Impact of Neighborhood Social and Environmental Resources on Medicaid Spending.

INTRODUCTION: In an era of COVID-19, Black Lives Matter, and unsustainable healthcare spending, efforts to address the root causes of health are urgently needed. Research linking medical spending to variation in neighborhood resources is critical to building the case for increased funding for social conditions. However, few studies link neighborhood factors to medical spending. This study assesses the relationship between neighborhood social and environmental resources and medical spending across the spending distribution. METHODS: Individual-level health outcomes were drawn from a sample of Medicaid enrollees living in Baltimore, Maryland during 2016. A multidimensional index of neighborhood social and environmental resources was created and stratified by tertile (high, medium, and low). Differences were examined in individual-level medical spending associated with living in high-, medium-, or low-resource neighborhoods in unadjusted and adjusted 2-part models and quantile regression models. Analyses were conducted in 2019. RESULTS: Enrollees who live in neighborhoods with low social and environmental resources incur significantly higher spending at the mean and across the distribution of medical spending even after controlling for age, race, sex, and morbidity than those who live in neighborhoods with high social and environmental resources. On average, this spending difference between individuals in low- and those in high-resource neighborhoods is estimated to be $523.60 per person per year. CONCLUSIONS: Living in neighborhoods with low (versus those with high) resources is associated with higher individual-level medical spending across the distribution of medical spending. Findings suggest potential benefits from efforts to address the social and environmental context of neighborhoods in addition to the traditional orientation to addressing individual behavior and risk.

Association between neighborhood socioeconomic status, tobacco store density and smoking status in pregnant women in an urban area.

Smoking during pregnancy can lead to serious health consequences. Given such health risks, an understanding of factors that influence maternal smoking behaviors during pregnancy is critical. The objective of this study is to assess the relationship between tobacco store density, neighborhood socioeconomic status, and neighborhood rates of maternal smoking during pregnancy. Fifty-five community areas in Baltimore City were summarized using data from the Neighborhood Health Profiles. Associations between tobacco store density and smoking while pregnant in a community were determined using Moran's I and spatial regression analyses to account for autocorrelation. The fully adjusted model took into account the following community-level socioeconomic variables as covariates: neighborhood median income, percentage of those living in poverty, percentage of uninsured, and percentage of persons with at least a college degree. In regards to the findings, the percentage of women by community area who identified as actively smoking while pregnant was 10.4% ± 5.8%. The tobacco store density was 21.0 ± 12.7 per 10,000 persons (range 0.0-49.1 tobacco store density per 10,000 persons). In the adjusted model, an increase in density of 1 tobacco store per 10,000 persons was associated with a 10% increase in women who reported smoking during pregnancy (ß = 0.10, p = 0.04). In conclusion, tobacco store density and neighborhood socioeconomic factors were associated with prevalence of maternal smoking while pregnant. These findings support the need to further assess and develop interventions to reduce the impact of tobacco store density on smoking behaviors and health risks in communities.

The Association Between Neighborhood Socioeconomic Disadvantage and Readmissions for Patients Hospitalized With Sepsis.

OBJECTIVES: To evaluate associations between a readily availvable composite measurement of neighborhood socioeconomic disadvantage (the area deprivation index) and 30-day readmissions for patients who were previously hospitalized with sepsis. DESIGN: A retrospective study. SETTING: An urban, academic medical institution. PATIENTS: The authors conducted a manual audit for adult patients (18 yr old or older) discharged with an International Classification of Diseases, 10th edition code of sepsis during the 2017 fiscal year to confirm that they met SEP-3 criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The area deprivation index is a publicly available composite score constructed from socioeconomic components (e.g., income, poverty, education, housing characteristics) based on census block level, where higher scores are associated with more disadvantaged areas (range, 1-100). Using discharge data from the hospital population health database, residential addresses were geocoded and linked to their respective area deprivation index. Patient characteristics, contextual-level variables, and readmissions were compared by t tests for continuous variables and Fisher exact test for categorical variables. The associations between readmissions and area deprivation index were explored using logistic regression models. A total of 647 patients had an International Classification of Diseases, 10th edition diagnosis code of sepsis. Of these 647, 116 (17.9%) either died in hospital or were discharged to hospice and were excluded from our analysis. Of the remaining 531 patients, the mean age was 61.0 years (± 17.6 yr), 281 were females (52.9%), and 164 (30.9%) were active smokers. The mean length of stay was 6.9 days (± 5.6 d) with the mean Sequential Organ Failure Assessment score 4.9 (± 2.5). The mean area deprivation index was 54.2 (± 23.8). The mean area deprivation index of patients who were readmitted was 62.5 (± 27.4), which was significantly larger than the area deprivation index of patients not readmitted (51.8 [± 22.2]) (p < 0.001). In adjusted logistic regression models, a greater area deprivation index was significantly associated with readmissions (ß, 0.03; p < 0.001). CONCLUSIONS: Patients who reside in more disadvantaged neighborhoods have a significantly higher risk for 30-day readmission following a hospitalization for sepsis. The insight provided by neighborhood disadvantage scores, such as the area deprivation index, may help to better understand how contextual-level socioeconomic status affects the burden of sepsis-related morbidity.

Going Beyond Clinical Care to Reduce Health Care Spending: Findings From the J-CHiP Community-based Population Health Management Program Evaluation.

BACKGROUND: Addressing both clinical and nonclinical determinants of health is essential for improving population health outcomes. In 2012, the Johns Hopkins Community Health Partnership (J-CHiP) implemented innovative population health management programs across acute and community environments. The community-based program involved multidisciplinary teams [ie, physicians, care managers (CM), health behavior specialists (HBS), community health workers, neighborhood navigators] and collaboration with community-based organizations to address social determinants. OBJECTIVES: To report the impact of a community-based program on cost and utilization from 2011 to 2016. DESIGN: Difference-in-difference estimates were calculated for an inclusive cohort of J-CHiP participants and matched nonparticipants. The analysis was replicated for participants with a CM and/or HBS to estimate the differential impact with more intensive program services. SUBJECTS: A total of 3268 high-risk Medicaid and Medicare beneficiaries (1634 total J-CHiP participants, 1365 with CM and 678 with HBS). OUTCOME MEASURES: Paid costs and counts of emergency department visits, admissions, and readmissions per member per year. RESULTS: For Medicaid, costs were almost $1200 per member per year lower for participants as a whole, $2000 lower for those with an HBS, and $3000 lower for those with a CM; hospital admission and readmission rates were 9%-26% lower for those with a CM and/or HBS. For Medicare, costs were lower (-$476), but utilization was similar or higher than nonparticipants. None of the observed Medicaid or Medicare differences were statistically significant. CONCLUSIONS: Although not statistically significant, the results indicate a promising innovation for Medicaid beneficiaries. For Medicare, the impact was negligible, indicating the need for further program modification.

Development and Usefulness of a District Health Systems Tool for Performance Improvement in Essential Public Health Functions in Botswana and Mozambique.

INTRODUCTION: This study describes the development of a self-audit tool for public health and the associated methodology for implementing a district health system self-audit tool that can provide quantitative data on how district governments perceive their performance of the essential public health functions. METHODS: Development began with a consensus-building process to engage Ministry of Health and provincial health officers in Mozambique and Botswana. We then worked with lists of relevant public health functions as determined by these stakeholders to adapt a self-audit tool describing essential public health functions to each country's health system. We then piloted the tool across districts in both countries and conducted interviews with district health personnel to determine health workers' perception of the usefulness of the approach. RESULTS: Country stakeholders were able to develop consensus around 11 essential public health functions that were relevant in each country. Pilots of the self-audit tool enabled the tool to be effectively shortened. Pilots also disclosed a tendency to upcode during self-audits that was checked by group deliberation. Convening sessions at the district enabled better attendance and representative deliberation. Instant feedback from the audit was a feature that 100% of pilot respondents found most useful. CONCLUSION: The development of metrics that provide feedback on public health performance can be used as an aid in the self-assessment of health system performance at the district level. Measurements of practice can open the door to future applications for practice improvement and research into the determinants and consequences of better public health practice. The current tool can be assessed for its usefulness to district health managers in improving their public health practice. The tool can also be used by the Ministry of Health or external donors in the African region for monitoring the district-level performance of the essential public health functions.

Bridging the Silos of Service Delivery for High-Need, High-Cost Individuals.

Health care reform efforts that emphasize value have increased awareness of the importance of nonmedical factors in achieving better care, better health, and lower costs in the care of high-need, high-cost individuals. Programs that care for socioeconomically disadvantaged, high-need, high-cost individuals have achieved promising results in part by bridging traditional service delivery silos. This study examined 5 innovative community-oriented programs that are successfully coordinating medical and nonmedical services to identify factors that stimulate and sustain community-level collaboration and coordinated care across silos of health care, public health, and social services delivery. The authors constructed a conceptual framework depicting community health systems that highlights 4 foundational factors that facilitate community-oriented collaboration: flexible financing, shared leadership, shared data, and a strong shared vision of commitment toward delivery of person-centered care.

Development and applications of an outcomes assessment framework for care management programs in learning health systems.

PURPOSE: To develop and apply an outcomes assessment framework (OAF) for care management programs in health care delivery settings. BACKGROUND: Care management (CM) refers to a regimen of organized activities that are designed to promote health in a population with particular chronic conditions or risk profiles, with focus on the triple aim for populations: improving the quality of care, advancing health outcomes, and lowering health care costs. CM has become an integral part of a care continuum for population-based health care management. To sustain a CM program, it is essential to assure and improve CM effectiveness through rigorous outcomes assessment. To this end, we constructed the OAF as the foundation of a systematic approach to CM outcomes assessment. INNOVATIONS: To construct the OAF, we first systematically analyzed the operation process of a CM program; then, based on the operation analysis, we identified causal relationships between interventions and outcomes at various implementation stages of the program. This set of causal relationships established a roadmap for the rest of the outcomes assessment. Built upon knowledge from multiple disciplines, we (1) formalized a systematic approach to CM outcomes assessment, and (2) integrated proven analytics methodologies and industrial best practices into operation-oriented CM outcomes assessment. CONCLUSION: This systematic approach to OAF for assessing the outcomes of CM programs offers an opportunity to advance evidence-based care management. In addition, formalized CM outcomes assessment methodologies will enable us to compare CM effectiveness across health delivery settings.

Rates of intentionally caused and road crash deaths of US citizens abroad.

CONTEXT: Currently, little is known about rates of death by cause and country among US travellers. Understanding the risk by cause and country is imperative to risk communication and the development of risk reduction strategies. METHODS: Publicly available data on non-natural deaths of US citizens abroad were gathered from January 2003 to December 2009 from the US Department of State's Department Bureau of Consular Affairs. Traveller information was gathered from the US Department of Commerce Office of Travel and Tourism for the same time period. Rates of death were calculated by dividing the number of non-natural deaths of US citizens abroad by the number of US outbound visits for each country. RESULTS: A total of 5417 non-natural death events were retrieved between 2003 and 2009 from the US State Department. Intentionally caused death rates ranged from 21.44 per 1 000 000 visits in the Philippines to 0 per 1 000 000 visits in several countries; the majority of countries had fewer than five intentionally caused deaths per 1 000 000 visits. Rates of road traffic crashes were higher than rates of intentionally caused deaths in almost every instance. Thailand had the highest rate of deaths due to road traffic crashes (16.49 per 1 000 000), followed by Vietnam, Morocco and South Africa (15.12 per 1 000 000, 11.96 per 1 000 000 and 10.90 per 1 000 000, respectively). Motorcycle deaths account for most of the heightened risk observed in Thailand and Vietnam. CONCLUSIONS: The leading cause of non-natural deaths in US travellers abroad was road crashes, which exceeds intentional injury as the leading cause of non-natural deaths in almost every country where US citizens travel. Southeast Asia had the highest unintentional injury death rates for US citizens abroad due to the high rates of deaths from motorcycle crashes.