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:

How can we reduce the heterogeneity of diagnoses by different clinicians?
What would a healthcare system designed around AI look like?
Why don't we use risk thresholds for more decisions (e.g., polygenic risk scores to determine cancer screening frequency)?
How can we accelerate the integration of new scientific knowledge into clinical decisions?
To what extent can we automate the process of learning from observational data (EHR and claims, yes, but also behavioral data from phones and other ambient sensors)?
How would our world change if we substantially lengthened our lifespans?

News

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.