TY -的盟Ramasubramanian哈里盟,Joshi Satish AU -克里希,作者PY - 2022 DA - 2022/7/26 TI -专家的智慧和意见的人群在医院质量评级:分析医院比较星评级和谷歌星评级乔- J地中海互联网Res SP - e34030六世- 24 - 7 KW医院质量KW -基于web的评级千瓦在线评级KW -医院比较KW -星评级AB -背景:流行的基于web的门户提供免费和方便的访问用户生成的医院质量评价。医疗保险和医疗补助服务中心(CMS)还发布了医院比较星级评级(HCSR)，这是美国医院质量的综合专家评级，综合了多种质量衡量标准。CMS在2021年修订了HCSR方法。分析基于网络的评级在多大程度上反映了专家对医院质量的衡量是很重要的，因为容易获得的、众包的医院评级会影响消费者对医院的选择。目的:本研究旨在评估反映大众意见的基于web的谷歌医院质量评级与代表专家智慧的HCSR之间的关联，以及在2021年CMS评级体系修订后这些关联的变化。方法:我们在2020年6月使用应用程序编程接口提取谷歌星级评级。2020年4月(HCSR方法修订前)和2021年4月(HCSR方法修订后)的HCSR数据从CMS医院比较网站获得。我们还使用医院比较提供的代码提取了样本中每个医院质量的各个组成部分的分数。分数阶反应模型用于估计谷歌星评级与HCSR以及质量的单个组成部分之间的关联(n=2619)。 Results: The Google star ratings are statistically associated with HCSR (P<.001) after controlling for hospital-level effects; however, they are not associated with clinical components of HCSR that require medical expertise for evaluation such as safety of care (P=.30) or readmission (P=.52). The revised CMS rating system ameliorates previous partial inconsistencies in the association between Google star ratings and quality component scores of HCSR. Conclusions: Crowdsourced Google star hospital ratings are informative regarding expert CMS overall hospital quality ratings and individual quality components that are easier for patients to evaluate. Improvements in hospital quality metrics that require expertise to assess, such as safety of care and readmission, may not lead to improved Google star ratings. Hospitals can benefit from using crowdsourced ratings as timely and easily available indicators of their quality performance while recognizing their limitations and biases. SN - 1438-8871 UR - //www.mybigtv.com/2022/7/e34030 UR - https://doi.org/10.2196/34030 UR - http://www.ncbi.nlm.nih.gov/pubmed/35881418 DO - 10.2196/34030 ID - info:doi/10.2196/34030 ER -