TY -非盟的Ahmed Wasim盟——Jagsi莱西玛·非盟- Gutheil,托马斯·G AU -卡茨马修年代PY - 2020 DA - 2020/9/1 TI -识别患者信息的公开披露在社交媒体上卫生专业人员:内容分析Twitter数据的乔- J地中海互联网Res SP - e19746六世- 22 - 9千瓦——社交媒体KW - Twitter千瓦患者信息KW -保密KW -健康专家AB -背景:尊重病人的隐私和保密对于医患关系和公众对医疗专业人员的信任至关重要。在积极参与期间，网上潜在可识别信息披露的频率尚不清楚。目的:本研究的目的是量化医生和其他医疗保健提供者使用#ShareAStoryInOneTweet标签在社交媒体上分享的潜在可识别内容。方法:我们使用Symplur软件访问并搜索Twitter的API，查找包含#ShareAStoryInOneTweet标签的推文。我们从2018年5月分享的43374条推文中识别出1206条由医生、护士和其他卫生专业人员发布的推文。2019年1月对推文内容进行了评估，以确定共享患者姓名或潜在可识别信息的情况的发生率;对公开他人信息的推文进行内容分析。该研究还评估了参与者是否对隐私泄露表示担忧，并估计了删除推文的频率。该研究对10%的样本使用双盲编码来估计编码间的可靠性，使用科恩κ统计量来识别推文内容的潜在可识别性。 Results: Health care professionals (n=656) disclosing information about others included 486 doctors (74.1%) and 98 nurses (14.9%). Health care professionals sharing stories about patient care disclosed the time frame in 95 tweets (95/754, 12.6%) and included patient names in 15 tweets (15/754, 2.0%). It is estimated that friends or families could likely identify the clinical scenario described in 242 of the 754 tweets (32.1%). Among 348 tweets about potentially living patients, it was estimated that 162 (46.6%) were likely identifiable by patients. Intercoder reliability in rating the potential identifiability demonstrated 86.8% agreement, with a Cohen κ of 0.8 suggesting substantial agreement. We also identified 78 out of 754 tweets (6.5%) that had been deleted on the website but were still viewable in the analytics software data set. Conclusions: During periods of active sharing online, nurses, physicians, and other health professionals may sometimes share more information than patients or families might expect. More study is needed to determine whether similar events arise frequently and to understand how to best ensure that patients’ rights are adequately respected. SN - 1438-8871 UR - //www.mybigtv.com/2020/9/e19746 UR - https://doi.org/10.2196/19746 UR - http://www.ncbi.nlm.nih.gov/pubmed/32870160 DO - 10.2196/19746 ID - info:doi/10.2196/19746 ER -