The work of our DBEI Distinguished Faculty members demonstrates how the synergies among our three core disciplines serve important population-health issues. We welcomed our inaugural class in 2017-18. In 2018-19, we named the second annual class. Read more about the work of the first two classes below.
Most recently, we announced our third annual class: Blanca Himes, PhD, of our Informatics Division, and Pamela Shaw, PhD, of our Biostatistics Division. Join us for Research Day 2021, March 24, to hear virtual talks by Dr. Himes (Enhancing Electronic Health Record Data to Address Health Disparitiesand) and Dr. Shaw (Efficient Study Designs for the Analysis of Error-Prone Electronic Health Records [EHR] Data).
Class of 2018-19
Below we highlight research projects by our 2018-19 class. Penn community members may log in via Penn Key to view their Dec. 1, 2020 talks.
Expanding the Reach of the EHR Through Data Integration
Yong Chen, PhD, of our Biostatistics Division, is exploring new ways to leverage the electronic health record, with new methods for data integation. Read more.
Bridging the Gap Between Complex Sensor Data and Knowledge
Wearable sensor data carry implications for a wide range of outcomes in patients—including, notably, for their mental-health status. Haochang Shou, PhD, is finding new ways to overcome the statistical challenges they pose. Read more.
Below we highlight research projects by our inaugural class (2017-18). View video about their work.
Partnering to Address Psoriatic Arthritis
Alexis Ogdie-Beatty, MD, MSCE, of our Epidemiology Division and Alisa Stephens Shields, PhD, of our Biostatistics Division are exploring how we can revolutionize the design of clinical trials in psoriatic arthritis, proposing solutions that fit the disease’s diverse population. Read more.
Looking to a Collaborative Approach to Advance MS Solutions
Two recent biostatistics methods studies by Russell (“Taki”) Shinohara, PhD, offer potentially game-changing approaches for multiple sclerosis diagnosis and care. He looks forward to advancing the techniques in collaboration with clinical epidemiologists. Read more.
Working Across Disciplines to Understand Sex Differences in Concussion
By applying machine-learning approaches, can we detect sex differences that have not emerged through traditional epidemiologic analyses of concussion? Read more about a new informatics collaboration that epidemiologist Douglas Wiebe, PhD, and team are pursuing.
Read about our ceremony that honored the inaugural Distinguished Faculty members.