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Katherine E. Goodman, PhD, JD

Academic Title:

Assistant Professor

Primary Appointment:

Epidemiology & Public Health

Education and Training

2018      PhD                  Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

Dissertation: Prediction Models for Carbapenem-Resistant Enterobacteriaceae (CRE) and Other Multidrug-Resistant Gram-Negative (MDRGN) Bacteria in Healthcare Settings

2013      PGDiPH              University of Auckland, New Zealand

2010      JD                     Columbia University School of Law, New York, NY          

2006      BA                     Dartmouth College (Moral Philosophy), Hanover, NH

Biosketch

My research interests include Gram-negative antimicrobial resistance in inpatient settings, the development of evidence-based healthcare epidemiology and antimicrobial stewardship policies, and applying machine learning and other prediction model approaches to healthcare epidemiology questions using ‘Big Data.’ An increasing component of my work encompasses use of large claims databases and the application of novel machine learning and informatics techniques, primarily natural language processing, to electronic health record data.

Prior to my doctoral studies, I practiced FDA law in Washington, D.C., and the intersection of law and public health remains an important research interest. With collaborators across the School of Medicine and the School of Law, we have ongoing work focused on the equitable and legal allocation of scarce medical resources during public health emergencies and on the regulation of clinical algorithms under anti-discrimination laws.

Research/Clinical Keywords

Antimicrobial resistance, Gram-negatives, machine learning, predictive analytics, claims data

Highlighted Publications

  • Goodman, K. E., Baghdadi, J. D., Magder, L. S., Heil, E. L., Sutherland, M., Dillon, R., Puzniak, L., Tamma, P. D., & Harris, A. D. (2022). Patterns, Predictors, and Inter-Center Variability in Empiric Gram-Negative Antibiotic Use Across 928 U.S. Hospitals. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, ciac504. Advance online publication. https://doi.org/10.1093/cid/ciac504
  • Goodman, K. E., Heil, E. L., Claeys, K. C., Banoub, M., & Bork, J. T. (2022). Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program. Open forum infectious diseases, 9(7), ofac289. https://doi.org/10.1093/ofid/ofac289
  • Goodman KE, Magder LS, Baghdadi JD, et al. Impact of Sex and Metabolic Comorbidities on COVID-19 Mortality Risk Across Age Groups: 66,646 Inpatients Across 613 U.S. Hospitals. Clinical Infectious Diseases 2020; Available at: https://doi.org/10.1093/cid/ciaa1787.
  • Goodman KE, Pineles L, Magder LS, et al. Electronically Available Patient Claims Data Improve Models for Comparing Antibiotic Use Across Hospitals: Results from 576 U.S. Facilities. Clin Infect Dis 2020 [Epub ahead of print].
  • Goodman KE, Cosgrove SE, Pineles L, et al. Significant Regional Differences in Antibiotic Use Across 576 U.S. Hospitals and 11,701,326 Million Adult Admissions, 2016 - 2017 [published online ahead of print, 2020 May 18]. Clin Infect Dis. 2020; ciaa570. doi:10.1093/cid/ciaa570.
  • Pineles BL, Goodman KE, Pineles L, O'Hara LM, Nadimpalli G, Magder LS, Baghdadi JD, Parchem JG, Harris AD. In-Hospital Mortality in a Cohort of Hospitalized Pregnant and Nonpregnant Patients With COVID-19. Ann Intern Med. 2021 May 11. doi: 10.7326/M21-0974. Epub ahead of print. PMID: 33971101.
  • Bi Q, Goodman KE, Kaminsky J, Lessler J. What Is Machine Learning: a Primer for the Epidemiologist. American Journal of Epidemiology, Volume 188, Issue 12, December 2019, Pages 2222–2239, https://doi.org/10.1093/aje/kwz189
  • Goodman KE, Harris AD, Hoffmann DE. Legal Challenges To Allocating New COVID-19 Antibody Therapies To Those Who Need Them Most. Health Affairs Blog (Dec. 24, 2020).

 

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