Global Social Determinants of Health Market is Segmented By Type (Economic Stability, Food Insecurity, Social Context, Environment, Education, Healthcare Systems), By Application (Authentication, Authorization, Person-matching, Consent management, Privacy), By End User (Payers, Providers), By Geography

This dataset contains place-level (incorporated and census-designated places) social determinants of health (SDOH) measures from the American Community Survey 5-year data for the entire United States—50 states and the District of Columbia. Data were downloaded from data.census.gov using Census API and processed by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. These measures complement existing PLACES measures, including PLACES SDOH measures (e.g., health insurance, routine check-up). These data can be used together with PLACES data to identify which health and SDOH issues overlap in a community to help inform public health planning. To access spatial data, please use the ArcGIS Online service: https://cdcarcgis.maps.arcgis.com/home/item.html?id=d51009ea78b54635be95c6ec9955ec17.

This maps displays the composite outcomes for all 5 domains (Economic Stability, Education Access and Quality, Health Care Access and Quality, Social and Community Context, and Neighborhood / Built Environment), from the PLAN4Health - Miami Valley Health Environment Assessment project. Learn more about the PLAN4Health - Miami Valley Health Environment Assessment by following this link.

Find Massachusetts health data by community, county, and region, including population demographics. Build custom data reports with over 100 health and social determinants of health data indicators and explore over 28,000 current and historical data layers in the map room.

BackgroundDespite the incentives and provisions created for hospitals by the US Affordable Care Act related to value-based payment and community health needs assessments, concerns remain regarding the adequacy and distribution of hospital efforts to address SDOH. This scoping review of the peer-reviewed literature identifies the key characteristics of hospital/health system initiatives to address SDOH in the US, to gain insight into the progress and gaps.MethodsPRISMA-ScR criteria were used to inform a scoping review of the literature. The article search was guided by an integrated framework of Healthy People SDOH domains and industry recommended SDOH types for hospitals. Three academic databases were searched for eligible articles from 1 January 2018 to 30 June 2023. Database searches yielded 3,027 articles, of which 70 peer-reviewed articles met the eligibility criteria for the review.ResultsMost articles (73%) were published during or after 2020 and 37% were based in Northeast US. More initiatives were undertaken by academic health centers (34%) compared to safety-net facilities (16%). Most (79%) were research initiatives, including clinical trials (40%). Only 34% of all initiatives used the EHR to collect SDOH data. Most initiatives (73%) addressed two or more types of SDOH, e.g., food and housing. A majority (74%) were downstream initiatives to address individual health-related social needs (HRSNs). Only 9% were upstream efforts to address community-level structural SDOH, e.g., housing investments. Most initiatives (74%) involved hot spotting to target HRSNs of high-risk patients, while 26% relied on screening and referral. Most initiatives (60%) relied on internal capacity vs. community partnerships (4%). Health disparities received limited attention (11%). Challenges included implementation issues and limited evidence on the systemic impact and cost savings from interventions.ConclusionHospital/health system initiatives have predominantly taken the form of downstream initiatives to address HRSNs through hot-spotting or screening-and-referral. The emphasis on clinical trials coupled with lower use of EHR to collect SDOH data, limits transferability to safety-net facilities. Policymakers must create incentives for hospitals to invest in integrating SDOH data into EHR systems and harnessing community partnerships to address SDOH. Future research is needed on the systemic impact of hospital initiatives to address SDOH.

The table SDOH_ZCTA_2011 is part of the dataset Social Determinants of Health Database (SDOH), available at https://redivis.com/datasets/js6v-91cgjnnm6. It contains 33120 rows across 133 variables.

This dataset contains ZCTA-level social determinants of health (SDOH) measures from the American Community Survey 5-year data for the entire United States—50 states and the District of Columbia. Data were downloaded from data.census.gov using Census API and processed by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. These measures complement existing PLACES measures, including PLACES SDOH measures (e.g., health insurance, routine check-up). These data can be used together with PLACES data to identify which health and SDOH issues overlap in a community to help inform public health planning.

To access spatial data, please use the ArcGIS Online service: https://cdcarcgis.maps.arcgis.com/home/item.html?id=d51009ea78b54635be95c6ec9955ec17.

This archived SDOH Database (beta version) is available for reference. The most recent version of the SDOH Database replaces the beta version and is available on the main page. To ensure consistency in variable names and construction, analyses should not combine data from the beta version and the updated database.Download DataThe SDOH Data Source Documentation (PDF, 1.5 MB) file contains information for researchers about the structure and contents of the database and descriptions of each data source used to populate the database.The Variable Codebook (XLSX, 494 KB) Excel file provides descriptive statistics for each SDOH variable by year.

The Health Atlas for the City of Los Angeles 2021 presents a data-driven snapshot of health conditions and outcomes in the City of Los Angeles. It illustrates geographic variation in socio-economic conditions, demographic characteristics, the physical environment, and access to support systems and services, and provides a context for understanding how these factors contribute to the health of Angelenos.The data underscore a key issue: where Angelenos live often influences their health and well-being. Los Angeles is a city with great health disparities and the patterns of inequality are reflected in many of the indicators highlighted in the Health Atlas. The spatial characteristics of physical and social determinants of health have roots in structural racism and historic and ongoing discrimination. Historic policies such as redlining have had lasting effects in Los Angeles. The analysis is a first step in understanding the areas of the City burdened with the most adverse health-related conditions in order to improve health outcomes and environmental justice for all Angelenos.The Health Atlas contains 115 maps covering regional context, demographic and social characteristics, economic conditions, education, health conditions, land use, transportation, food systems, crime, housing, and environmental health. In addition to displaying US Census Bureau, City, County, and other data, the Health Atlas contains several indices to facilitate comparisons across the city on subjects including environmental hazards (Map 113: Pollution Burden Index), transportation quality (Map 84: Transportation Index), and economic conditions (Map 19: Hardship Index). The Health Atlas culminates in a Community Health and Equity Index (Maps 114 and 115) which combines many of the above variables into a single index to compare health conditions across the City of Los Angeles. The Community Health and Equity Index can be used to understand the areas of the city with the highest vulnerabilities and cumulative burdens as compared to other portions of the City.The Health Atlas for the City of Los Angeles was originally developed in 2013 as an early step in the process to develop a Health, Wellness, and Equity Element of the General Plan (also known as the Plan for a Healthy Los Angeles). This data set is an update of the Health Atlas, completed in 2021. The Health Element and both editions of the Health Atlas are available as PDFs on the Los Angeles City Planning website, https://planning.lacity.gov.

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: HSD Data Book 2022Item Type: URLSummary: Health and Human Services Department of New Mexico 2022 Data Book. For a link to the download page with County Fact Sheets, and other data, see here: https://www.hsd.state.nm.us/2022-data-book/Notes: Link to PDF maintained by HSDPrepared by: Uploaded by EMcRae_NMCDCSource: Health and Human Services Dept Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=ba99c113ced244bbbeb4026da10bb98aUID: 73Data Requested: Annual data book on socioeconomic population healthMethod of Acquisition: Published publicly online by HSDDate Acquired: May 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 6Tags: PENDING

Coronavirus-19 Cases vs. Deaths (Hourly Update)See Detailed graphs and tables describing the COVID-19 crisis in New Mexico, updated daily (includes some county level data not found elsewhere) - https://sites.google.com/view/new-mexico-covid19-tracking/homeCDC's Description of the Social Vulnerability Index (takes into account 15 different selected indicators):https://svi.cdc.gov/

This dataset tracks the updates made on the dataset "Social Determinants and Health Equity Resource Guide" as a repository for previous versions of the data and metadata.

These datasets provide de-identified insurance data for hypertension hyperlipidemia. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 calendar year.

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Agricultural Workers Health and Safety Information - English VersionItem Type: PDFSummary: Know your rights: Agricultural workers health and safety information with COVID information, factsheet.Notes: Spanish version availablePrepared by: Uploaded by EMcRae_NMCDCSource: New Mexico Center on Law and PovertyFeature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=edb60e07d062487eaea9854f6e710b2eUID: 97Data Requested: NM Center on Law and Poverty dataMethod of Acquisition: Publicly posted onlineDate Acquired: May 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 5Tags: PENDING

These datasets provide de-identified insurance data for hyperlipidemia. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 calendar year.

The Social Determinants of Health report provides a detailed analysis of emerging investment pockets, highlighting current and future market trends. It offers strategic insights into capital flows and market shifts, guiding investors toward growth opportunities in key industry segments and regions.

IntroductionSince February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States.MethodsA retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022.Results and discussionIn this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90  days (n = 19,679), and 13% were readmitted within 30  days (n = 11,912). In logistic regression analyses, Hispanic and non-Hispanic Asian patients were less likely to be readmitted within 90  days (adjusted odds ratio [aOR]: 0.8, 95% confidence interval [CI]: 0.7–0.9, and aOR: 0.8, 95% CI: 0.8–0.8), while non-Hispanic Black patients were more likely to be readmitted (aOR: 1.1, 95% CI: 1.0–1.1, p = 0.002), compared to non-Hispanic White patients. Area deprivation index displayed a clear dose–response relationship to readmission: patients living in the most disadvantaged neighborhoods were more likely to be readmitted within 30 (aOR: 1.1, 95% CI: 1.0–1.2), 60 (aOR: 1.1, 95% CI: 1.2–1.2), and 90  days (aOR: 1.2, 95% CI: 1.1–1.2), compared to patients from the least disadvantaged neighborhoods. Our findings demonstrate the lasting impact of COVID-19, especially among members of marginalized communities, and the increasing burden of COVID-19 morbidity on the healthcare system.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

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