Estimating Patient Satisfaction Through a Language Processing Model: Model Development and Evaluation.

ABSTRACT:

Background

Measuring patient satisfaction is a crucial aspect of medical care. Advanced natural language processing (NLP) techniques enable the extraction and analysis of high-level insights from textual data; nonetheless, data obtained from patients are often limited.

Objective

This study aimed to create a model that quantifies patient satisfaction based on diverse patient-written textual data.

Methods

We constructed a neural network-based NLP model for this cross-sectional study using the textual content from disease blogs written in Japanese on the Internet between 1994 and 2020. We extracted approximately 20 million sentences from 56,357 patient-authored disease blogs and constructed a model to predict the patient satisfaction index (PSI) using a regression approa

SUBMITTER: Matsuda S 

PROVIDER: S-EPMC10540017 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature