Seltzer Emily K, Guntuku Sharath Chandra, Lanza Amy L, Tufts Christopher, Srinivas Sindhu K, Klinger Elissa V, Asch David A, Fausti Nick, Ungar Lyle H, Merchant Raina M
Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, PA, United States.
Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, United States.
JMIR Form Res. 2022 Mar 31;6(3):e28379. doi: 10.2196/28379.
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.
The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp.
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.
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).
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.
传统上，分娩护理质量是通过医院医疗服务提供者和系统消费者评估来衡量的，但对于患者和护理人员在公众更容易访问的在线网站上报告的护理体验，我们了解得较少。
本研究的目的是通过Yelp上的医院评论来深入了解分娩体验。
我们识别了2005年5月至2017年3月期间在美国在线发布的所有Yelp对美国医院的评论。我们使用一种机器学习工具——潜在狄利克雷分配，在这些评论中识别出100个主题，并使用皮尔逊相关系数r来识别主题与高评分（5星）和低评分（1星）之间的统计显著相关性。
美国医院协会目录中列出的1569家医院至少有一条Yelp帖子，总共贡献了41095条Yelp评论。在这些医院中，919家（59%）至少有一条关于分娩服务的Yelp评分（中位数为9条评论），总共贡献了6523条分娩评论。评论集中在5星（n = 2643，41%）和1星评论（n = 1934，30%）。与好评密切相关的主题包括：一流的护理（r = 0.45，P <.001）、形容工作人员令人安心（r = 0.52，P <.001）、分娩体验（r = 0.46，P <.001）、现代化且干净的设施（r = 0.44，P <.001）以及医院食物（r = 0.38，P <.001）。与1星分娩评论密切相关的主题包括向管理层投诉（r = 0.30，P <.001）、患者缺乏自主性（r = 0.47，P <.001）以及出院问题（r = 0.32，P <.001）。
关于分娩的在线评论内容可以提供有关患者满意度和体验的有意义信息。这些评论中的叙述在传统调查中未被其他方式捕捉到，可以指导努力改善产科护理体验。
