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Background and Aims: Responses to the 2019 US outbreak of 'e‐cigarette or vaping product use‐associated lung injury' (EVALI) ranged from temporary restrictions on nicotine e‐cigarette sales to critiques of state cannabis policies. However, if either mass‐marketed nicotine e‐cigarettes or cannabis use per se drove this outbreak, as opposed to an additive in regionally available black‐market e‐liquids, states' rates of vaping and/or cannabis use should predict their EVALI prevalence. This study tests that relationship. Design Observational study of EVALI data from US states' health departments Setting: United States. Participants: All US states (n = 50). Measurements The outcome of interest was each state's total EVALI cases per 12–64‐year‐old resident—an age group covering most EVALI patients—as reported in the second week of January 2020. Predictors are 2017–18 rates of adult e‐cigarette use and past‐month cannabis use by state. Findings The average state EVALI prevalence was 1.4 cases per 100 000 12–64‐year‐olds. Maps suggest a high‐prevalence cluster comprising seven contiguous states in the northern Midwest. EVALI cases per capita were negatively associated with rates of vaping and past‐month cannabis use, with the preferred specification's coefficients at −0.239 [95% confidence interval (CI) = −0.441, −0.037; P = 0.02] and −0.086 (95% CI = −0.141, −0.031; P = 0.003), respectively. Robustness checks supported this finding. Conclusions: In the United States, states with higher rates of e‐cigarette and cannabis use prior to the 2019 'e‐cigarette or vaping product use‐associated lung injury' (EVALI) outbreak had lower EVALI prevalence. These results suggest that EVALI cases did not arise from e‐cigarette or cannabis use per se, but rather from locally distributed e‐liquids or additives most prevalent in the affected areas. [ABSTRACT FROM AUTHOR]

Services offered through Part C of the Individuals With Disabilities Education Improvement Act improve cognitive, behavioral, and physical skills for children less than 3 years old at risk for or with a disability. However, there are low enrollment rates into services. Various Lead Agencies oversee services through Part C, and states determine which agency is in charge of administering these services. The objective of this study was to describe odds of enrollment into early intervention services based on the department administering services (Lead Agency). Each state’s Lead Agency (Education, Health, or Other), state population size, narrowness of eligibility criteria, and state-level screening rates were fit into a negative binomial regression model to predict odds of enrollment into Part C services. Results show that state’s reporting from “Health” and “Other” as a Lead Agency had significantly higher odds for Part C services compared with the state Lead Agency of Education (Health adjusted odds ratio [AOR] = 1.56, 95% confidence interval [CI] = [1.557, 1.561]; Other AOR = 2.40, 95% CI = [2.401, 2.405]). Further research should describe unique components of a Lead Agency’s administrative practices that contribute to the variation in enrollment. This study was an important step toward the investigation of low enrollment rates into Part C services. [ABSTRACT FROM AUTHOR]

Medicaid is vastly more important than Medicare or private insurance in funding long-term care (LTC). However, states vary tremendously in their commitment to Medicaid LTC. This article advances knowledge of the origins, nature, and implications of this variation. After examining the degree of variation in state spending on Medicaid LTC, we show how federal policy has over the past fifty years steadily increased state discretion to shape these services. This decentralization largely reflects the potency of the intergovernmental lobby--governors and other state officials--in influencing federal policy. While fueling state variation, the intergovernmental lobby has also provided valuable political support that has helped Medicaid grow and resist retrenchment. After considering policy options that could mitigate Medicaid LTC inequities rooted in state differences, we assess how the catalytic forces that have fueled growth in Medicaid LTC may be insufficient to protect the program from future erosion. [ABSTRACT FROM AUTHOR]

Introduction Driving under the influence of drugs, including marijuana, has become more prevalent in recent years despite local, state, and federal efforts to prevent such increases. The Fatality Analysis Reporting System (FARS) is the primary source of drugged driving data for fatal crashes in the United States but lacks the completeness required to calculate unbiased estimates of drug use among drivers involved in fatal crashes. Methods This article uses the 2013 FARS dataset to present differences in state drug testing rates by driver type, driver fault type, and state-level factors; discusses limitations related to analysis and interpretation of drugged driving data; and offers suggestions for improvements that may enable appropriate use of FARS drug testing data in the future. Results Results showed that state drug testing rates were highest among drivers who died at the scene of the crash (median = 70.8%) and drivers who died and were at fault in the crash (median = 64.4%). The lowest testing rates were seen among surviving drivers who were not transported to a hospital (median = 14.0%) and surviving drivers who were not at fault in the crash (median = 10.0%). Drug testing rates differed by state blood alcohol content (BAC) testing rate across all driver types and driver fault types, and in general, states that tested a higher percentage of drivers for BAC had higher drug testing rates. Discussion Testing rates might be increased through standardization and mandatory testing policies. FARS data users should continue to be cautious about the limitations of using currently available data to quantify drugged driving. More efforts are needed to improve drug testing and reporting practices, and more research is warranted to establish drug concentration levels at which driving skills become impaired. [ABSTRACT FROM AUTHOR]

Objectives: To ascertain differences across states in children's oral health care access and oral health status and the factors that contribute to those differences. Study design: Observational study using cross-sectional surveys. Methods: Using the 2007 National Survey of Children's Health, we examined state variation in parents' report of children's oral health care access (absence of a preventive dental visit) and oral health status. We assessed the unadjusted prevalences of these outcomes, then adjusted with child-, family-, and neighbourhood-level variables using logistic regression; these results are presented directly and graphically. Using multilevel analysis, we then calculated the degree to which child-, family-, and community-level variables explained state variation. Finally, we quantified the influence of state-level variables on state variation. Results: Unadjusted rates of no preventive dental care ranged 9.0e26.8% (mean 17.5%), with little impact of adjusting (10.3-26.7%). Almost 9% of the population had fair/poor oral health; unadjusted range 4.1-14.5%. Adjusting analyses affected fair/poor oral health more than access (5.7-10.7%). Child, family and community factors explained ~1/4 of the state variation in no preventive visit and ~1/2 of fair/poor oral health. State-level factors further contributed to explaining up to a third of residual state variation. Conclusion: Geography matters: where a child lives has a large impact on his or her access to oral health care and oral health status, even after adjusting for child, family, community, and state variables. As state-level variation persists, other factors and richer data are needed to clarify the variation and drive changes for more egalitarian and overall improved oral health. [ABSTRACT FROM AUTHOR]

State Medicaid programs have expanded home and community-based services (HCBS). This article compares trends and variations in state policies for Medicaid HCBS programs in 2005 and 2010. State limitations on financial eligibility criteria and service benefits have remained stable. Although the use of consumer direction, independent providers, and family care providers has increased, some states do not have these options. The increased adoption of state cost control policies have led to large increases in persons on waiver wait lists. Access could be improved by standardizing and liberalizing state HCBS policies, but state fiscal concerns are barriers to rebalancing between HCBS and institutional services. [ABSTRACT FROM AUTHOR]

Background: Individuals involved in the criminal legal system face unique challenges to accessing substance use disorder (SUD) treatment, yet state-level variation in referrals for treatment remains largely unknown. To address disparities in the overdose crisis among individuals with criminal legal involvement, it is important to understand variation in SUD treatment across states., Methods: We conducted a retrospective comparison of substance use treatment referrals from the criminal legal system and other sources across participating states. Using data from the 2018-2019 Treatment Episode Dataset-Admissions, we characterized treatment referral rates from the criminal legal system, the substances most commonly leading to treatment, and rates of treatment with medication for opioid use disorder (MOUD) across states., Results: Across all states, criminal legal referral rates were higher than non-criminal legal rates. Criminal-legal referral rates, adjusted for state overdose deaths, were highest in the Northeast and Midwest. Methamphetamine use was the most common substance leading to treatment referral from the criminal legal system in 24 states while opioid use was the most common reason for non-criminal legal referrals in 34 states. In over half the states analyzed, fewer than 10% of opioid treatment referrals from the criminal legal system received MOUD. In almost all states, MOUD was more common in treatment referred from non-criminal legal settings., Conclusion: State-specific policies and practices shape drug policy and the SUD treatment landscape for people with criminal legal involvement. Standards and ongoing monitoring for substance use treatment referrals from the criminal-legal system should be considered by federal agencies charged with addressing the ongoing overdose crisis., Competing Interests: Conflict of Interest No conflict declared., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objective: Policies and regulations on opioid use have evolved from being primarily state-to federally based. We examined the trends and variation in chronic opioid use among states and nursing homes., Design: Retrospective cohort study., Setting and Participants: We used the nursing home Minimum Data Set and Medicare claims from 2014 to 2018 and included long-term care nursing home residents from each year who had at least 120 days of consecutive stay., Measurements: Chronic opioid use was defined as use for ≥90 days. Three-level hierarchical logistic regression models (resident, nursing home, state) were constructed to estimate intraclass correlation coefficient (ICC) at the state level and at the nursing home level. The ICC shows the proportion of variation in chronic opioid use that is attributable to states or nursing homes. All models were constructed separately for each calendar year and controlled for resident, nursing home, and state characteristics., Results: We included 3,245,714 nursing home stays from 2014 to 2018, representing 1,502,131 unique residents. The stays ranged from 676,413 in 2014 to 594,874 in 2018, with residents contributing a maximum of 1 stay per year. Chronic opioid use among nursing home residents declined from 14.1% in 2014 to 11.4% in 2018. The variation (ICC) in chronic opioid use among states declined from 2.5% in 2014 to 1.7% in 2018. In contrast, the variation (ICC) among nursing homes increased from 5.6% in 2014 to 6.5% in 2018., Conclusions and Implications: Variation in chronic opioid use declined by one-third at the state level but not at the nursing home level. National guidelines on opioid use and federal policies on opioid use may have contributed to reducing state-level variation in chronic opioid use., (Copyright © 2021. Published by Elsevier Inc.)

This study examined differences by race/ethnicity and state in poisoning deaths of undetermined intent (UnD) versus suicide classification and the potential impact of state variations on UnD rates for Blacks and Hispanics. We used data from the 2005-2015 U.S. National Violent Death Reporting System ( N  = 29,567 aged 15+) and weighted coarsened exact matching. The odds of UnD classification were 7-10 times higher in the 5 highest UnD states (Kentucky, Maryland, Michigan, Utah, and Rhode Island) than in other states. Blacks in these 5 states had twice the odds of Whites of being classified as UnDs than suicides, but had lower odds in other states. Other significant UnD classification factors were opioid and cocaine positive toxicologies.