Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review

Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in wide range outcomes. Electronic records (EHRs) have been widely employed to conduct observational studies the age artificial intelligence (AI). However, there has little research into how make most SBDH information from EHRs. Methods: A systematic search was conducted six databases find relevant peer-reviewed publications had recently published. Relevance determined by screening evaluating articles. Based on selected studies, methodological analysis AI algorithms leveraging EHR data provided. Results: Our synthesis driven an categories, relationship between healthcare-related statuses, several NLP approaches for extracting SDOH clinical literature. Discussion: The associations outcomes are complicated diverse; pathways may be involved. Using Natural Language Processing (NLP) technology support extraction other ideas simplifies identification essential concepts data, efficiently unlocks unstructured aids resolution data-related issues. Conclusion: Despite known disease, factors rarely investigated as interventions improve patient Gaining knowledge about can collected EHRs using predictive models improves chances influencing policy change wellness, ultimately promoting equity. Keywords: Social Behavioral Determinants Health, Artificial Intelligence, Health Records, Processing, Predictive Model