SAN FRANCISCO — EHRs are everywhere … no, wait, you already know that. What’s more elusive, though, is exactly what the next generation of health IT will look like. But I caught a glimpse last week at the Healthcare IT News Big Data and Healthcare Analytics Forum.
The usual suspects were on hand: population health and precision medicine, predictive and prescriptive analytics, even natural language processing and, not coincidentally, big data itself.
Some new-ish faces showed up as well. Artificial intelligence, cognitive clinical science and machine learning, for instance, and then there was “targeted learning” a fresh idea for many in healthcare brought to the conference by Maya Petersen, MD, an associate professor of biostatistics and epidemiology at the UC Berkeley School of Public Health.
Petersen described targeted learning as encompassing machine learning and inferential theory to both understand complex relations within data sets and quantify the reliability of results, thereby ultimately yielding actionable insights.