Automated classification of online reviews of otolaryngologists

The study successfully validated an NLP text classification system for categorizing online physician reviews. Positive reviews were found to have an association with directly-physician related context. 1-star reviews were related to treatment plan, accessibility, wait time, office scheduling, billing, and facilities. This method of text classification effectively discerned the nuances of human-written text, providing valuable insights into online healthcare feedback that is scalable.Level of evidence: Level 3.

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Publication Details

Journal
Laryngoscope Investigative Otolaryngology
Published
2024-11-13
DOI
https://doi.org/10.1002/lio2.70036
Primary Topic
Patient Satisfaction in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Automated classification of online reviews of otolaryngologists

Jake Stenzel, N. R. Schultz, Michael J. Marino
Laryngoscope Investigative Otolaryngology
Patient Satisfaction in Healthcare
article

Automated classification of online reviews of otolaryngologists

Jake Stenzel, N. R. Schultz, Michael J. Marino
article en

Abstract

The study successfully validated an NLP text classification system for categorizing online physician reviews. Positive reviews were found to have an association with directly-physician related context. 1-star reviews were related to treatment plan, accessibility, wait time, office scheduling, billing, and facilities. This method of text classification effectively discerned the nuances of human-written text, providing valuable insights into online healthcare feedback that is scalable.Level of evidence: Level 3.

Laryngoscope Investigative OtolaryngologyVol. 9(6)
University of Arizona (US), WinnMed (US), Mayo Clinic in Florida (US)
Quality Education
Openalex Percentile: Top 64%
Patient Satisfaction in Healthcare
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