How AI is closing the health equity gap

 Artificial Intelligence (AI) has the potential to revolutionize healthcare, and one area where it can make a significant impact is in improving health equity. Health equity refers to the idea that all people should be able to access the same quality of healthcare. It seems simple, but there are many obstacles to overcome before we can reach that goal.  

Social determinants of health (SDOH) are the circumstances in which people are born and live, including housing stability, physical safety, and access to food, that impact their health outcomes.  

Beginning April 1st of this year, healthcare providers will be able to use ICD-10 codes that address social determinants of health. Many healthcare organizations have already been collecting this data, but struggle to integrate this data into practical solutions regarding health and treatment plans.  

Enter AI. AI’s ability to analyze and make conclusions from massive amounts of data relatively quickly is an asset to any organization that wants to address health equity.  

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One way AI can be used to close the SDOH data gap is by analyzing electronic health data and subsequently identifying common health outcomes related to SDOH. AI can identify patients who are at high risk of developing certain conditions or who are likely to have poor health outcomes. This information can help providers create preventative treatment plans and use targeted outreach to inform patients. 

The information can be used to better inform patients, providers, payers, and public health policy: 

• Providers can have a better understanding of their patient’s medical and social needs 
• Healthcare organizations can better prepare for patient needs and more efficiently utilize their social service resources 
• Payers can better anticipate healthcare costs 
• Public health policies can adapt to meet needs of the public  

An AI-powered data strategy also helps organizations bring precision medicine to patients at scale. One-size-fits-all treatment plans may not be suitable for all patients, and some groups may be more susceptible to certain health conditions than others. By incorporating SDOH factors like food deficiencies, housing, and other socioeconomic realities into a health assessment, providers can tailor treatment plans to each patient.   

AI has the potential to bridge the gap between social determinants of health and healthcare outcomes, helping to achieve health equity. With the ability to quickly analyze large amounts of data, AI can help healthcare providers identify patients who are at risk of developing chronic conditions, allowing for targeted outreach and preventative care. Incorporating social determinants of health into healthcare assessments can also lead to more personalized treatment plans. As healthcare organizations begin to utilize AI in their data strategies, we can expect to see improvements in patient outcomes, more efficient resource allocation, and a more equitable healthcare system overall. 

Divurgent is a solutions provider committed to healthcare IT evolution, and the strategies and processes that make it possible. It helps hospitals, health systems, and affiliated providers with payment and delivery reform, operational efficiency, patient engagement, and raising the quality and lowering the cost of care to improve outcomes towards healthier communities.