REDUCE: Re-imagining Documentation as Ultimately Computable from Clinical Encounters

Faculty: Kevin Johnson

Opportunity: What if, instead of spending more time documenting a clinical encounter than engaging with the patient, health care providers could leverage AI-based technology to generate documentation?  Could such tools enable us to think of the computational system as a partner in ensuring the safety and quality of each visit?


Challenge: Studies by my lab and others show that at least two hours is spent documenting each hour of patient-facing time; EHR technology is currently among the least usable of all commonly available technologies. REDUCE aims to eliminate (or at least radically reduce) the need for clinician-generated documentation in healthcare, by leveraging the latest advances in computer science and artificial intelligence to observe and to computationally analyze audio and video of clinical interactions.  REDUCE will provide real-time feedback during clinical visits, as well as automated generation of visit summaries.