Conceptualizing the Socio-Built Environment: An Expanded Theoretical Framework to Promote a Better Understanding of Risk for Nonmedical Opioid Overdose Outcomes in Urban and Non-Urban Settings.

Nonmedical opioid (NMO) use has been linked to significant increases in rates of NMO morbidity and mortality in non-urban areas. While there has been a great deal of empirical evidence suggesting that physical features of built environments represent strong predictors of drug use and mental health outcomes in urban settings, there is a dearth of research assessing the physical, built environment features of non-urban settings in order to predict risk for NMO overdose outcomes. Likewise, there is strong extant literature suggesting that social characteristics of environments also predict NMO overdoses and other NMO use outcomes, but limited research that considers the combined effects of both physical and social characteristics of environments on NMO outcomes. As a result, important gaps in the scientific literature currently limit our understanding of how both physical and social features of environments shape risk for NMO overdose in rural and suburban settings and therefore limit our ability to intervene effectively. In order to foster a more holistic understanding of environmental features predicting the emerging epidemic of NMO overdose, this article presents a novel, expanded theoretical framework that conceptualizes "socio-built environments" as comprised of (a) environmental characteristics that are applicable to both non-urban and urban settings and (b) not only traditional features of environments as conceptualized by the extant built environment framework, but also social features of environments. This novel framework can help improve our ability to identify settings at highest risk for high rates of NMO overdose, in order to improve resource allocation, targeting, and implementation for interventions such as opioid treatment services, mental health services, and care and harm reduction services for people who use drugs.

Does health service funding go where the need is? A prototype spatial access analysis for new urban contracts data.

BACKGROUND: Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government. METHODS: In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study. RESULTS: We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago's high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout the city). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department. CONCLUSIONS: The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results.

What Happened to Disparities in CRC Screening Among FFS Medicare Enrollees Following Medicare Modernization?

The Medicare Modernization Act of 2003, implemented in 2006, increased managed care options for seniors. It introduced insurance plans for prescription drug coverage for all Medicare beneficiaries, whether they were enrolled in FFS or managed care (Medicare Advantage) plans. The availability of drug coverage beginning in 2006 served to free up budgets for FFS Medicare enrollees that could be used to make copayments for colorectal cancer (CRC) screening using endoscopy (colonoscopy or sigmoidoscopy). In 2007, Medicare eliminated the copayments required by seniors for CRC screening by endoscopy. Later in 2008, CRC screening by colonoscopy became part of the gold standard for CRC screening. This legitimized its use and offered even further encouragement to seniors, who may have been reluctant to undergo the procedure because of the non-pecuniary risks associated with it. In addition, 37 CRC screening interventions occurred during this timeframe to enhance compliance with screening standards. Using multilevel analysis of individuals' endoscopy utilization, derived from 100% FFS Medicare claims, along with county-level market and contextual factors, we compare the periods before and after the MMA (2001-2005 to 2006-2009) to determine whether disparities in the utilization of endoscopic CRC screening occurred or changed over the decade. We examined Blacks, Asians, and Hispanics relative to Whites, and Females relative to Males (with race or ethnicity combined). We examined each state separately for evidence of disparities within states, to avoid confounding by geographic disparities. We expected that the net effect of the policy changes and the targeted interventions over the decade would be to increase CRC screening by endoscopy, reducing disparities. We saw improvements over time (reduced disparities relative to Whites) for Blacks and Hispanics residing in several states, and improvements over time for Females relative to Males in many states. For the vast majority of states, however, disparities persisted with Whites and Males exhibiting greater rates of utilization than other groups. States that undertook the interventions were more likely to have had improvements in disparities or positive disparities for women and minorities. While some gains were made over this time period, the gains were unevenly distributed across the USA and more work needs to be done to reduce remaining disparities.

Chicago supermarket data and food access analytics in census tract shapefiles for 2007-2014.

Longitudinal analysis of supermarkets over time is essential to understanding the dynamics of foodscape environments for healthy living. Supermarkets for 2007, 2011, and 2014 for the City of Chicago were curated and further validated. The average distance to all supermarkets along the street network was constructed for each resident-populated census tract. These analytic results were generated with GIS software and stored as spatially enabled data files, facilitating further research and analysis. The data presented in this article are related to the research article entitled "Urban foodscape trends: Disparities in healthy food access in Chicago, 2007-2014" (Kolak et al., 2018).

Urban foodscape trends: Disparities in healthy food access in Chicago, 2007-2014.

We investigated changes in supermarket access in Chicago between 2007 and 2014, spanning The Great Recession, which we hypothesized worsened local food inequity. We mapped the average street network distance to the nearest supermarket across census tracts in 2007, 2011, and 2014, and identified spatial clusters of persistently low, high or changing access over time. Although the total number of supermarkets increased city-wide, extremely low food access areas in segregated, low income regions did not benefit. Among black and socioeconomically disadvantaged residents of Chicago, access to healthy food is persistently poor and worsened in some areas following recent economic shocks.

Spatial Variation in the Quality of American Community Survey Estimates.

Social science research, public and private sector decisions, and allocations of federal resources often rely on data from the American Community Survey (ACS). However, this critical data source has high uncertainty in some of its most frequently used estimates. Using 2006-2010 ACS median household income estimates at the census tract scale as a test case, we explore spatial and nonspatial patterns in ACS estimate quality. We find that spatial patterns of uncertainty in the northern United States differ from those in the southern United States, and they are also different in suburbs than in urban cores. In both cases, uncertainty is lower in the former than the latter. In addition, uncertainty is higher in areas with lower incomes. We use a series of multivariate spatial regression models to describe the patterns of association between uncertainty in estimates and economic, demographic, and geographic factors, controlling for the number of responses. We find that these demographic and geographic patterns in estimate quality persist even after we account for the number of responses. Our results indicate that data quality varies across places, making cross-sectional analysis both within and across regions less reliable. Finally, we present advice for data users and potential solutions to the challenges identified.

The case for spatial analysis in evaluation to reduce health inequities.

The article begins by giving an overview of spatial thinking concepts that are relevant to evaluation. The article relates the spatial perspective to both a realist evaluation and a randomized control trial perspective in evaluation to demonstrate the benefits of a spatialized program and evaluation perspective. The article mainly suggests that the adoption of a spatial perspective can add new insights to the theory and practice of evaluation in ways that helps evaluation move closer to reducing health inequities.

Managed care and the diffusion of endoscopy in fee-for-service Medicare.

OBJECTIVE: To determine whether Medicare managed care penetration impacted the diffusion of endoscopy services (sigmoidoscopy, colonoscopy) among the fee-for-service (FFS) Medicare population during 2001-2006. METHODS: We model utilization rates for colonoscopy or sigmoidoscopy as impacted by both market supply and demand factors. We use spatial regression to perform ecological analysis of county-area utilization rates over two time intervals (2001-2003, 2004-2006) following Medicare benefits expansion in 2001 to cover colonoscopy for persons of average risk. We examine each technology in separate cross-sectional regressions estimated over early and later periods to assess differential effects on diffusion over time. We discuss selection factors in managed care markets and how failure to control perfectly for market selection might impact our managed care spillover estimates. RESULTS: Areas with worse socioeconomic conditions have lower utilization rates, especially for colonoscopy. Holding constant statistically the socioeconomic factors, we find that managed care spillover effects onto FFS Medicare utilization rates are negative for colonoscopy and positive for sigmoidoscopy. The spatial lag estimates are conservative and interpreted as a lower bound on true effects. Our findings suggest that managed care presence fostered persistence of the older technology during a time when it was rapidly being replaced by the newer technology.

Does context matter for the relationship between deprivation and all-cause mortality? The West vs. the rest of Scotland.

BACKGROUND: A growing body of research emphasizes the importance of contextual factors on health outcomes. Using postcode sector data for Scotland (UK), this study tests the hypothesis of spatial heterogeneity in the relationship between area-level deprivation and mortality to determine if contextual differences in the West vs. the rest of Scotland influence this relationship. Research into health inequalities frequently fails to recognise spatial heterogeneity in the deprivation-health relationship, assuming that global relationships apply uniformly across geographical areas. In this study, exploratory spatial data analysis methods are used to assess local patterns in deprivation and mortality. Spatial regression models are then implemented to examine the relationship between deprivation and mortality more formally. RESULTS: The initial exploratory spatial data analysis reveals concentrations of high standardized mortality ratios (SMR) and deprivation (hotspots) in the West of Scotland and concentrations of low values (coldspots) for both variables in the rest of the country. The main spatial regression result is that deprivation is the only variable that is highly significantly correlated with all-cause mortality in all models. However, in contrast to the expected spatial heterogeneity in the deprivation-mortality relationship, this relation does not vary between regions in any of the models. This result is robust to a number of specifications, including weighting for population size, controlling for spatial autocorrelation and heteroskedasticity, assuming a non-linear relationship between mortality and socio-economic deprivation, separating the dependent variable into male and female SMRs, and distinguishing between West, North and Southeast regions. The rejection of the hypothesis of spatial heterogeneity in the relationship between socio-economic deprivation and mortality complements prior research on the stability of the deprivation-mortality relationship over time. CONCLUSIONS: The homogeneity we found in the deprivation-mortality relationship across the regions of Scotland and the absence of a contextualized effect of region highlights the importance of taking a broader strategic policy that can combat the toxic impacts of socio-economic deprivation on health. Focusing on a few specific places (e.g. 15% of the poorest areas) to concentrate resources might be a good start but the impact of socio-economic deprivation on mortality is not restricted to a few places. A comprehensive strategy that can be sustained over time might be needed to interrupt the linkages between poverty and mortality.

Spatial analysis of elderly access to primary care services.

BACKGROUND: Admissions for Ambulatory Care Sensitive Conditions (ACSCs) are considered preventable admissions, because they are unlikely to occur when good preventive health care is received. Thus, high rates of admissions for ACSCs among the elderly (persons aged 65 or above who qualify for Medicare health insurance) are signals of poor preventive care utilization. The relevant geographic market to use in studying these admission rates is the primary care physician market. Our conceptual model assumes that local market conditions serving as interventions along the pathways to preventive care services utilization can impact ACSC admission rates. RESULTS: We examine the relationships between market-level supply and demand factors on market-level rates of ACSC admissions among the elderly residing in the U.S. in the late 1990s. Using 6,475 natural markets in the mainland U.S. defined by The Health Resources and Services Administration's Primary Care Service Area Project, spatial regression is used to estimate the model, controlling for disease severity using detailed information from Medicare claims files. Our evidence suggests that elderly living in impoverished rural areas or in sprawling suburban places are about equally more likely to be admitted for ACSCs. Greater availability of physicians does not seem to matter, but greater prevalence of non-physician clinicians and international medical graduates, relative to U.S. medical graduates, does seem to reduce ACSC admissions, especially in poor rural areas. CONCLUSION: The relative importance of non-physician clinicians and international medical graduates in providing primary care to the elderly in geographic areas of greatest need can inform the ongoing debate regarding whether there is an impending shortage of physicians in the United States. These findings support other authors who claim that the existing supply of physicians is perhaps adequate, however the distribution of them across the landscape may not be optimal. The finding that elderly who reside in sprawling urban areas have access impediments about equal to residents of poor rural communities is new, and demonstrates the value of conceptualizing and modelling impedance based on place and local context.