Leveraging AI/NLP Technology to Reduce Health Inequities and Improve Patient Outcomes
While SDoH can provide a wealth of information about non-clinical factors impacting a patient’s overall well-being, identifying a patient’s SDoH can be challenging because the details aren’t always easily accessible, especially when clinicians are making important treatment decisions. SDoH data often resides in EHRs but are essentially trapped as unstructured text within clinical notes, patient-reported data, secure email exchanges, patient portal messages, and telehealth transcripts.
To unlock insights from unstructured data and improve patient care, healthcare organizations can leverage the power of AI-based technologies, such as natural language processing (NLP). With NLP, providers can eliminate manual and time-consuming chart reviews to find critical patient information.
To reduce the systemic health inequities that have put so many individuals at higher risk of getting sick and dying from Covid-19, healthcare organizations must leverage advanced technologies such as NLP to identify SDoH and other critical information from unstructured notes.
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