Measuring Implicit Bias in ICU Notes Using Word-Embedding Neural Network Models.

ABSTRACT:

Background

Language in nonmedical data sets is known to transmit human-like biases when used in natural language processing (NLP) algorithms that can reinforce disparities. It is unclear if NLP algorithms of medical notes could lead to similar transmissions of biases.

Research question

Can we identify implicit bias in clinical notes, and are biases stable across time and geography?

Study design and methods

To determine whether different racial and ethnic descriptors are similar contextually to stigmatizing language in ICU notes and whether these relationships are stable across time and geography, we identified notes on critically ill adults admitted to the University of California, San Francisco (UCSF), from 2012 through 2022 and to Beth Israel Deaconess Hospital (BID

SUBMITTER: Cobert J 

PROVIDER: S-EPMC11317817 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature