Dell Medical School is hosting a talk by Dr Griffin Weber:

"Using Big Data About the Biomedical Workforce to Predict Patient Outcomes and Build New Collaborations."

Large observational clinical databases, such as electronic health records (EHR) and administrative claims, contain a history of patients' interactions with the healthcare system. For example, a laboratory test result reflects not only a patient’s pathophysiology, but also a physician’s decision to order that test at that particular point in time. Most researchers ignore the latter, but analysis of millions of clinical encounters reveals patterns in physician behavior that can be used to improve predictions of patient outcomes, such as survival and readmission rates. This presentation will also show how we load data about the biomedical workforce into a social networking website used by thousands of physicians and scientists across the country. The goal of the website is to help users form new collaborations, but it also provides a platform to study how knowledge flows across disciplines, how effective teams form, and how a person’s position within the biomedical community can influence his or her career trajectory.

Griffin Weber, M.D., Ph.D., is an Associate Professor of Medicine and Head of the Knowledge Discovery & Management Group in the Department of Biomedical Informatics at Harvard Medical School and the Director of the Biomedical Informatics Research Core at Beth Israel Deaconess Medical Center (BIDMC). One of Dr. Weber's research areas is in expertise mining and social network analysis. In his previous role as Chief Technology Officer of Harvard Medical School, he invented an open source social networking website for scientists called Profiles RNS, which is used at dozens of institutions across the country. Dr. Weber studies the data from Profiles RNS to learn how scientific teams form and to determine the role of cross-disciplinary collaborations in biomedical research. At BIDMC, he manages the institution’s clinical data repository, using an open source software platform he helped develop called i2b2 (Informatics for Integrating Biology & the Bedside). The repository contains over 300 million data “facts” for 2.5 million patients. Dr. Weber has an NIH “Big Data to Knowledge” (BD2K) grant to develop data visualizations that illustrate how dynamics of the healthcare system create patterns in large clinical databases, which can be used to predict patient outcomes, such as survival and readmission rates.

Please RSVP here.