Suppr超能文献

评估患者对自动算法识别 cis 女性进行 HIV 暴露前预防的接受程度。

Assessing Patient Acceptance of an Automated Algorithm to Identify Ciswomen for HIV Pre-Exposure Prophylaxis.

机构信息

Division of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.

Section of Infectious Diseases and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA.

出版信息

J Womens Health (Larchmt). 2024 Apr;33(4):505-514. doi: 10.1089/jwh.2023.0491. Epub 2024 Feb 9.

Abstract

The use of HIV pre-exposure prophylaxis (PrEP) in cisgender women (ciswomen) lags far behind their need. Data elements from the electronic medical record (EMR), including diagnosis of a sexually transmitted infection (STI), can be incorporated into automated algorithms for identifying clients who are most vulnerable to HIV and would benefit from PrEP. However, it is unknown how women feel about the use of such technology. In this study, we assessed women's attitudes and opinions about an automated EMR-based HIV risk algorithm and determined if their perspectives varied by level of HIV risk. Respondents were identified using best practice alerts or referral to a clinic for STI symptoms from January to December 2021 in Chicago, IL. Participants were asked about HIV risk factors, their self-perceived HIV risk, and their thoughts regarding an algorithm to identify ciswomen who could benefit from PrEP. Most of the 112 women who completed the survey (85%) thought they were at low risk for HIV, despite high rates of STI diagnoses. The majority were comfortable with the use of this algorithm, but their comfort level dropped when asked about the algorithm identifying them specifically. Ciswomen had mixed feelings about the use of an automated HIV risk algorithm, citing it as a potentially helpful and empowering tool for women, yet raising concerns about invasion of privacy and potential racial bias. Clinics must balance the benefits of using an EMR-based algorithm for ciswomen with their concerns about privacy and bias to improve PrEP uptake among particularly vulnerable women.

摘要

HIV 暴露前预防(PrEP)在顺性别女性(顺女)中的使用远远落后于她们的需求。电子病历(EMR)中的数据元素,包括性传播感染(STI)的诊断,可以纳入到自动算法中,以识别最容易感染 HIV 且受益于 PrEP 的客户。然而,目前尚不清楚女性对这种技术的看法。在这项研究中,我们评估了女性对基于自动 EMR 的 HIV 风险算法的态度和意见,并确定她们的观点是否因 HIV 风险水平而异。2021 年 1 月至 12 月,在伊利诺伊州芝加哥市,通过最佳实践警报或因性传播感染症状转介至诊所的方式识别出受访者。参与者被问及 HIV 风险因素、自我感知的 HIV 风险以及对识别可能受益于 PrEP 的顺女的算法的看法。在完成调查的 112 名女性中(85%),大多数人认为自己感染 HIV 的风险较低,尽管性传播感染的诊断率很高。大多数人对使用该算法感到舒适,但当被问及该算法专门识别她们时,她们的舒适感就会下降。顺女对使用自动 HIV 风险算法的看法不一,认为这是一种对女性有潜在帮助和赋权的工具,但同时也对侵犯隐私和潜在的种族偏见表示担忧。诊所必须平衡使用基于 EMR 的算法为顺女带来的好处与其对隐私和偏见的担忧,以提高特别脆弱的女性对 PrEP 的接受度。

相似文献

本文引用的文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验