Our Impact

Improving Patients’ Health with Social Data and AI

The social determinants of health (SDOH) are increasingly being recognized as a key driver of health and wellbeing. SDOH, defined by the World Health Organization (WHO) as “the conditions in which people are born, grow, live, work, and age,” are as diverse as income, access to transportation, access to healthy food, and education. These local and personal factors play a huge role in determining health risk and the success of treatment: Many health experts now believe that your ZIP code could be as important to your health as your genetic code. According to the National Academy of Medicine, socioeconomic and physical environmental factors that are directly linked to your local area account for 80% of overall health outcomes.

Recognizing social determinants at the population and individual level can help health plans and providers coordinate care more efficiently and connect patients with necessary social services. ZeOmega, a Texas-based company that provides population health management solutions to major health plans works with data and records on some 30 million Americans across the country. By analyzing public sources of population data with patient records and using AI applications, ZeOmega is able to predict health risks, but not to a sufficient level of granularity.  In collaboration with CODE, ZeOmega began to explore how integrating SDOH data into their algorithms could more accurately predict individual and population health outcomes. Using data identified by CODE, ZeOmega is now integrating data from these SDOH categories into their population health management platform. As a result of this work, CODE and ZeOmega produced a white paper on Social Determinants of Health: Improving Population Health With Data-Driven Insights.  

In 2020, CODE also explored the impact of social and economic factors on the fight against COVID-19 at its Roundtable on Using SDOH Data for Fight COVID-19 and Support Recovery Efforts. CODE developed a Briefing Paper that provides a landscape analysis of existing COVID-19 data sources, challenges with the collection and use of such data, and other background on the state of the pandemic. Roundtable participants explored the challenges hindering the ability to fully leverage SDOH data to fight the pandemic, and identified rapid opportunities to use social factors to predict and address the impact of COVID-19 at a national, state, and local level. The resulting report includes seven high-priority recommendations that can advance the use of SDOH data to fight COVID-19 in the short term. Roundtable participants were encouraged to continue the conversation and share stories, post ideas, and collaborate with others on the Crowdicity platform. You can read more about the SDOH and COVID-19 program and how HHS can use social data for better healthcare in CODE’s articles on FedScoop.