The global social determinants of health (SDOH) market size was USD XX in 2022 and is likely to reach USD XX by 2031, expanding at a CAGR of XX% during 2023–2031. Increase in healthcare costs and the presence of government mandates are likely to boost the market.



Social determinants of health (SDOH) refer to the conditions in which people are born, live, age, grow, and work, and they include a wide range of factors that influence health outcomes. These determinants include socioeconomic status, education, housing, access to healthcare, and social support networks.

Research has shown that these social determinants have a significant impact on an individual’s health outcomes. For example, people with reduce levels of education and income are more likely to experience chronic health conditions such as diabetes and heart disease and high rates of infant mortality, while those with higher levels of education and income tend to have better health outcomes.



Other social determinants of health (SDOH) include discrimination, violence, and social isolation, which can all have negative impacts on an individual’s physical and mental health. Understanding and addressing these social determinants of health is crucial for promoting health equity and reducing health disparities in populations.



The market report finds that the COVID-19 Pandemic has propelled the market. SDOH plays an important role in improving the health of millions of people.

Social Determinants of Health Market Dynamics

Major Driver

Increasing awareness about SDOH in healthcare is expected to drive the market, as it has shown to have more impact on hea

Abstract

An integral part of delivering high-quality healthcare is understanding the social determinants of health (SDOH) of patients and of communities in which healthcare is provided. SDOH are defined by the World Health Organization as the conditions in which people are born, grow, live, work, and age.

SDOH, although experienced by individuals, exist at the community level. Healthcare systems that learn about the communities in which their patients live can adapt their services to meet the communities’ specific needs. This, in turn, can help patients and community members overcome obstacles to achieving and maintaining good health.

Usage

Additional information about SDOH is available on the Agency for Healthcare Research and Quality (AHRQ) SDOH website (https://www.ahrq.gov/sdoh/about.html).

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

Dataset associated with "Searching for the social determinants of health" research study

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.

The table county_2017 is part of the dataset Social Determinants of Health Database (SDOH), available at https://redivis.com/datasets/js6v-91cgjnnm6. It contains 3224 rows across 308 variables.

Find Massachusetts health data by community, county, and region, including population demograhics. 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.

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.

The table SDOH_ZCTA_2018 is part of the dataset Social Determinants of Health Database (SDOH), available at https://redivis.com/datasets/js6v-91cgjnnm6. It contains 33120 rows across 166 variables.

Dataset Card for Dataset Name

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

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  Dataset Description

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  Dataset Sources [optional]… See the full description on the dataset page: https://huggingface.co/datasets/davanstrien/SDOH-NLI.

This dataset was generated from a cross sectional survey of 4142 US adults age 18 and older and includes demographics, 7 Patient Reported Outcomes Measurement Information System (PROMIS) domains with 2 items each, PROMIS-preference (PROPr) score, self-rated health (SRH), 30 social determinants of health (SDoH), and 12 chronic medical conditions.

The survey was offered in English and Spanish, both online and by phone in December 2018. Participants were selected from the AmeriSpeak Panel maintained by NORC at the University of Chicago using sampling strata based on age, race, Hispanic ethnicity, education, and gender. NORC provided demographic information about the sample, latitude and longitude of the participants’ household, and the sampling weights necessary to make nationally representative estimates.

The associated publications used this dataset to assess the sensitivity of SRH questions, PROMIS domains, and PROPr scores to SDoH and chronic medical conditions.

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.

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/

Self-identified assessment of an individual's sense of safey or security about social determinants of health (SDOH).

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.

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.

The table SDOH_ZCTA_2013 is part of the dataset Social Determinants of Health Database (SDOH), available at https://redivis.com/datasets/js6v-91cgjnnm6. It contains 3225 rows across 298 variables.

The North America Social Determinants of Health report features an extensive regional analysis, identifying market penetration levels across major geographic areas. It highlights regional growth trends and opportunities, allowing businesses to tailor their market entry strategies and maximize growth in specific regions.

Background: The WHO Commission on Social Determinants of Health (CSDH 2008) emphasized the importance of addressing structural determinants to improve health equity. However, many health policies, including those in Europe, often focus on individual behavioural determinants rather than structural or intermediary determinants. This systematic review aims to identify and evaluate frameworks and indicators for measuring social determinants of health at the city level in Europe informing both local and national health policies. Methods: This review follows the JBI methodological approach for systematic reviews of frameworks and indicators, reported using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We will include population-based observational studies, case studies, qualitative studies and mixed-methods studies conducted in cities within Europe. Databases such as Ovid MEDLINE, Embase, Scopus, Cochrane Library, and WHO Global Index Medicus will be searched. Data extraction will be performed independently by two reviewers using Covidence, with any discrepancies resolved by a third reviewer. The primary outcomes include identifying effective frameworks and indicators of social determinants of health and developing predefined criteria for their selection. Results: The review will synthesize findings on the current frameworks and indicators used for measuring social determinants of health, highlighting effective practices and identifying gaps in existing frameworks. The predefined criteria for indicator selection will also be developed based on relevance to health outcomes, data availability, reliability, validity, feasibility and comparability. Conclusions: This systematic review will provide insights into the frameworks and indicators used to measure social determinants of health at the city level in Europe. The findings will inform the development of city level indicators for use in Ireland, leading to more effective health policies and contributing to the WHO’s goal of reducing health inequalities.