Sonita S. Bennett

Ms. Bennett is an Informatics Analyst at MedStar National Center for Human factors as well as Department of Biostatistics and Biomedical informatics at MHRI and holds a master’s degree from Johns Hopkins University majoring in Biotechnology and bachelor’s at George Washington University majoring in Computer Science focused on Bioinformatics with a minor in biology. She has extensive experience in retrieving and analyzing EHR data using variety of programming languages and software applications. Her expertise includes exploratory data analysis, customized cohort discovery, and workflow analysis. She also has experience in data visualization. As an informatics analyst, she currently supports multiple projects including the Safe babies and Safe Moms project. The purpose of the project is to implement new CDS tools for screening in the EHR based on known risk factors and developing and implementing new EHR algorithms to predict who is at risk for adverse maternal or infant outcomes. In addition, another project she also supports is the SARS-CoV-2 surveillance project, a prospective multi-state cohort study to conduct real time syndromic surveillance and serologic testing as well as Electronic Record data collection to understand the disease. Finally, she also provides informatics support in the R03 Prospective memory project, this project examines memory demands related to medication administration and strategies nurses use to remember tasks to link errors made during medication administration to memory demands. Prior to joining the Human factors team, Ms. Bennett worked as a Research Fellow at the Food and Drug Administration (FDA) and the National Institute of Health (NIH), where she was able to gain experience in basic science and data analysis. Through her work at the FDA in the Laboratory of Molecular and Developmental Immunology within the Division of Monoclonal Antibodies, she was able to develop a database from the ground up. This database consisted of monoclonal antibodies for the new drugs that were under review in her branch. She was able to work closely with doctors and scientists to collect the required information for the database. Additionally, from her work at both NIH and FDA, she has not only been able to gain data analytics skills but also experimental skills in the laboratory.