Katherine E. Goodman, PhD, JD

2018      PhD, Epidemiology         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

My research applies novel informatics and machine learning/AI methods, including natural language processing (NLP) and large language models (LLMs), to large electronic health record and claims data. These projects span multiple clinical domains, from infectious diseases to oncology to maternal-fetal medicine, with a particular interest in improving the screening and diagnosis of antimicrobial resistance gut carriage and early-onset colorectal cancer.

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 legal regulation and oversight of clinical algorithms and emerging AI technologies.

Generative AI, natural language processing, clinical algorithms, antimicrobial resistance, Gram-negatives, machine learning, predictive analytics, claims data

• Goodman KE, Blumenthal-Barby J, Redberg RF, Hoffmann DE. FAIRS - A Framework for Evaluating the Inclusion of Sex in Clinical Algorithms. N Engl J Med. 2025 Jan 23;392(4):404-411. doi: 10.1056/NEJMms2411331. Epub 2025 Jan 8. PMID: 39778166.
• Rodriguez-Nava G, Egoryan G, Goodman KE, Morgan DJ, Salinas JL. Performance of a large language model for identifying central line-associated bloodstream infections (CLABSI) using real clinical notes. Infect Control Hosp Epidemiol. 2024 Oct 30:1-4. doi: 10.1017/ice.2024.164. Epub ahead of print. PMID: 39473230.
• Goodman KE, Yi PH, Morgan DJ. AI-Generated Clinical Summaries Require More Than Accuracy. JAMA. 2024 Feb 27;331(8):637-638. doi: 10.1001/jama.2024.0555. PMID: 38285439.
• Goodman KE, Rodman AM, Morgan DJ. Preparing Physicians for the Clinical Algorithm Era. New England Journal of Medicine (NEJM). 2023 Aug 5. https://www.nejm.org/doi/full/10.1056/NEJMp2304839
• Goodman KE, Morgan DJ, Hoffmann DE. Clinical Algorithms, Antidiscrimination Laws, and Medical Device Regulation. JAMA. 2023 Jan 24;329(4):285-286. doi: 10.1001/jama.2022.23870. PMID: 36602795.
• Hoffmann, Diane E. and Goodman, Katherine E., Allocating Scarce Medical Resources During a Public Health Emergency: Can We Consider Sex? (November 21, 2022). 22(2) Houston Journal of Health Law and Policy, Forthcoming 2023, https://houstonhealthlaw.scholasticahq.com/article/88426-allocating-scarce-medical-resources-during-a-public-health-emergency-can-we-consider-sex
• Pineles BL, Harris AD, Goodman KE. Adverse Maternal and Delivery Outcomes in Children and Very Young (Age ≤13 Years) US Adolescents Compared With Older Adolescents and Adults. JAMA. 2022 Nov 1;328(17):1766-1768.
• 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 Forefront (Dec. 24, 2020).