Evaluating the association between the built environment and primary care access for new Medicaid enrollees in an urban environment using Walk and Transit Scores

An evaluation of the impact of social and structural determinants of health on forgone care during the COVID-19 pandemic in Baltimore, Maryland

Evidence suggests that reductions in healthcare utilization, including forgone care, during the COVID-19 pandemic may be contributing towards excess morbidity and mortality. The objective of this study was to describe individual and community-level correlates of forgone care during the COVID-19 pandemic. We conducted a cross-sectional, secondary data analysis of participants (n = 2,003) who reported needing healthcare in two population-representative surveys conducted in Baltimore, MD in 2021 and 2021-2022. Abstracted data included the experience of forgone care, socio-demographic data, comorbidities, financial strain, and community of residence. Participant's community of residence were linked with data acquired from the Baltimore Neighborhood Indicators Alliance relevant to healthcare access and utilization, including walkability and internet access, among others. The data were analyzed using weighted random effects logistic regression. Individual-level factors found to be associated with increased odds for forgone care included individuals age 35-49 (compared to 18-34), female sex, experiencing housing insecurity during the pandemic, and the presence of functional limitations and mental illness. Black/African American individuals were found to have reduced odds of forgone care, compared to any other race. No community-level factors were significant in the multilevel analyses. Moving forward, it will be critical that health systems identify ways to address any barriers to care that populations might be experiencing, such as the use of mobile health services or telemedicine platforms. Additionally, public health emergency preparedness planning efforts must account for the unique needs of communities during future crises, to ensure that their health needs can continue to be met. Finally, additional research is needed to better understand how healthcare access and utilization practices have changed during versus before the pandemic.

Examining multilevel neighborhood socioeconomic characteristics associated with colorectal cancer screening in Vietnamese Americans residing in Philadelphia County

Colorectal cancer (CRC) is one of the most predominant cancers in the USA and ranks third among all cancers in incidence and mortality. Vietnamese Americans exhibit persistently lower screening rates compared to the general U.S. population, due to cultural, economic, and environmental barriers. The impact of environmental factors in particular is not well known, and lack of geographical access may be a significant barrier to accessing screening. This study aims to elucidate build and neighborhood environmental factors affecting CRC screening rates among Vietnamese Americans. A total of 517 Vietnamese Americans 50 years and older residing in Philadelphia County were included in the study. Surveys were collected to determine CRC screening behavior and sociodemographic characteristics. Individual neighborhood characteristics, which included the Walk Score, was obtained based on the participant's address. Neighborhood characteristics were calculated using census-tract level data for the social deprivation index, ethnic composition, and presence of hospitals or federally qualified health centers (FQHC). The generalized linear mixed model revealed that residing in an ethnically dense neighborhood was negatively associated with CRC screening (β = -0.67, SE = 0.29, p = .01), while social deprivation (β = 0.30, SE = 0.27, p = .27) and presence of FQHCs or hospitals (β = 0.16, SE = 0.30, p = .58) were not. Individual neighborhood characteristics including the Walk Score (β = 0.21, SE = 0.26, p = .43) was not associated with CRC screening behavior. Neighborhood characteristics, specifically ethnic density is associated with lower uptake of screening in this population. Future interventions should aim to target specific Vietnamese American and other Asian ethnic neighborhoods that may experience disparities in screening.

Google Street View Images as Predictors of Patient Health Outcomes, 2017–2019

Collecting neighborhood data can both be time- and resource-intensive, especially across broad geographies. In this study, we leveraged 1.4 million publicly available Google Street View (GSV) images from Utah to construct indicators of the neighborhood built environment and evaluate their associations with 2017–2019 health outcomes of approximately one-third of the population living in Utah. The use of electronic medical records allows for the assessment of associations between neighborhood characteristics and individual-level health outcomes while controlling for predisposing factors, which distinguishes this study from previous GSV studies that were ecological in nature. Among 938,085 adult patients, we found that individuals living in communities in the highest tertiles of green streets and non-single-family homes have 10–27% lower diabetes, uncontrolled diabetes, hypertension, and obesity, but higher substance use disorders—controlling for age, White race, Hispanic ethnicity, religion, marital status, health insurance, and area deprivation index. Conversely, the presence of visible utility wires overhead was associated with 5–10% more diabetes, uncontrolled diabetes, hypertension, obesity, and substance use disorders. Our study found that non-single-family and green streets were related to a lower prevalence of chronic conditions, while visible utility wires and single-lane roads were connected with a higher burden of chronic conditions. These contextual characteristics can better help healthcare organizations understand the drivers of their patients’ health by further considering patients’ residential environments, which present both risks and resources.

Choosing a Provider: What Factors Matter Most to Consumers and Patients?

Enhancing consumer and patient choice has been proposed as a means to improve care quality and reduce health-related costs. Choosing a medical provider is one of the most critical and often complex decisions patients make about their health care. We investigated the perceived importance of factors patients may consider when selecting a practitioner and if rated importance of the factors varies with their characteristics and prior experiences with different types of clinicians (physicians, physician assistants, and nurse practitioners). Participants most often identified medical license, certification, and whether the provider accepts the patients’ health insurance as important, while provider type, others’ recommendations, and online reviews were among the least important. We found wide-ranging differences based on patient characteristics. Prior experience with providers was also a strong determinant of patterns of factors patients considered valuable. Policy-makers, health systems, insurers, and providers need to take into account that patients rely on a range of factors that vary based on their distinct needs, backgrounds, and previous experiences—requiring tailored information to make more informed decisions.

Identifying urban built environment factors in pregnancy care and maternal mental health outcomes

Backgrounds

Risk factors related to the built environment have been associated with women’s mental health and preventive care. This study sought to identify built environment factors that are associated with variations in prenatal care and subsequent pregnancy-related outcomes in an urban setting.

Methods

In a retrospective observational study, we characterized the types and frequency of prenatal care events that are associated with the various built environment factors of the patients’ residing neighborhoods. In comparison to women living in higher-quality built environments, we hypothesize that women who reside in lower-quality built environments experience different patterns of clinical events that may increase the risk for adverse outcomes. Using machine learning, we performed pattern detection to characterize the variability in prenatal care concerning encounter types, clinical problems, and medication prescriptions. Structural equation modeling was used to test the associations among built environment, prenatal care variation, and pregnancy outcome. The main outcome is postpartum depression (PPD) diagnosis within 1 year following childbirth. The exposures were the quality of the built environment in the patients’ residing neighborhoods. Electronic health records (EHR) data of pregnant women (n = 8,949) who had live delivery at an urban academic medical center from 2015 to 2017 were included in the study.

Results

We discovered prenatal care patterns that were summarized into three common types. Women who experienced the prenatal care pattern with the highest rates of PPD were more likely to reside in neighborhoods with homogeneous land use, lower walkability, lower air pollutant concentration, and lower retail floor ratios after adjusting for age, neighborhood average education level, marital status, and income inequality.

Conclusions

In an urban setting, multi-purpose and walkable communities were found to be associated with a lower risk of PPD. Findings may inform urban design policies and provide awareness for care providers on the association of patients’ residing neighborhoods and healthy pregnancy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-04056-1.

Leveraging 31 Million Google Street View Images to Characterize Built Environments and Examine County Health Outcomes

OBJECTIVES

Built environments can affect health, but data in many geographic areas are limited. We used a big data source to create national indicators of neighborhood quality and assess their associations with health.

METHODS

We leveraged computer vision and Google Street View images accessed from December 15, 2017, through July 17, 2018, to detect features of the built environment (presence of a crosswalk, non-single-family home, single-lane roads, and visible utility wires) for 2916 US counties. We used multivariate linear regression models to determine associations between features of the built environment and county-level health outcomes (prevalence of adult obesity, prevalence of diabetes, physical inactivity, frequent physical and mental distress, poor or fair self-rated health, and premature death [in years of potential life lost]).

RESULTS

Compared with counties with the least number of crosswalks, counties with the most crosswalks were associated with decreases of 1.3%, 2.7%, and 1.3% of adult obesity, physical inactivity, and fair or poor self-rated health, respectively, and 477 fewer years of potential life lost before age 75 (per 100 000 population). The presence of non-single-family homes was associated with lower levels of all health outcomes except for premature death. The presence of single-lane roads was associated with an increase in physical inactivity, frequent physical distress, and fair or poor self-rated health. Visible utility wires were associated with increases in adult obesity, diabetes, physical and mental distress, and fair or poor self-rated health.

CONCLUSIONS

The use of computer vision and big data image sources makes possible national studies of the built environment's effects on health, producing data and results that may inform national and local decision-making.

Geographic access to buprenorphine prescribers for patients who use public transit

OBJECTIVE

Urban Medicaid enrollees with opioid use disorder often rely on public transit to reach buprenorphine prescribers. Research has not shown whether public transit provides this population with adequate geographic access to buprenorphine prescribers. We examined travel times to buprenorphine prescribers by car and public transit in urban areas, and determined whether car-based Medicaid regulatory standards produce their intended geographic coverage.

METHODS

We obtained data for this study from the Substance Abuse and Mental Health Services Administration's Buprenorphine Practitioner Locator, Microsoft Bing Maps, and the American Community Survey. We examined four urban counties at the centers of the metropolitan statistical areas with the highest 2017 accidental drug poisoning death rates: Kanawha, WV; Montgomery, OH; Philadelphia, PA; and St. Louis City, MO. These counties comprised 696 census tracts representing 1,038,564 households. We calculated travel times from each census tract center to the nearest buprenorphine prescribers by car and public transit, and compared that to 30-min regulatory standards and by whether census tracts had below median levels of car access. We calculated Global Moran's I statistics to determine whether spatial clustering was present among census tracts with limited access to buprenorphine prescribers.

RESULTS

Households in all but two census tracts could access a buprenorphine prescriber within 30 min by car. However, households in 12.1% (84) of census tracts could not do so by public transit. The correlation between car- and public transit-based travel times to the nearest buprenorphine prescriber was 0.11 (95% CI = 0.07-0.22). More than 15% (47,918) of households in the two less densely populated counties could not travel to the nearest prescriber in 30 min and resided in census tracts where access to cars was relatively low. There was no evidence of spatial clustering among census tracts with public transit travel times exceeding 30 min, or among census tracts with public transit travel times exceeding 30 min and below median values of access to cars.

CONCLUSIONS

Geographic access to buprenorphine prescribers is overestimated by regulatory standards that apply car-based travel time estimates, which are a weak proxy for public transit-based travel times. Since geographic areas with limited access to buprenorphine prescribers do not tend to cluster near one another, individually targeted interventions may be necessary to improve buprenorphine access and utilization.

Intersectionality, special populations, needs and suggestions: the Flint Women's study

BACKGROUND

Equitable access to services that promote health and wellbeing is an important component of social justice. A community-engaged participatory qualitative study was conducted in Flint, Michigan, USA, to understand the needs of special populations (young women, perinatal women and new mothers, older women, women with disabilities, and LGBTQIA women) and elicit their ideas about solutions.

METHODS

In-depth interviews (n = 100) were conducted. Participants were either women living in the Flint area, human service providers in the area, or both. A team of community and academic coders analyzed the data using an a priori framework.

RESULTS

Participants identified needs of different groups of women and suggested ways to address them. Access to healthy food, reducing healthcare costs, and improving transportation, job opportunities and affordable quality housing were crosscutting themes across all groups of women. Mentoring support was said to protect vulnerable young women from the risk of human trafficking. Older women were said to gain a sense of purpose, build their social support and reduce their loneliness by engaging in mentoring younger women. Women with disabilities were reported to benefit from infrastructure accessibility and authentic inclusion in all areas of life. Providing help that considers their dignity, pride and self-worth were suggested. LGBTQIA women were reported to have housing needs due to discrimination; mostly turned down as renters and can be rejected from faith-based homeless shelters. LGBTQIA women would also benefit from increased sensitivity among healthcare providers. For all groups of women, streamlining access to social services and other resources, building social support networks and increasing awareness about existing resources were recommended.

CONCLUSION

Efforts directed towards improving women's health and wellbeing should include perspectives and suggestions of diverse groups of women from the community. Acting on suggestions that emanate from the community's lived experiences may reduce inequalities in health and wellbeing.