Erich Huang, M.D., Ph.D., has been named the new director for Duke Forge, succeeding founder Rob Califf, M.D., who last year took a full-time role with the Alphabet Co., serving as head of medical strategy and policy and working across the Google Health and Verily enterprises.
Duke Forge is a team of scholars, clinicians, and experts from multiple disciplines who represent Duke’s campus-wide interest in health data science. The organization described its primary mission this way: “to free the data to enable actionable insights and measurements that will guide implementation efforts across health systems.” Califf had been instrumental in development of the Duke AI for Health initiative.
Huang served as principal investigator on an NIH-funded project under the Big Data to Knowledge (BD2K) RFAs, and also served as faculty lead for informatics on the Google Life Sciences-funded Baseline Study. He is also currently leading a Duke University School of Medicine-wide initiative for a data service for biomedical researchers, as well as projects on applied machine learning, user interfaces, and visualization of surgical outcomes (Clinical & Analytic Learning Platform for Surgical Outcomes, CALYPSO) and a chronic kidney disease "early warning" system.
Huang, who also has been named chief data officer for quality for the Duke University Health System, wrote a blog post about his new role.
He said Califf “used an analogy that continues to resonate for me: “we take rigid structures, melt them down, and make them into new tools.” Medicine is changing. If data science is going to help change it for the better, we will need hot fires, and much vigorous pounding on anvils.”
He continued that looking ahead, Duke Forge must anticipate the challenges it will face, including:
• Identifying and managing algorithmic bias;
• Addressing the possibility of “de-skilling” in the health professions as algorithms assume roles in clinical decision and operations support; and
• Squarely addressing the deficiencies of electronic health records in exacerbating clinician burnout, their failures in providing useable data, and their impeding innovation in patient and clinician-facing applications.
