Beneath the surface of talking about physicians: A statistical model of language for patient experience comments

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 re...

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Autores principales:	Taylor Turpen, Lea Matthews, Senem Guney
Formato:	article
Lenguaje:	EN
Publicado:	The Beryl Institute 2019
Materias:	patient experience language data patient satisfaction surveys natural language processing (nlp) Medicine (General) R5-920 Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/e8cc402c0b6440adb585528e14171f49
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spelling	oai:doaj.org-article:e8cc402c0b6440adb585528e14171f492021-11-15T04:28:44ZBeneath the surface of talking about physicians: A statistical model of language for patient experience comments2372-0247https://doaj.org/article/e8cc402c0b6440adb585528e14171f492019-07-01T00:00:00Zhttps://pxjournal.org/journal/vol6/iss2/10https://doaj.org/toc/2372-0247This 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. <strong>Experience Framework</strong> This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework. (<a href="http://bit.ly/ExperienceFramework">http://bit.ly/ExperienceFramework</a>) <ul> <li><a href="https://www.theberylinstitute.org/page/PXSEARCH#resource-list-all/?view_28_page=1&view_28_filters=%5B%7B%22field%22%3A%22field_38%22%2C%22operator%22%3A%22in%22%2C%22value%22%3A%5B%22PXJ%20Article%22%5D%7D%2C%7B%22field%22%3A%22field_20%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%5D%7D%2C%7B%22field%22%3A%22field_40%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%2C%22Innovation%20%26%20Technology%22%5D%7D%2C%7B%22field%22%3A%22field_41%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%5D%7D%5D">Access other PXJ articles</a> related to this lens.</li> <li><a href="https://www.theberylinstitute.org/page/Ecosystem-InnovationTechnology">Access other resources</a> related to this lens</li> </ul>Taylor TurpenLea MatthewsSenem GuneyThe Beryl Institutearticlepatient experiencelanguage datapatient satisfaction surveysnatural language processing (nlp)Medicine (General)R5-920Public aspects of medicineRA1-1270ENPatient Experience Journal (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	patient experience language data patient satisfaction surveys natural language processing (nlp) Medicine (General) R5-920 Public aspects of medicine RA1-1270
spellingShingle	patient experience language data patient satisfaction surveys natural language processing (nlp) Medicine (General) R5-920 Public aspects of medicine RA1-1270 Taylor Turpen Lea Matthews Senem Guney Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
description	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. <strong>Experience Framework</strong> This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework. (<a href="http://bit.ly/ExperienceFramework">http://bit.ly/ExperienceFramework</a>) <ul> <li><a href="https://www.theberylinstitute.org/page/PXSEARCH#resource-list-all/?view_28_page=1&view_28_filters=%5B%7B%22field%22%3A%22field_38%22%2C%22operator%22%3A%22in%22%2C%22value%22%3A%5B%22PXJ%20Article%22%5D%7D%2C%7B%22field%22%3A%22field_20%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%5D%7D%2C%7B%22field%22%3A%22field_40%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%2C%22Innovation%20%26%20Technology%22%5D%7D%2C%7B%22field%22%3A%22field_41%22%2C%22operator%22%3A%22is%22%2C%22value%22%3A%5B%22%22%5D%7D%5D">Access other PXJ articles</a> related to this lens.</li> <li><a href="https://www.theberylinstitute.org/page/Ecosystem-InnovationTechnology">Access other resources</a> related to this lens</li> </ul>
format	article
author	Taylor Turpen Lea Matthews Senem Guney
author_facet	Taylor Turpen Lea Matthews Senem Guney
author_sort	Taylor Turpen
title	Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
title_short	Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
title_full	Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
title_fullStr	Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
title_full_unstemmed	Beneath the surface of talking about physicians: A statistical model of language for patient experience comments
title_sort	beneath the surface of talking about physicians: a statistical model of language for patient experience comments
publisher	The Beryl Institute
publishDate	2019
url	https://doaj.org/article/e8cc402c0b6440adb585528e14171f49
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Beneath the surface of talking about physicians: A statistical model of language for patient experience comments

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