How to automatically turn patient experience free-text responses into actionable insights: a natural language programming (NLP) approach

How to automatically turn patient experience free-text responses into actionable insights: a natural language programming (NLP) approach

Abstract Background Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language Processing (NLP) techniques could provide a data-driven, hospital-independent solution to indicate poi...

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Bibliographic Details
Main Authors: Simone A. Cammel, Marit S. De Vos, Daphne van Soest, Kristina M. Hettne, Fred Boer, Ewout W. Steyerberg, Hileen Boosman
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Natural language processing
Patient experience analysis
PREM
Text analytics
Data science
Machine learning
Online Access:http://link.springer.com/article/10.1186/s12911-020-1104-5

Internet

http://link.springer.com/article/10.1186/s12911-020-1104-5

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