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Seminar Abstract: Public health has not traditionally been a data-driven field. The good news is that has been changing in recent years, accelerated significantly by the COVID epidemic, but public health and human services organizations have many more fundamental things to worry about before we will have the luxury of considering what machine learning and other advanced analytics can enable. These fundamentals include data-related facets such as electronic data capture and exchange, data quality, data governance, information technology infrastructure, and data management best practices. In addition, data literacy, workforce development, and compensation (that is a fraction of what "quants" can earn in industry) are also major stumbling blocks toward advanced analytics in public health. At the start of the COVID pandemic, many communicable diseases were reporting by fax machine and then hand-entered into a database. Although there was significant interest in predictive modeling to project hospital capacity out in the future, even the most sophisticated models were of limited use to policy makers beyond basic trends and observations from the front lines. Dr. Tenenbaum will give a view from the trenches of North Carolina's COVID-19 pandemic response and lay out NCDHHS's data strategy moving forward. Instructor
Biosketch: Jessie Tenenbaum, PhD, is the Chief Data Officer (CDO) for North Carolina's Department of Health and Human Services. In this role, Dr. Tenenbaum is responsible for the development and oversight of departmental data governance and strategy to enable data-driven policy to improve the health and well-being of North Carolinians. Dr. Tenenbaum is also a faculty member in Duke University's Department of Biostatistics and Bioinformatics. Dr. Tenenbaum is passionate about data-driven decision making, addressing non-clinical drivers of health, mental health, data sharing, and ethical, legal, and social issues around big data in biomedicine. She is also a supporter and advocate for the next generation of women in STEM.