Patient Experience and Satisfaction in Online Reviews of Obstetric Care: Observational Study

JMIR FORMATIVE RESEARCH(2022)

引用 3|浏览14
暂无评分
摘要
Background: The quality of care in labor and delivery is traditionally measured through the Hospital Consumer Assessment of Healthcare Providers and Systems but less is known about the experiences of care reported by patients and caregivers on online sites that are more easily accessed by the public. Objective: The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp. Methods: We identified all Yelp reviews of US hospitals posted online from May 2005 to March 2017. We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson r to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. Results: A total of 1569 hospitals listed in the American Hospital Association directory had at least one Yelp posting, contributing a total of 41,095 Yelp reviews. Among those hospitals, 919 (59%) had at least one Yelp rating for labor and delivery services (median of 9 reviews), contributing a total of 6523 labor and delivery reviews. Reviews concentrated among 5-star (n=2643, 41%) and 1-star reviews (n=1934, 30%). Themes strongly associated with favorable ratings included the following: top-notch care (r=0.45, P<.001), describing staff as comforting (r=0.52, P<.001), the delivery experience (r=0.46, P<.001), modern and clean facilities (r=0.44, P<.001), and hospital food (r=0.38, P<.001). Themes strongly correlated with 1-star labor and delivery reviews included complaints to management (r=0.30, P<.001), a lack of agency among patients (r=0.47, P<.001), and issues with discharging from the hospital (r=0.32, P<.001). Conclusions: Online review content about labor and delivery can provide meaningful information about patient satisfaction and experiences. Narratives from these reviews that are not otherwise captured in traditional surveys can direct efforts to improve the experience of obstetrical care.
更多
查看译文
关键词
patient satisfaction, Yelp, online reviews, labor and delivery, ob-gyn, quality improvement, machine learning, labor, delivery, natural language processing, maternal health, ML, patients, obstetrics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要