Predictive Analytics for Retention in HIV Care

保持护理对艾滋病毒的治疗和预防是必不可少的，但在世界各地艾滋病毒携带者中，只有不到一半的人 美国人被保留在医疗保健领域。有效的保留干预措施，如强化病例管理和 患者导航是高度资源密集型的。随着艾滋病毒护理资源的减少，更好的方法 需要确定哪些患者具有最高的保留失败风险，谁将从保留中获益最多 资源。预测性模型可以量化特定患者未来保留护理失败的风险 他/她独一无二的特点。这种基于电子健康数据和补充的预测模型 社会因素知情数据可以自动化，以实时生成风险预测。与其试图 按照目前的做法，定位并重新接触那些“失去随访”的患者，一个预测性模型将 允许案例经理识别有风险的客户，并在发生保留失败之前进行干预以防止保留失败。 我在临床信息学、生物统计学和流行病学方面有很强的背景。通过这个K23，我会 进一步发展我在纵向数据分析和高级数据分析方面的技能，并创建预测性 护理中的留存模式。在目标1中，我将使用来自 大型临床数据研究网络，覆盖芝加哥的11个医疗保健系统，利用混合效应物流 回归与随机森林。通过目标2，我将评估补充社会因素的加入是否 引入预测模型的知情电子数据源增强了其性能(例如， 电子病历记录、地理空间数据、社交媒体数据)。最后，在目标3中，我将探讨使用该模型的可行性。 实时增加对高危患者的保留努力。 我将在我的导师(约翰·施耐德博士)、共同导师(大卫博士)的监督下完成这个项目 以及我的顾问团队(罗伯特·吉本斯博士、雷德·加尼博士和C·亨德里克斯·布朗博士)。一起， 这个多学科团队带来了全国知名的艾滋病毒研究、EHR研究、纵向 数据分析、自然语言处理、社交媒体数据、实施科学和伦理学。此外, 他们是芝加哥消除艾滋病毒中心(施耐德)、健康和社会中心的主任 科学(梅尔策)、数据科学和公共政策中心(加尼)、卫生统计中心(吉本斯)、 和药物滥用和艾滋病毒预防实施方法中心(布朗)。一个完整的 课程安排、研讨会、有组织的指导、研究活动和会议将为我提供 具备完成拟议研究和向独立过渡所需的技能。我的长期生活 职业目标是成为一名独立的调查员，利用艾滋病毒信息学开发预测模型 以及在整个艾滋病毒护理过程中为艾滋病毒预防和治疗提供信息的工具。指导和培训 我将通过这个K23奖项获得的奖励将为我提供实现这一目标所需的基础，并 该提案将构成未来R01提案的基础。

Retention in care is essential to HIV treatment and prevention, yet less than half of people living with HIV in the U.S. are retained in medical care. Effective retention interventions, such as intensive case management and patient navigation, are highly resource intensive. With diminishing resources for HIV care, better approaches are needed to identify patients at highest risk for retention failure who would most benefit from retention resources. A predictive model may quantify a specific patient's risk of future retention-in-care failure based on his/her unique characteristics. Such a predictive model based on electronic health data and supplemental social factor informed data could be automated to generate risk prediction in real time. Instead of attempting to locate and re-engage patients who are “lost to follow-up” as is the current practice, a predictive model would allow case managers to identify at risk clients and intervene to prevent retention failure before it occurs. I have a strong background in clinical informatics, biostatistics, and epidemiology. Through this K23, I will further develop my skills in longitudinal data analysis and advanced data analytics and create a predictive model of retention in care. In Aim 1, I will create a predictive model of retention in care using EHR data from a large clinical data research network spanning 11 healthcare systems in Chicago, utilizing mixed effects logistic regression and random forest. Through Aim 2, I will evaluate whether the addition of supplemental social factor informed electronic data sources into the predictive model enhances its performance (e.g., unstructured text of EHR notes, geospatial data, social media data). Finally, in Aim 3, I will explore the feasibility of using the model in real time to increase retention efforts for at-risk patients. I will complete this project under the supervision of my mentor (Dr. John Schneider), co-mentor (Dr. David Meltzer), and my advisory team (Dr. Robert Gibbons, Rayid Ghani, and Dr. C. Hendricks Brown). Together, this multidisciplinary team brings nationally renowned expertise in HIV research, EHR research, longitudinal data analysis, natural language processing, social media data, implementation science, and ethics. In addition, they serve as Directors of the Chicago Center for HIV Elimination (Schneider), Center for Health and the Social Sciences (Meltzer), Center for Data Science and Public Policy (Ghani), Center for Health Statistics (Gibbons), and Center for Prevention Implementation Methodology for Drug Abuse and HIV (Brown). An integrated program of coursework, seminars, structured mentorship, research activities, and conferences will provide me with the skills necessary to complete the proposed research and transition to independence. My long-term career goal is to become an independent investigator utilizing HIV informatics to develop prediction models and tools to inform HIV prevention and treatment across the HIV care continuum. The mentorship and training that I will receive through this K23 award will provide me with the foundation necessary to pursue that goal and this proposal will form the basis for future R01 proposals.