Mootz Jennifer J, Evans Henry, Tocco Jack, Ramon Christian Vivar, Gordon Peter, Wainberg Milton L, Yin Michael T
Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.
New York State Psychiatric Institute, New York, NY, USA.
Mhealth. 2020 Apr 5;6:11. doi: 10.21037/mhealth.2019.10.03. eCollection 2020.
Large data sets, also known as "big data", shared in health information exchanges (HIEs), can be used in novel ways to advance health, including among communities at risk for HIV infection. We examined values and opinions about the acceptability of using electronic healthcare predictive analytics (eHPA) to promote HIV prevention in men who have sex with men (MSM). Our aims were twofold: (I) to evaluate the perspectives of MSM with diverse race/ethnicity and age on the acceptability of predictive analytics to determine individual HIV risk and (II) to determine acceptability of having targeted prevention messaging based upon those risk estimates sent directly to the consumer. Two of the authors facilitated 12 focus groups (n=57) with adult MSM without HIV, living in NYC. Groups were divided by ethnicity (Black, Latino, and White) and age (under 35 and 35 and over). Participants were recruited through HIV prevention sites, community-based organizations, social media, and Internet sites that serve these communities. Grounded theory methods were used to analyze the data with Dedoose.
We identified six main themes related to acceptability: (I) reach, relevance, and potential uptake of using predictive analytics to establish HIV risk and deliver targeted prevention messaging; (II) patient-provider communication; (III) public health and individual rights; (IV) perceptions of intervention effectiveness; (V) electronic health data security; and (VI) stigma. Within each thematic domain, MSM discussed concerns, benefits, and provided recommendations for implementation.
MSM in this study were supportive of the use of "big data" and technology to reach marginalized populations and improve public health, yet expressed concerns about the relevance, effectiveness, and security eHPA. Efforts to advance eHPA for HIV prevention should address these concerns, especially among the most-at-risk communities of color. Development of eHPA for HIV prevention should involve targeted messaging that addresses specific concerns regarding eHPA security, accuracy, and relevance.
在健康信息交换(HIEs)中共享的大型数据集,也被称为“大数据”,可以以新颖的方式用于促进健康,包括在有感染艾滋病毒风险的社区中。我们研究了关于使用电子医疗预测分析(eHPA)促进男男性行为者(MSM)预防艾滋病毒的可接受性的价值观和观点。我们的目标有两个:(I)评估不同种族/族裔和年龄的男男性行为者对预测分析以确定个体艾滋病毒风险的可接受性的看法,以及(II)确定基于这些风险估计直接向消费者发送有针对性的预防信息的可接受性。两位作者在纽约市对57名无艾滋病毒的成年男男性行为者进行了12个焦点小组访谈。小组按种族(黑人、拉丁裔和白人)和年龄(35岁以下和35岁及以上)划分。参与者通过艾滋病毒预防场所、社区组织、社交媒体以及服务这些社区的互联网网站招募。采用扎根理论方法,使用Dedoose软件对数据进行分析。
我们确定了与可接受性相关的六个主要主题:(I)使用预测分析确定艾滋病毒风险并提供有针对性的预防信息的覆盖范围、相关性和潜在采用情况;(II)患者与提供者的沟通;(III)公共卫生和个人权利;(IV)对干预效果的看法;(V)电子健康数据安全;以及(VI)耻辱感。在每个主题领域内,男男性行为者讨论了相关问题、益处,并为实施提供了建议。
本研究中的男男性行为者支持使用“大数据”和技术覆盖边缘化人群并改善公共卫生,但对电子医疗预测分析的相关性、有效性和安全性表示担忧。推进用于艾滋病毒预防的电子医疗预测分析的努力应解决这些担忧,特别是在风险最高的有色人种社区中。开发用于艾滋病毒预防的电子医疗预测分析应包括有针对性的信息传递,以解决有关电子医疗预测分析的安全性、准确性和相关性的具体问题。