal mental health disorders are increasingly acknowledged as contributors to adverse maternal outcomes. We analyzed data from the Healthcare Cost and Utilization Project National Inpatient Sample (2016 and 2017) to estimate hospitalization cost, length-of-stay, and severe maternal morbidity associated with perinatal mental health disorders overall, as well as stratified by payer and by specific mental health category. We found that people with mental health disorders had $458 higher costs per delivery hospitalization and 50 percent higher rates of severe maternal morbidity compared with people without mental health disorders. We estimated increased annual delivery hospitalization costs of $102 million in the US among people with perinatal mental health conditions compared with those without. Furthermore, people diagnosed with trauma- or stress-related mental health disorders had even higher rates of hospitalization costs-$825 higher per delivery-and 87 percent higher rates of severe maternal morbidity compared with people without those diagnoses. These findings provide important information for perinatal mental health program feasibility and cost-effectiveness analyses and suggest the need for increased focus on trauma- and stress-related disorders.

Understanding racial disparities in severe maternal morbidity using Bayesian network analysis.

Previous studies have evaluated the marginal effect of various factors on the risk of severe maternal morbidity (SMM) using regression approaches. We add to this literature by utilizing a Bayesian network (BN) approach to understand the joint effects of clinical, demographic, and area-level factors. We conducted a retrospective observational study using linked birth certificate and insurance claims data from the Arkansas All-Payer Claims Database (APCD), for the years 2013 through 2017. We used various learning algorithms and measures of arc strength to choose the most robust network structure. We then performed various conditional probabilistic queries using Monte Carlo simulation to understand disparities in SMM. We found that anemia and hypertensive disorder of pregnancy may be important clinical comorbidities to target in order to reduce SMM overall as well as racial disparities in SMM.

Multilevel modeling of county-level excessive alcohol use, rurality, and COVID-19 case fatality rates in the US.

OBJECTIVE: Reports of disparities in COVID-19 mortality rates are emerging in the public health literature as the pandemic continues to unfold. Alcohol misuse varies across the US and is related to poorer health and comorbidities that likely affect the severity of COVID-19 infection. High levels of pre-pandemic alcohol misuse in some counties may have set the stage for worse COVID-19 outcomes. Furthermore, this relationship may depend on how rural a county is, as access to healthcare in rural communities has lagged behind more urban areas. The objective of this study was to test for associations between county-level COVID-19 mortality, pre-pandemic county-level excessive drinking, and county rurality. METHOD: We used national COVID-19 data from the New York Times to calculate county-level case fatality rates (n = 3,039 counties and county equivalents; October 1 -December 31, 2020) and other external county-level data sources for indicators of rurality and health. We used beta regression to model case fatality rates, adjusted for several county-level population characteristics. We included a multilevel component to our model and defined state as a random intercept. Our focal predictor was a single variable representing nine possible combinations of low/mid/high alcohol misuse and low/mid/high rurality. RESULTS: The median county-level COVID-19 case fatality rate was 1.57%. Compared to counties with low alcohol misuse and low rurality (referent), counties with high levels of alcohol and mid (ß = -0.17, p = 0.008) or high levels of rurality (ß = -0.24, p<0.001) demonstrated significantly lower case fatality rates. CONCLUSIONS: Our findings highlight the intersecting roles of county-level alcohol consumption, rurality, and COVID-19 mortality.

Race, Medicaid Coverage, and Equity in Maternal Morbidity.

BACKGROUND: Severe maternal morbidity (SMM) affects 50,000 deliveries in the United States annually, with around 1.5 times the rates among Medicaid-covered relative to privately covered deliveries. Furthermore, large racial inequities exist in SMM for non-Hispanic Black women and Hispanic women with rates being 2.1 and 1.4 times higher than White women, respectively. This study aimed to compare the differences in SMM among women of different races/ethnicities and delivery insurance types. Quantifying the rates of SMM based on the intersection of race/ethnicity and insurance status can help to elucidate how multiple forms of oppression and racism may contribute to the substantial inequities in SMM among Black women. METHODS: Using hospital discharge data from the Healthcare Cost and Utilization Project National Inpatient Sample (years 2016 and 2017), we conducted multivariate logistic models to evaluate equity in maternal outcomes among women with different primary payers, overall and stratified by race/ethnicity. RESULTS: We found a rate of SMM equal to 138.3 per 10,000 deliveries. Differences in the rate of SMM among non-Hispanic Black, non-Hispanic Asian, and Hispanic women relative to White women were lower among Medicaid-covered deliveries relative to deliveries of all payer types. For example, among all payers, Black women had 2.17 (221.3 vs. 102.1 per 10,000) times the rate of SMM compared with White women; however, among Medicaid-covered deliveries, Black women had 1.84 (227.3 vs. 123.2) times the rate. Despite increased risk associated with Medicaid coverage (adjusted odds ratio, 1.12; 95% confidence interval, 1.07-1.16), the risk was no longer significant in the stratified regression including Black women (adjusted odds ratio, 1.06; 95% confidence interval, 0.98-1.15). CONCLUSIONS: Our findings suggest that Black women with Medicaid do not have higher rates of SMM relative to Black women with private insurance. National and state policy efforts should continue to focus on addressing structural racism and other socioeconomic drivers of adverse maternal outcomes, including barriers to high-quality care among women with Medicaid coverage.

Associations Between Comorbidities and Severe Maternal Morbidity.

OBJECTIVE: To evaluate the associations between the number of chronic conditions and maternal race and ethnicity (race) with the risk of severe maternal morbidity. METHODS: Using the National Inpatient Sample, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality, years 2016-2017, we examined risk of severe maternal morbidity among 1,480,925 delivery hospitalizations among women of different races and with different numbers of comorbid conditions using multivariable logistic regression. RESULTS: The rate of severe maternal morbidity was 139.7 per 10,000 deliveries. Compared with women with no comorbidities (rate 48.5/10,000), there was increased risk of severe maternal morbidity among women with one comorbidity (rate 238.6; odds ratio [OR] 5.0, 95% CI 4.8-5.2), two comorbidities (rate 379.9; OR 8.1, 95% CI 7.8-8.5), or three or more comorbidities (rate 560; OR 12.1, 95% CI 11.5-12.7). In multivariable regressions, similar associations were noted for women with one (adjusted odds ratio [aOR] 4.4, 95% CI 4.2-4.6), two (aOR 6.6, 95% CI 6.3-6.9), or three or more comorbidities (aOR 9.1, 95% CI 8.7-9.6). Black women had higher rates of comorbid conditions than all other racial and ethnic groups, with 55% (95% CI 54-56%) of Black women having no comorbidities, compared with 67% (95% CI 67-68%) of White women, 68% (95% CI 67-69%) of Hispanic women, and 72% (95% CI 71-73%) of Asian women. CONCLUSION: We found a dose-response relationship between number of comorbidities and risk of severe maternal morbidity, with the highest rates of severe maternal morbidity among women with three or more comorbidities. Focusing on the prevention and treatment of chronic conditions among women of childbearing age may have the potential to improve maternal outcomes across races and ethnicities.

Geographic Hotspots for Low Birthweight: An Analysis of Counties With Persistently High Rates.

This study evaluated persistency in county-level rates of low birthweight outcomes to identify "hotspot counties" and their associated area-level characteristics. Administrative data from the National Center for Health Statistics Birth Data Files, years 2011 to 2016 were used to calculate annual county-level rates of low birthweight. Counties ranking in the worst quintile (Q5) for ≥3 years with a neighboring county in the worst quintile were identified as hotspot counties. Multivariate logistic regression was used to associate county-level characteristics with hotspot designation. Adverse birth outcomes were persistent in poor performing counties, with 52% of counties in Q5 for low birthweight in 2011 remaining in Q5 in 2016. The rate of low birthweight among low birthweight hotspot counties (n = 495) was 1.6 times the rate of low birthweight among non-hotspot counties (9.3% vs 5.8%). The rate of very low birthweight among very low birthweight hotspot counties (n = 387) was twice as high compared to non-hotspot counties (1.8% vs 0.9%). A one standard deviation (6.5%) increase in the percentage of adults with at least a high school degree decreased the probability of low birthweight hotspot designation by 1.7 percentage points (P = .006). A one standard deviation (20%) increase in the percentage of the population that was of minority race/ethnicity increased hotspot designation for low birthweight by 5.7 percentage points (P < .001). Given the association between low birthweight and chronic conditions, hotspot counties should be a focus for policy makers in order to improve health equity across the life course.