This study applies natural language processing (NLP) techniques to patient experience comments. Our goal was to examine the language describing care experiences with two groups of physicians: those with scores in the top 100 and those with scores in the bottom 100 among all physicians (n=498) who received scores from patient satisfaction surveys. Our analysis showed a statistically significant difference in the language used to describe care experiences with these two distinct groups of physicians. This analysis illustrates how to apply NLP techniques in categorizing and building a statistical model for language use in order to identify meaningful language and significant phrasing in a dataset of natural language. We provide a review of limited work at the intersection of language analysis and patient experience. We present our analysis and conclude with a discussion on what care providers and patient experience leaders can learn from language used in patient experience comments for the delivery of patient-centered care.
This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework)
Turpen, Taylor; Matthews, Lea MD; and Guney, Senem PhD, CPXP
"Beneath the surface of talking about physicians: A statistical model of language for patient experience comments,"
Patient Experience Journal: Vol. 6
, Article 10.
Available at: https://pxjournal.org/journal/vol6/iss2/10
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