Paper Info
Title
What Do Patients Care About? Mining Fine-grained Patient Concerns from Online Physician Reviews Through Computer-Assisted Multi-level Qualitative Analysis.
Abstract
Online physician review (OPR) websites have been increasingly used by healthcare consumers to make informed decisions in selecting healthcare providers. However, consumer-generated online reviews are often unstructured and contain plural topics with varying degrees of granularity, making it challenging to analyze using conventional topic modeling techniques. In this paper, we designed a novel natural language processing pipeline incorporating qualitative coding and supervised and unsupervised machine learning. Using this method, we were able to identify not only coarse-grained topics (e.g., relationship, clinic management), but also fine-grained details such as diagnosis, timing and access, and financial concerns. We discuss how healthcare providers could improve their ratings based on consumer feedback. We also reflect on the inherent challenges of analyzing user-generated online data, and how our novel pipeline may inform future work on mining consumer-generated online data.
Year
Venue
DocType
2020
AMIA
Conference
Volume
ISSN
Citations 
2020
1942-597X
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Lu He112.40
Changyang He201.35
Yue Wang325.57
Zhaoxian Hu400.34
Kai Zheng500.68
Yunan Chen600.68