健康记录优化用于识别艾滋病毒候选人 暴露前预防:一个社区知情的发展模式的方法
Meredith E Clement1,2, Jennifer Thomas3,4, Clare Kelsey1
1Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA.
AIDS patient care and STDs
|June 27, 2025
概括
电子健康记录 (EHR) 模型可以识别比传统得分更多的人进行暴露前预防 (PrEP). 来自社区倡导者和临床医生的当地投入对于优化这些模型和改善PrEP吸收至关重要.
科学领域:
- 公共卫生 公共卫生
- 传染病流行病学 传染病流行病学
- 医疗信息学 医疗信息学
背景情况:
- 基于电子健康记录 (EHR) 的模型在识别暴露前预防 (PrEP) 候选人方面表现有前途,可能会改善传统的风险评分.
- 由于美国HIV (人类免疫缺陷病毒) 流行病学的区域差异,这些模型的本地适应是必不可少的.
研究的目的:
- 在路易斯安那州新奥尔良和巴顿鲁日,为基于EHR的PrEP识别模型的开发和实施提供信息.
- 收集社区倡导者和临床医生的见解,以优化PrEP的模型性能和实施策略.
主要方法:
- 从2023年1月到3月,与18名社区倡导者进行了焦点小组讨论 (FGD),并与12名临床医生进行了深入访谈 (IDI).
- 专题分析用于分析FGD和IDI的音频录音.
- 参与者提供了关于艾滋病毒流行病学,PrEP吸收的观点,并建议了用于模型优化的当地相关变量.
主要成果:
- 社区倡导者报告说,PrEP营销缺乏包容性,阻碍了对当地艾滋病毒发病率的影响.
- 临床医生发现需要改善教育,PrEP提供者和负担得起的药物,以促进PrEP的吸收.
- 利益相关者为EHR模型提出了特定的变量,包括性侵犯史,怀孕,乙型肝炎,性传播感染 (STI) 治疗,监禁史和阿片类药物使用.
结论:
- 基于EHR的模型得到证据支持,用于识别PrEP候选人.
- 纳入当地利益相关者的见解,如社区倡导者和临床医生,对于提高这些模型的性能和成功实施至关重要.
- 解决社区关切和临床医生识别的障碍是优化PrEP可访问性和采用性的关键.
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