杂志文章@ 1438- 8871% I Gunther Eysenbach %V 14% N 2% P 50% T在线医生评论:他们跟踪外科医生的数量，一个代理的护理质量?%A Segal,Jeffrey %A Sacopulos,Michael %A Sheets,Virgil %A Thurston,Irish %A Brooks,Kendra %A Puccia,Ryan +医疗正义服务公司，PO Box 49669, Greensboro, NC, 27419，美国，1 336 691 1286,jsegal@medicaljustice.com %K医生评论%K评级网站%K医生评论%K在线声誉%K临床结果%K医生选择%K手术量%K外科医生量%D 2012 %7 10.04.2012 %9原始论文%J J医学互联网Res %G英文%X背景:越来越多的消费者通过互联网寻求健康信息。消费者还使用在线医生评论网站来帮助他们选择医生。这类网站记录了过去患者的数字评分和评论。据我们所知，之前没有研究分析过在医生评论网站上拥有积极在线声誉的医生是否真的提供了更高质量的护理，通常与更好的临床结果和更好的安全记录相关。目的:对于一些手术，手术次数多的外科医生比手术次数少的外科医生有更好的临床结果和安全记录。我们的目标是确定作为临床结果和患者安全代理的外科医生数量是否与在线声誉相关。方法:我们调查了9个在线评论网站上对三种手术(腰椎手术、全膝关节置换术和减肥手术)的高容量和低容量外科医生的数值评分和评论。使用相关的现行程序术语(CPT)代码，从索赔要求最高的四分之一组中随机选择高容量外科医生。 Low-volume surgeons were randomly selected from the lowest quartile of submitted claims for the procedures’ relevant CPT codes. Claims were collated within the Normative Health Information Database, covering multiple payers for more than 25 million insured patients. Results: Numerical ratings were found for the majority of physicians in our sample (547/600, 91.2%) and comments were found for 385/600 (64.2%) of the physicians. We found that high-volume (HV) surgeons could be differentiated from low-volume (LV) surgeons independently by analyzing: (1) the total number of numerical ratings per website (HV: mean = 5.85; LV: mean = 4.87, P<.001); (2) the total number of text comments per website (HV: mean = 2.74; LV: mean = 2.30, P=.05); (3) the proportion of glowing praise/total comments about quality of care (HV: mean = 0.64; LV: mean = 0.51, P=.002); and (4) the proportion of scathing criticism/total comments about quality of care (HV: mean = 0.14; LV: mean = 0.23, P= .005). Even when these features were combined, the effect size, although significant, was still weak. The results revealed that one could accurately identify a physician’s patient volume via discriminant and classification analysis 61.6% of the time. We also found that high-volume surgeons could not be differentiated from low-volume surgeons by analyzing (1) standardized z score numerical ratings (HV: mean = 0.07; LV: mean = 0, P=.27); (2) proportion of glowing praise/total comments about customer service (HV: mean = 0.24; LV: mean = 0.22, P=.52); and (3) proportion of scathing criticism/total comments about customer service (HV: mean = 0.19; LV: mean = 0.21, P=.48). Conclusions: Online review websites provide a rich source of data that may be able to track quality of care, although the effect size is weak and not consistent for all review website metrics. %M 22491423 %R 10.2196/jmir.2005 %U //www.mybigtv.com/2012/2/e50/ %U https://doi.org/10.2196/jmir.2005 %U http://www.ncbi.nlm.nih.gov/pubmed/22491423