Building on the key tenets of precision medicine, Stanford Medical School believes algorithms will transform healthcare into an industry that is more predictive than reactive.
In fact, the school is so invested in the promise of data analytics and artificial intelligence, it launched a new department 18 months ago that focuses specifically on biomedical data, Lloyd Minor, M.D., dean of the Stanford University School of Medicine, told the Wall Street Journal, adding that there is a “huge demand for data scientists” in the healthcare industry.
It’s all part of a transition within the last decade to find ways that data can predict illnesses and prevent disease—an approach Minor refers to as “precision health,” a twist on genomics-based precision medicine initiatives.
“The goal is to be predictive, preventive, and to cure precisely when disease occurs,” he told the WSJ. “It begins really with prediction.”
For example, the medical center recently partnered with computer science experts to develop artificial intelligence that could determine whether clinicians washed their hands before entering a room in the ICU.
Lloyd says Stanford Medical has also created a de-identified clinical data repository that researchers can draw from, and partnered with Google in its Baseline Project that aims to collect health data from 10,000 volunteers.
On the opposite side of the country, Inova Health System has made significant investments in its new Center for Personalized Health and is staffing that new venture with a new cadre of geneticists and bioinformatics software engineers. Late last year, Johns Hopkins unveiled a control center staffed by 24 people designed to streamline care.
Healthcare providers see tremendous promise in AI and precative analytics. One recent survey shows just 30% of hospitals are using predictive analytics currently, but 80% of executives believe the technology can improve patient care.