Health equity data analysis provides information on how to think about, collect, and analyze local data related to health equity. It provides a starting point for understanding how to document health inequities. This interesting information came to us from Healthcare DIVE in their article, “How data and AI can advance health equity.”

As pervasive health disparities in the United States continue to widen, data and artificial intelligence (AI) offer the potential to help close that gap. New technologies can analyze large, diverse data sets, informing the work of researchers, decision makers, and policymakers across healthcare.

The COVID-19 outbreak in the U.S. has shown the country what all hospital and health systems leaders have known for years: serious gaps exist in access, cost, and quality for patients based on race, ethnicity, gender and gender identity, age, sexual orientation, and other demographic and socio-economic factors. Hospitals and health systems have the opportunity to use data to identify outcome disparities resulting from inequities and societal factors influencing health.

If done correctly, AI can ultimately improve care delivery, advance proactive healthcare planning and predictive treatments, reduce clinician burnout, and drive better patient outcomes. 

Data Harmony is Access Innovations’ AI suite of tools that leverages explainable AI for efficient, innovative, and precise semantic discovery of new and emerging concepts, to help find the information you need when you need it.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.