Data Science to Inform Coordinated Behavioral Health and HIV Care Re-Engagement

数据科学为协调行为健康和艾滋病毒护理重新参与提供信息

• 批准号: 10599453
• 负责人: Jane M. Simoni
• 金额: $ 28.62万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10599453
• 关键词: Age; Algorithms; Americas; Applications Grants; Area; Assertiveness; Behavior Therapy; Books; Caring; Characteristics; Collaborations; Communities; Complex; County; Data; Data Science; Emergency department visit; Ensure; Epidemic; Ethnic Origin; Evidence based intervention; Future; Gender; Goals; HIV; Health; Health Services; Homelessness; Housing; Human; Individual; Information Systems; Infrastructure; Intervention; Investigation; Jail; Logic; Mental Health; Modeling; Outcome; Personal Satisfaction; Persons; Population; Public Health; Quality of life; ROC Curve; Race; Reduce health disparities; Reporting; Research; Research Personnel; Research Project Grants; Research Proposals; Sensitivity and Specificity; Service delivery model; Services; Subgroup; Substance Use Disorder; System; Testing; United States; Universities; Viral Load result; Vision; Washington; Work; barrier to care; base; behavioral health; classification trees; community based treatment; community partnership; community setting; design; evidence base; experience; health data; housing instability; implementation design; implementation research; implementation science; implementation strategy; improved; injection drug use; machine learning method; marginalized population; member; multidisciplinary; outreach; prediction algorithm; predictive modeling; programs; prototype; public health intervention; public health relevance; regression trees; service engagement; severe mental illness; social health determinants; substance use; theories; therapy design

PROJECT SUMMARY / ABSTRACT Engaging the most marginalized people with HIV (PWH) in treatment is crucial to end the HIV epidemic in the U.S. The Ending the HIV Epidemic (EHE) strategy in King County, Washington is designed to improve HIV services for people with complex barriers to care, including homelessness or unstable housing, severe mental illness, and substance use disorders. The health department in King County has developed a robust information exchange system with data from HIV surveillance, jail booking, and emergency room visits to guide public health interventions to re-engage PWH in care (“Data to Care”). The overall goals of the proposed project are to use data science to improve public health Data to Care activities and to establish a community-engaged partnership team that will collaboratively develop a future data-guided mobile outreach & treatment team for high-need PWH. For Aim 1, we will develop and validate an algorithm to prioritize individual PWH for interventions to improve engagement in HIV care and behavioral health services. Using a machine learning method (classification and regression tree models), we will analyze data from >14 years of case investigations and the current health department information exchange system. During the project year, we will newly integrate behavioral health and housing data into the information exchange. Throughout this work, we will incorporate input from our community partners on our use of data for care re-engagement. For Aim 2, we will establish a community-engaged partnership team to develop a mobile outreach & treatment intervention for high-need PWH in King County. This team will include representatives of key service agencies and the health department, people with lived experience, and university researchers. We will use the Transcreation Framework for community-engaged implementation science research to develop a mobile outreach and engagement team based on the Assertive Community Treatment approach, an evidence-based service delivery model that uses a multidisciplinary team to deliver community-based mental health treatment to individuals with severe mental illness. The expected outcomes of this project include: 1) a validated case prioritization algorithm for HIV care re-engagement interventions that will immediately inform health department Data to Care efforts and guide a future mobile outreach & treatment team; 2) a solidified partnership of community agencies, community members with lived experience, the health department, and researchers, which will collaboratively implement and evaluate the future mobile outreach & treatment team; and 3) a refined intervention, implementation strategy, and implementation research logic model to be used in a grant proposal to study the data-guided mobile outreach & treatment team.

项目摘要 /摘要 让最边缘化的艾滋病毒（PWH）参与治疗对结束艾滋病毒流行至关重要 美国终止华盛顿金县的艾滋病毒流行（EHE）战略旨在改善艾滋病毒 为具有复杂护理障碍的人提供服务，包括无家可归或不稳定的住房，严重的精神 疾病和药物使用障碍。金县的卫生部门已开发出强大的信息 交换系统和艾滋病毒监视，监狱预订和急诊室访问的数据指导公共卫生 重新接触PWH的干预措施（“护理数据”）。拟议项目的总体目标是使用 数据科学以改善公共卫生数据以护理活动并建立社区参与的合作伙伴关系 将为高需求PWH的未来数据引导的移动外展与治疗团队合作的团队。 对于AIM 1，我们将开发和验证一种算法以优先考虑单个PWH以改善干预措施 参与艾滋病毒护理和行为卫生服务。使用机器学习方法（分类和 回归树模型），我们将分析> 14年的案例调查和当前健康状况的数据 部门信息交换系统。在项目年度，我们将新地整合行为健康和 将数据存储到信息交换中。通过这项工作，我们将结合社区的意见 我们使用数据进行护理重新参与的合作伙伴。对于AIM 2，我们将建立一个社区参与的 合作团队为金县的高需求PWH开发移动外展与治疗干预措施。这 团队将包括代表关键服务机构和卫生部门，有生活的人 经验和大学研究人员。我们将使用转造框架进行社区参与 实施科学研究，以基于自信 社区治疗方法，一种基于证据的服务交付模型，使用多学科团队 向患有严重精神疾病的人提供基于社区的心理健康治疗。预期 该项目的结果包括：1）艾滋病毒护理重新参与的经过验证的案例优先算法 干预措施将立即告知卫生部门数据以照顾工作并指导未来的手机 外展与治疗团队； 2）社区机构的巩固合作伙伴关系，有实时的社区成员 经验，卫生部门和研究人员，将协作实施和评估未来 移动外展与治疗团队； 3）精致的干预，实施策略和实施 研究逻辑模型将在赠款建议中使用，以研究数据引导的移动外展和治疗团队。