Electronic Health Records and clinical decision support has remained remarkably simple for decades; there’s great potential (and need) for AI to guide clinicians on tougher questions of patient care. But these advanced techniques have their own limitations – sometimes quite insidious – that can lead to bad decisions and worse care. Nick, Sudipto and Darryl discuss the problem of bias in AI, and new ways to hopefully address it.
Dr. Nicholas Genes is an emergency physician and clinical informaticist – he’s implemented EHRs, developed mHealth apps, and led telemedicine initiatives. From his role in IT leadership at a large urban academic medical center, he remains an enthusiastic believer in the potential for technology to improve patient care and safety, while making staff more efficient. Over the years, though, he’s also seen the toll of unintended consequences, and has developed a healthy skepticism toward rosy pitch decks or sweeping policy initiatives.
Sudipto Srivastava is a digital health enthusiast whose career has been dedicated to delivering practical innovations in healthcare. He has worked for leading healthcare organizations in New York City, giving him an insider’s perspective while exposing him to a hotbed of innovative startups. Whether it’s AI or telemedicine or remote monitoring, he has kept the pulse on the disruptive innovation streaming through healthcare.
