Andrea J. Cook, PhD

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“National interest in using data to improve patient care and safety is growing. Our group is developing the biostatistical methods for that work.”

Andrea J. Cook, PhD

Senior Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute

Andrea.J.Cook@kp.org
206-287-4257

Biography

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.

Research interests and experience

  • Biostatistics

    Causal inference; clinical trials; longitudinal data analysis; survival analysis; spatial statistics; nonparametrics; rare disease outcomes; missing data; electronic data; distributed data; postmarketing drug and vaccine safety; study design and analysis
  • Vaccines & Infectious Diseases

    Vaccine safety; methods for observational studies
  • Obesity

    Role of built environment; obesity prevention and control; nutrition

  • Complementary & Integrative Health

    Comparative effectiveness methods
  • Medication Use & Patient Safety

    Analysis of longitudinal data; sequential methods

  • Behavior Change

    Physical activity; nutrition; built environment

Recent publications

Cook AJ, Elmore JG, Zhu W, Jackson SL, Carney PA, Flowers C, Onega T, Geller B, Rosenberg RD, Miglioretti DL. Mammographic interpretation: radiologists' ability to accurately estimate their performance and compare it with that of their peers.  AJR Am J Roentgenol. 2012 Sep;199(3):695-702. PubMed

Zhao S, Cook AJ, Jackson LA, Nelson JC. Statistical performance of group sequential methods for observational post-licensure medical product safety surveillance: a simulation study. Stat Interface. 2012; 5:381-90. PubMed

Green BB, Anderson ML, Cook AJ, Catz S, Fishman P, McClure JB, Reid R. Using body mass index data in the electronic health record to calculate cardiovascular risk. Am J Prev Med. 2012;42:342-7. PubMed

Jackson SL, Cook AJ, Miglioretti DL, Carney PA, Geller BM, Onega T, Rosenberg RD, Brenner RJ, Elmore JG. Are radiologists' goals for mammography accuracy consistent with published recommendations?  Acad Radiol. 2012 Mar;19(3):289-95. Epub 2011 Nov 30. PubMed

 

Research

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Neighborhood density connected to changes in body mass index for children

Study uses geographic data to track change over time.

Research

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Can where you move impact future weight gain?

A new study finds that moving from low- to high-density neighborhoods might be related to reductions in weight gain.

Research

urban setting apartments and skyscrapers obesity and the built environment

Built environment plays little role in weight gain

New research suggests fast food and other aspects of built environments don’t affect weight, contrary to earlier findings.