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Objective: To determine whether neighborhood-level social determinants of health (SDoH) influence mortality following sepsis in the United States. Study Setting and Design: Retrospective analysis of data from 4.4 million hospitalized patients diagnosed with sepsis, identified using International Classification of Diseases-10 codes, across the United States. Data Sources and Analytic Sample: De-identified, aggregated data were sourced from the TriNetX Diamond Network. SDoH variables included income, housing cost burden, broadband access, park proximity, racial/ethnic diversity, and the Area Deprivation Index (ADI). The primary outcome was mortality, assessed using univariate and multivariate binomial generalized linear models. Predictors with high multicollinearity (Variance Inflation Factor > 5) were excluded to enhance model stability. Principal Findings: Lower median income, higher ADI scores, limited park access, and lack of broadband connectivity were strongly associated with increased sepsis mortality. Unexpectedly, greater racial/ethnic diversity was negatively associated with mortality, possibly reflecting regional disparities in healthcare access and socioeconomic conditions. Multivariate analyses revealed that the inclusion of SDoH variables attenuated some effects observed in univariate models, highlighting their complex interplay. Random Forest analysis identified park access as the most important predictor of sepsis mortality, emphasizing its role as a potential proxy for broader neighborhood resources. Conclusions: Neighborhood-level SDoH are critical for risk stratification in sepsis prognostic models and should be systematically integrated into predictive frameworks. These findings highlight the need for targeted public health interventions to address social vulnerabilities, enhance access to green spaces, and reduce disparities in sepsis outcomes across diverse populations.
Objective: To determine whether neighborhood-level social determinants of health (SDoH) influence mortality following sepsis in the United States. Study Setting and Design: Retrospective analysis of data from 4.4 million hospitalized patients diagnosed with sepsis, identified using International Classification of Diseases-10 codes, across the United States. Data Sources and Analytic Sample: De-identified, aggregated data were sourced from the TriNetX Diamond Network. SDoH variables included income, housing cost burden, broadband access, park proximity, racial/ethnic diversity, and the Area Deprivation Index (ADI). The primary outcome was mortality, assessed using univariate and multivariate binomial generalized linear models. Predictors with high multicollinearity (Variance Inflation Factor > 5) were excluded to enhance model stability. Principal Findings: Lower median income, higher ADI scores, limited park access, and lack of broadband connectivity were strongly associated with increased sepsis mortality. Unexpectedly, greater racial/ethnic diversity was negatively associated with mortality, possibly reflecting regional disparities in healthcare access and socioeconomic conditions. Multivariate analyses revealed that the inclusion of SDoH variables attenuated some effects observed in univariate models, highlighting their complex interplay. Random Forest analysis identified park access as the most important predictor of sepsis mortality, emphasizing its role as a potential proxy for broader neighborhood resources. Conclusions: Neighborhood-level SDoH are critical for risk stratification in sepsis prognostic models and should be systematically integrated into predictive frameworks. These findings highlight the need for targeted public health interventions to address social vulnerabilities, enhance access to green spaces, and reduce disparities in sepsis outcomes across diverse populations.
BACKGROUND Social determinants of health (SDOH) have been shown to be predictors of health outcomes. Integrating SDOH screening tools into primary care may help to identify individuals or groups with a greater burden of social vulnerability and to promote health equity. OBJECTIVE Our objectives are: 1) to identify the existing screening tools to assess social deprivation in adults in primary care settings; 2) to describe the characteristics of these tools and, where appropriate, their psychometric properties; 3) to describe their validity and reliability in those scales in which validation processes have been conducted; and 4), to identify evidence gaps and provide recommendations for future research METHODS This study protocol was structured according a 5-stage framework, and the scoping review will be conducted according to the Joanna Briggs Institute methodology for scoping reviews and reported following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines Furthermore, due to the fact that not all the SDOH assessment tools are published as scientific articles, we will use a slightly modified form of the scoping review framework outlined by Peters and colleagues to retrieve specific information about specific tools for screening of SDOH in primary care contexts. The following electronic databases will be searched by 2 reviewers: Medline (via PubMed), CINAHL Plus, Web of Science (WoS) and SCOPUS. In addition, to searching on grey literature will search in the following sources: DART-Europe E-thesis Portal, OpenGrey and Google Scholar. After revision of inclusion and exclusion criteria, title, abstracts and full text of included studies will be separately screened by two reviewers. RESULTS A PRISMA-ScR flow chart will be used to depict the sources of evidence screened, and data charting will be used to gain in depth knowledge. The findings of the scoping review will be presented in both narrative and tabular formats, summarizing the existing literature on tools used for SDOH in primary care settings. A critical analysis addressing the variability in tool validation, cultural adaptability, and integration into diverse healthcare systems will be included. Finally, key gaps in the existing evidence will be examined, and research priorities will be proposed emphasizing the need for screening tools culturally sensitive, scalable, and easily integrated into primary care workflows. CONCLUSIONS This scoping review will provide a comprehensive and critical description of the available tools aimed at screening SDOH in primary care settings. Incorporating these tools into routine care has been recognized as a key strategy for addressing health inequalities, given the growing evidence base on the influence of SDOH on health outcomes.
A key challenge in monitoring, managing, and mitigating global health crises is the need to coordinate clinical decision-making with systems outside of healthcare. In the 21st century, human engagement with Internet-connected ubiquitous devices generates an enormous amount of big data, which can be used to address complex, intersectoral problems via participatory epidemiology and mHealth approaches that can be operationalized with digital citizen science. These big data – which traditionally exist outside of health systems – are underutilized even though their usage can have significant implications for prediction and prevention of communicable and non-communicable diseases. To address critical challenges and gaps in big data utilization across sectors, a Digital Citizen Science Observatory (DiScO) is being developed by the Digital Epidemiology and Population Health Laboratory by scaling up existing digital health infrastructure. DiScO's development is informed by the Smart Framework, which leverages ubiquitous devices for ethical surveillance. The Observatory will be operationalized by implementing a rapidly adaptable, replicable, and scalable progressive web application that repurposes jurisdiction-specific cloud infrastructure to address crises across jurisdictions. The Observatory is designed to be highly adaptable for both rapid data collection as well as rapid responses to emerging and existing crises. Data sovereignty and decentralization of technology are core aspects of the observatory, where citizens can own the data they generate, and researchers and decision-makers can re-purpose digital health infrastructure. The ultimate aim of DiScO is to transform health systems by breaking existing jurisdictional silos in addressing global health crises.
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