Clinical documentation improvement is important to physicians and hospitals to capture how sick patients truly are by documenting clear and specific diagnoses that impact the encounter, to document it while the patient is still in-house, and for the physician to be able to address it while they are in their workflow. This will show a true reflection of the time and resources used to treat the patient and thus be accurately reflected on discharge.
After participating in this activity, the learner should be better able to:
- Explore practical applications of artificial intelligence and natural language processing in healthcare
- Learn how artificial intelligence can be used specifically for Clinical Documentation improvement
- Stay educated on future healthcare technologies and potential pilot / full deployment projects
Tanuj K. Gupta, MD, MBA
Beth McCauley, RHIA
Lead Clinical Terminologist
As Vice President of Cerner Intelligence, Dr. Tanuj Gupta leads the product management, data science, and engineering teams for machine learning (ML) and artificial intelligence (AI) in healthcare. The team is actively pursuing predictive and prescriptive intelligence, ambient voice solutions, natural language understanding (NLU), and semantic interoperability to make technology in healthcare more intuitive. Tanuj received his medical degree from Northwestern University, a Bachelor of Science in computer science from Boston University, and an MBA in finance from Wharton at the University of Pennsylvania.
As Manager/Lead Clinical Terminologist, Beth McCauley leads a team of terminologists who design, build and support algorithms using machine learning, natural language processing, and ontology to assist physicians on documentation improvement. Beth received a Bachelor of Science in Health Information Management from University of Kansas and a Bachelor of Science in Respiratory Therapy from University of Kansas.
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This webinar sponsored by Cerner.