EHR表现型方法用于测量我们所有人的艾滋病毒感染者的治疗依从性:对艾滋病毒护理连续体的差异和不平等。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01
Yuanzhen Yue, Ashok Khanal, Tianchu Lyu, Sharon Weissman, Chen Liang
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引用次数: 0

摘要

艾滋病毒治疗依从性是艾滋病毒结局的最重要决定因素之一。然而,在美国,只有50%的艾滋病毒感染者继续接受治疗。在临床环境中衡量艾滋病毒治疗依从性是可行的,但是当涉及到越来越多的多站点电子健康记录(EHR)时,缺乏足够的信息学方法来处理EHR的研究。我们试图通过开发一组通过EHR表型方法测量HIV治疗依从性的指标来解决这一差距。我们的方法是在“我们所有人”研究项目中开发和测试的。我们还进行了初步分析,以探讨艾滋病毒治疗依从性的差异和导致依从性差的人口因素。本研究为“All of Us”的HIV护理连续体、差异和不平等研究以及其他使用OMOP公共数据模型规范化的电子病历的系统数据挖掘和分析铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EHR Phenotyping Methods for Measuring Treatment Adherence Among People Living With HIV in All of Us: Towards Disparities and Inequalities in HIV Care Continuum.

HIV treatment adherence is among the most important determinants of HIV outcomes. However, only 50% of people living with HIV in the US were retained in care. Measuring HIV treatment adherence in the clinical settings is feasible but when it comes to the growing number of multi-site Electronic Health Records (EHR), there has been a dearth of research for adequate informatics methods to handle EHR. We sought to address this gap by developing a cluster of metrics for measuring HIV treatment adherence via EHR phenotyping methods. Our methods were developed and tested in the All of Us research program. We also performed preliminary analyses to explore disparities in HIV treatment adherence and demographic factors contributing to poor adherence. This study paves the way for systematic data mining and analyses for the HIV care continuum, disparities, and inequality research on All of Us and other EHR normalized with the OMOP Common Data Model.

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