Nathaniel Hendrix
Nathaniel Hendrix

I’m a researcher and data scientist with the American Board of Family Medicine and their Center for Professionalism and Value in Health Care.

My research focuses on natural language processing with clinical notes, epidemiology, and artificial intelligence for decision support.

Here are some questions that motivate me:

News

March 26, 2024: Another paper on physician satisfaction with EHRs and interoperability out in JAMA Network Open.
February 8, 2024: New preprint on medRxiv showing data on the massive lack of coordination about long COVID diagnosis in primary care: Heterogeneity of Diagnosis and Documentation of Post-COVID Conditions in Primary Care: A Machine Learning Analysis.
January 4, 2024: Preprint posted of a comparison I wrote between three surveys of physician experience with EHRs: Comparative Analysis of Three Surveys on Primary Care Providers’ Experiences with Interoperability and Electronic Health Records.
December 8, 2023: Preprint posted of my first little foray into psychometrics: Blueprinting the Future: Automatic Item Categorization using Hierarchical Zero-Shot and Few-Shot Classifiers. Led by Ting Wang.
October 31, 2023: At NAPCRG 2023, I presented a workshop on NLP for clinical researchers. The presentation also includes a linked Google Colab notebook with sample code!
August 7, 2023: Preprint posted of work with NCATS on how prior COVID-19 affects infection severity: Influence of Prior SARS-CoV-2 Infection on COVID-19 Severity: Evidence from the National COVID Cohort Collaborative
June 14, 2023: A policy brief I led titled How Do Family Physicians Document Patients’ Social Needs in Electronic Health Records? has been published in the Journal of the American Board of Family Medicine.
April 7, 2023: NASEM has posted a video of a talk I gave on AI in medical education.
March 23, 2023: Journal of General Internal Medicine has published a paper I led titled Variation in Family Physicians’ Experiences Across Different Electronic Health Record Platforms: a Descriptive Study.