The Next Generation Accountable Care Organization (NGACO) model (active during 2016-21) tested the effects of high financial risk, payment mechanisms, and flexible care delivery on health care spending and value for fee-for-service Medicare beneficiaries. We used quasi-experimental methods to examine the model's effects on Medicare Parts A and B spending. Sixty-two ACOs with more than 4.2 million beneficiaries and more than 91,000 practitioners participated in the model. The model was associated with a $270 per beneficiary per year, or approximately $1.7 billion, decline in Medicare spending. After shared savings payments to ACOs were included, the model increased net Medicare spending by $56 per beneficiary per year, or $96.7 million. Annual declines in spending for the model grew over time, reflecting exit by poorer-performing NGACOs, improvement among the remaining NGACOs, and the COVID-19 pandemic. Larger declines in spending occurred among physician practice ACOs and ACOs that elected population-based payments and risk caps greater than 5 percent.

Purpose: Investigations into rural tobacco-related disparities in the U.S. are hampered by the lack of a standardized approach for identifying the rurality-and, consequently, the urbanicity-of an area. Therefore, the purpose of this study was to compare the most common urban/rural definitions (Census Bureau, OMB, RUCA, and Isolation) and determine which is preferable for explaining the geographic distribution of several tobacco-related outcomes (behavior, receiving a doctor's advice to quit, and support for secondhand smoke policies). Methods: Data came from The Current Population Survey Tobacco Use Supplement. For each tobacco-related outcome, one logistic regression was conducted for each urban/rural measure. Models were then ranked according to their ability to explain the data using Akaike information criterion (AIC). Results: Each definition provided very different estimates for the prevalence of the U.S. population that is considered "rural" (e.g., 5.9% for the OMB, 17.0% for the Census Bureau). The OMB definition was most sensitive at detecting urban/rural differences, followed by the Isolation scale. Both these measures use strict, less-inclusive criteria for what constitutes "rural." Conclusions: Overall, results demonstrate the heterogeneity across urban/rural measures. Although findings do not provide a definitive answer for which urban/rural definition is the best for examining rural tobacco use, they do suggest that the OMB and Isolation measures may be most sensitive to detecting many types of urban/rural tobacco-related disparities. Caveats and implications of these findings for rural tobacco use disparities research are discussed. Efforts such as these to better understand which rural measure is appropriate for which situation can improve the precision of rural substance use research.

Significant disparities exist between rural-urban U.S. populations. Besides higher smoking rates, rural Americans are less likely to be protected from SHS. Few studies focus across all regions, obscuring regional-level differences. This study compares support for SHS restrictions across all HHS regions. Data: 2014/15 TUS-CPS; respondents (n = 228,967): 47,805 were rural residents and 181,162 urban. We examined bi-variates across regions and urban-rural adjusted odds ratios within each. Smoking inside the home was assessed along with attitudes toward smoking in bars, casinos, playgrounds, cars, and cars with kids. Urban respondents were significantly more supportive of all SHS policies: (e.g. smoking in bars [57.9% vs. 51.4%]; support for kids in cars [94.8% vs. 92.5%]. Greatest difference between urban-rural residents was in Mid-Atlantic (bar restrictions) and Southeast (home bans): almost 10% less supportive. Logistic regression confirmed rural residents least likely, overall, to support SHS in homes (OR = 0.78, 95% CI 0.74, 0.81); in cars (OR = 0.87, 95% CI 0.79, 0.95), on playgrounds (OR = 0.88, 95% CI. 83, 0.94) and in bars OR = 0.88, 95% CI 0.85, 0.92), when controlling for demog raphics and smoking status. South Central rural residents were significantly less likely to support SHS policies-home bans, smoking in cars with kids, on playgrounds, in bars and casinos; while Heartland rural residents were significantly more supportive of policies restricting smoking in cars, cars with kids and on playgrounds. Southeast and South Central had lowest policy score with no comprehensive state-level SHS policies. Understanding differences is important to target interventions to reduce exposure to SHS and related health disparities.

PURPOSE:To determine whether there are rural/urban differences in e-cigarette use and reasons for use that vary across the 10 Health & Human Services (HHS) regions.METHODS:Age-adjusted bivariate and multivariable analyses were conducted for n = 225,413 respondents to the 2014-2015 Tobacco Use Supplement-Current Population Survey to estimate the prevalence of e-cigarette use. Reasons for e-cigarette use were collected from n = 16,023 self-respondents who reported ever using e-cigarettes.FINDINGS:While nationally rural residents appeared more likely to use e-cigarettes, adjusted results indicated that current e-cigarette use was significantly less likely across the northern and western regions (New England, East North Central, Heartland, North Central Mountain, Northwest, and Southwest Pacific regions). Reasons for e-cigarette use differed by urban/rural status and region; for example, the rationale to use e-cigarettes as a smoking cessation aid was significantly more common among rural compared to urban adults in the New England and New York/New Jersey regions, but less common in the Southeast.CONCLUSIONS:For several regions, there were no significant rural/urban differences in e-cigarette use and reasons for use. Yet those regions that present differences face the need to develop public health approaches to minimize urban/rural disparities in health education, services, and outcomes related to tobacco use, particularly where access to health care is limited. Public health campaigns and guidance for clinical care within HHS regions should be tailored to reflect regional differences in beliefs about e-cigarettes.

OBJECTIVES:In 2013, the community of Redlands, California, created an initiative using evidence-based strategies to deter driving under the influence (DUI), underage drinking and driving, public intoxication, and alcohol-related calls for service. The initiative, called "Responsible Redlands," included adopting a social host and a deemed approved local ordinance, using minor-decoy and shoulder-tap operations, increasing sobriety checkpoints and saturation patrols, conducting responsible beverage service (RBS) training, using identification (ID) scanners to spot false IDs, and a publicity campaign to urge neighbors to report loud drinking parties. The objectives of this study were to determine whether the initiatives were carried out as planned and to assess any impacts that may have occurred due to the combination of initiatives. METHODS:Data from the Redlands Police Department were used to assess the process evaluation. The Statistical Analysis System (SAS) was used to create contingency tables to compare before (2007-2012) and after (2013-2014) the intervention start date and to conduct time-series analyses and calculate chi-squared test statistics on five outcome measures: DUI arrests, underage drinking violations, public intoxication violations, alcohol calls for service, and place of last drink (POLD) data from alcohol violators. Data sources were from the Redlands Police Department: DUI arrests for drivers under age 21 years and drivers age 21 or older; alcohol-related calls for service; public intoxication citations; and place of last drink surveys. Comparable data from control communities in California were not available at the time of the analyses. RESULTS:Responsible Redlands Initiatives appeared to be carried out as planned. There was a statistically significant decrease in DUI arrests for drivers 21 and older from preintervention to postintervention (p < .001), in alcohol-related calls for service (p < .001), in loud music calls for service (p = .06), and in public intoxication citations (p < .001). There were decreases in underage drinking violations and in DUIs for under age 21 drivers, but the numbers were too small for chi-squared statistical tests. CONCLUSIONS:"Responsible Redlands" interventions were associated with several significant decreases in outcome measures from preintervention to postintervention. Communities that consider these initiatives in combination (social host and deemed approved ordinances; minor-decoy and shoulder-tap operations; DUI checkpoints and saturation patrols; RBS training; use of ID scanners and a public information campaign to report loud drinking parties) can expect to experience potential decreases in alcohol-related harm.