Publications 

Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients

 

Abstract

One core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality 'serious illness communication' about patient goals and prognosis is required to support patient-centered decision-making, however current methods are not sensitive enough to measure the quality of this communication or determine whether care delivered matches patient priorities. Natural language processing (NLP) offers an efficient method for identification and evaluation of documented serious illness communication, which could serve as the basis for future quality metrics in oncology and other forms of serious illness. In this study, we trained NLP algorithms to identify and characterize serious illness communication with oncology patients.

 

URL

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285137/

 

LaTeX

@article{Davoudi2022AMIA,
	title    = {Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients},
	author   = {Davoudi, Anahita and Tissot, Hegler and Doucette, Abigail and Gabriel, Peter E and Parikh, Ravi and Mowery, Danielle L and Miranda, Stephen P},
	journal  = {AMIA Annu Symp Proc},
	volume   = {2022},
	pages    = {168--177},
	month    = {May},
	year     = {2022},
	address  = {United States}
}