Andrea Cook, PhD, is a biostatistician whose work focuses on leveraging available data such as electronic health records (EHRs) to efficiently address important public health questions and improve the overall health of our population. Dr. Cook has developed research methods using EHRs and other existing health care data for major initiatives led by the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC), and the U.S. Food and Drug Administration (FDA). Her work spans many areas, including hypertension control, cancer screening, obesity, diabetes, built environment, and alternative medicine for pain.
The goal of Dr. Cook’s research is finding interventions that improve patient care. She studies how pragmatic clinical trials, which are conducted under real-world conditions in health care organizations such as Kaiser Permanente Washington, can deliver more effective care and improve patient outcomes. Dr. Cook is a lead biostatistician for the Biostatistics and Study Design Core of the NIH Collaboratory, which facilitates the implementation of pragmatic clinical trials. She addresses the numerous statistical challenges of pragmatic clinical trials including how to design studies to answer research questions without impeding the delivery of care and how to use EHRs for more cost-effective studies.
Dr. Cook also studies how to use EHR data to improve the way we monitor the safety of new medical products including vaccines, drugs, and medical devices. She contributes to the FDA Sentinel Initiative and the CDC Vaccine Safety Datalink and has led the development of new statistical methods for actively monitoring medical products for rare adverse events using distributed data networks.
Dr. Cook obtained her PhD in biostatistics from the Harvard T.H. Chan School of Public Health in 2005. She is a member of the American Statistical Association and the Western North American Region of the International Biometric Society. She is also an affiliate professor in biostatistics at the University of Washington.
Role of built environment; obesity prevention and control; nutrition
Analysis of longitudinal data; sequential methods
Physical activity; nutrition; built environment
Cook AJ, Wellman RD, Marsh T, Shoaibi A, Tiwari R, Nguyen M, Boudreau D, Weintraub ES, Jackson L, Nelson JC. Applying sequential surveillance methods that use regression adjustment or weighting to control confounding in a multi-site, rare event, distributed setting: part 2:in-depth example of a re-analysis of the measles-mumps-rubella-varicella combination vacc J Clin Epidemiol. 2019 Sep; 113:114-122. PubMed
Drewnowski A, Arterburn D, Zane J, Aggarwal A, Gupta S, Hurvitz PM, Moudon AV, Bobb J, Cook A, Lozano P, Rosenberg D. The Moving to Health (M2H) approach to natural experiment research:a paradigm shift for studies on built environment and health. SSM Popul Health. 2018 Dec 28;7:100345. doi: 10.1016/j.ssmph.2018.100345. eCollection 2019. PubMed
Shortreed SM, Cook AJ, Coley RY, Bobb JF, Nelson JC. Challenges and opportunities for using big health care data to advance medical science and public health. Am J Epidemiol. 2019 May 1;188(5):851-861. doi: 10.1093/aje/kwy292. PubMed
Shortreed SM, Rutter CM, Cook AJ, Simon GE. Improving pragmatic clinical trial design using real-world data. Clin Trials. 2019 Jun;16(3):273-282. doi: 10.1177/1740774519833679. Epub 2019 Mar 13. PubMed
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