Clinicians often spend valuable time sifting through dense medical records, searching for “a needle in a haystack,” to assess Prior Authorization requests. We’re leveraging the power of LLMs to extract information from medical records — enabling more time spent with our members, and less time on paperwork. Our latest blog post is the first in a series where we delve into how our team is utilizing AI to help streamline clinician workflows. https://lnkd.in/eQagkKz8
I imagine similar challenges deploying LLM for population health and VBC measure compliance and patient risk stratification. It works very well for QI/QA when there are discrete variables to be extracted from free text.
Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer
1moIt's impressive how you're harnessing the capabilities of LLMs to streamline clinician workflows, minimizing the arduous task of sifting through dense medical records. This strategic integration of AI aligns with historical trends where technological advancements have revolutionized healthcare processes, improving efficiency and patient care. Considering the potential impact of AI-driven solutions on healthcare, how do you envision further optimizing these systems to ensure accuracy and compliance with evolving regulatory standards, ultimately enhancing patient outcomes while maintaining clinician trust and autonomy?