Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care

Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care

Background: Quality of cancer care may greatly impact upon patients’ health-related quality of life (HRQoL). Free-text responses to patient-reported outcome measures (PROMs) provide rich data but analysis is time and resource-intensive. This study developed and tested a learning-based text-mining ap...

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Bibliographic Details
Main Authors: Wagland, Richard, Recio Saucedo, Alejandra, Simon, Michael, Bracher, Michael, Hunt, Katherine, Foster, Claire, Downing, Amy, Glaser, Adam W., Corner, Jessica
Format: Article
Published: BMJ Publishing Group 2015
Subjects:
RC 254 Neoplasms. Tumors. Oncology (including Cancer)
RT Nursing
text-mining
PROMs
quality of life
colorectal cancer
machine learning
machine learning algorithms
thematic analysis
thematic content analysis
qualitative methods
Online Access:https://eprints.nottingham.ac.uk/32437/

Internet

https://eprints.nottingham.ac.uk/32437/

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