Leveraging large-scale administrative claims data to evaluate prescription opioid use, risks, and outcomes in older adults living with HIV

利用大规模行政索赔数据来评估老年艾滋病毒感染者的处方阿片类药物使用、风险和结果

• 批准号: 10917538
• 负责人: Stephanie Shiau
• 金额: $ 24.94万
• 依托单位: RUTGERS BIOMEDICAL AND HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10917538
• 关键词: Accident and Emergency department; Address; Adverse event; Affect; Age; Age Years; Aging; Anti-Retroviral Agents; Area; Area Under Curve; Benzodiazepines; Data; Data Set; Databases; Dementia; Development Plans; Disease; Dose; Drug Interactions; Drug Prescriptions; Drug Utilization; Drug usage; Elderly; Environment; Epidemic; Epidemiology; Foundations; Fracture; General Population; Goals; HIV; HIV Infections; HIV risk; Health; Hospitalization; Individual; Injecting drug user; Inpatients; Interdisciplinary Study; Intervention; Longevity; Machine Learning; Medicare; Medicare claim; Mental Health; Mentored Research Scientist Development Award; Mentors; Methods; Morbidity - disease rate; Older Population; Opioid; Outcome; Outpatients; Pattern; Persons; Pharmaceutical Preparations; Pharmacoepidemiology; Polypharmacy; Population; Positioning Attribute; Prevention; Prevention program; Protease Inhibitor; Quality of life; Reporting; Research; Research Infrastructure; Research Personnel; Research Priority; Research Support; Risk; Sampling; Techniques; Training; United States National Institutes of Health; Universities; Visit; adverse event risk; adverse outcome; antiretroviral therapy; beneficiary; career development; chronic pain; clinical decision support; clinical practice; co-infection; comorbidity; experience; falls; health care service utilization; high risk; improved; infection risk; insight; machine learning method; mortality; multidisciplinary; non-nucleoside reverse transcriptase inhibitors; novel; opioid use; prescription opioid; profiles in patients; programs; research and development; sedative; substance use; symposium; tool; treatment program

PROJECT SUMMARY The purpose of this Mentored Research Scientist Development Award (K01) is to provide support for me to become an independent investigator with a multidisciplinary research program in HIV at the intersection of prescription drug use, comorbidities, and aging. In this project, I propose to leverage existing administrative claims data from Medicare beneficiaries ≥65 years of age from 2007-2018 to determine how high-risk prescription opioid use, e.g. high dose use (≥120 mg/day) or prolonged use (≥90 days), affects health outcomes and health care utilization in older people living with HIV (PLWH). Building on my strong foundation in HIV epidemiology and HIV comorbidities across the lifespan, the training from this K01 will allow me to (1) obtain proficiency in the analysis of large-scale, longitudinal administrative claims data; (2) attain content expertise in prescription drug utilization research and pharmacoepidemiology; and (3) develop expertise in the application of machine learning methods. My career development plan includes specific coursework, seminars, conferences, directed readings, and tailored mentoring from a multidisciplinary team comprised of experts in administrative claims data, substance use epidemiology, pharmacoepidemiology, and machine learning methods. Rutgers University provides an exceptional environment for completion of this training, with research support and infrastructure for analyzing large, multiyear datasets (including Medicare claims) and conducting high-impact HIV research. The proposed research is significant given that a substantial gap exists in understanding how prescription opioid use affects a growing population of aging PLWH who commonly report chronic pain, and have multiple comorbidities, increasing polypharmacy, and increased risk for untoward drug-drug interactions. This research is critical to target appropriate prevention and treatment programs to optimize health outcomes for this population. To fill this gap, specific aims are to: (1) Assess the associations between HIV infection and a) adverse health outcomes (e.g. falls/fractures, dementia, mortality) and b) health care utilization (e.g. emergency department use, inpatient hospitalizations, and outpatient visits) among older adults, and estimate the interaction between HIV infection and high-risk prescription opioid use on adverse outcomes and utilization; (2) Among older PLWH, estimate drug-drug interactions between high-risk prescription opioid use and specific antiretroviral drug classes or sedatives (e.g. benzodiazepines) on risk of adverse health outcomes and health care utilization; and (3) Examine the feasibility of applying existing machine learning approaches to predict adverse health outcomes and high health care utilization among older PLWH based on patient profiles and opioid prescription patterns in a large administrative claims database. Findings from this project will generate valuable new information and tools to support clinical decisions and more precisely target prevention and treatment interventions to improve health for older PLWH who are prescribed opioids, and directly inform an R01 application to study drug-drug and drug- disease interactions between widely used prescription drugs and common comorbidities among older PLWH.

项目概要 指导研究科学家发展奖（K01）的目的是为我提供支持 成为一名独立研究者，在艾滋病毒的交叉领域开展多学科研究项目 处方药使用、合并症和老龄化 在这个项目中，我建议利用现有的行政管理。 2007 年至 2018 年 65 岁以上 Medicare 受益人的索赔数据，以确定高风险处方的情况 阿片类药物的使用，例如高剂量使用（≥120 毫克/天）或长时间使用（≥90 天）会影响健康结果和健康 建立在我在艾滋病毒流行病学方面的坚实基础上。 以及整个生命周期的艾滋病毒合并症，本次 K01 的培训将使我能够 (1) 熟练掌握 分析大规模、纵向的行政索赔数据；(2) 获得处方药的内容专业知识 研究利用和药物流行病学；(3) 发展机器学习应用方面的专业知识 我的职业发展计划包括具体的课程、研讨会、会议、定向阅读、 由行政索赔数据专家组成的多学科团队提供量身定制的指导， 物质使用流行病学、药物流行病学和机器学习方法。 为完成本次培训提供了一个特殊的环境，并提供了研究支持和基础设施 分析大型、多年的数据集（包括医疗保险索赔）并进行高影响力的艾滋病毒研究。 鉴于对处方阿片类药物如何使用的理解存在很大差距，拟议的研究具有重要意义 影响着越来越多的老年感染者，他们通常患有慢性疼痛，并有多种合并症， 日益增加的多重用药，以及药物之间不良相互作用的风险增加，这项研究至关重要。 制定适当的预防和治疗计划，以优化该人群的健康结果。 差距，具体目标是： (1) 评估 HIV 感染与 a) 不良健康结果之间的关联 （例如跌倒/骨折、痴呆、死亡）和 b) 医疗保健利用（例如急诊室使用、住院 住院和门诊），并估计艾滋病毒感染之间的相互作用 以及高风险处方阿片类药物使用对不良后果和利用的影响 (2) 在老年 PLWH 中，估计； 高风险处方阿片类药物使用与特定抗逆转录病毒药物类别之间的药物相互作用，或 镇静剂（例如苯二氮卓类药物）对不良健康结果和医疗保健利用的风险；以及 (3) 检查 应用现有机器学习方法来预测不良健康结果和高风险的可行性 基于患者概况和阿片类药物处方模式的老年 PLWH 的医疗保健利用率 该项目的调查结果将产生有价值的新信息和工具 支持临床决策并更准确地瞄准预防和治疗干预措施，以改善健康状况 服用阿片类药物的老年 PLWH，并直接告知 R01 申请以研究药物-药物和药物- 广泛使用的处方药与老年 PLWH 中常见合并症之间的疾病相互作用。

项目成果

Epigenetic Aging Biomarkers Associated With Cognitive Impairment in Older African American Adults With Human Immunodeficiency Virus (HIV).

表观遗传衰老生物标志物与感染人类免疫缺陷病毒 (HIV) 的老年非洲裔美国人认知障碍相关。

• 发表时间: 2021-12-06
• 作者: Shiau, Stephanie;Arpadi, Stephen M;Shen, Yanhan;Cantos, Anyelina;Ramon, Christian Vivar;Shah, Jayesh;Jang, Grace;Manly, Jennifer J;Brickman, Adam M;Baccarelli, Andrea A;Yin, Michael T
• 通讯作者: Yin, Michael T

Characterizing blood pressure trajectories in people living with HIV following antiretroviral therapy: A systematic review.

抗逆转录病毒治疗后艾滋病毒感染者的血压轨迹特征：系统评价。

• 发表时间: 2023-11
• 影响因子: 3
• 作者: Drago, Fabrizio;Soshnik;Cabling, Mark L;Pattarabanjird, Tanyaporn;Desderius, Bernard;Nyanza, Elias;Raymond, Henry;McNamara, Coleen A;Peck, Robert N;Shiau, Stephanie
• 通讯作者: Shiau, Stephanie

Unique Profile of Inflammation and Immune Activation in Pregnant People With HIV in the United States.

美国艾滋病毒孕妇炎症和免疫激活的独特概况。

• 发表时间: 2023-03-01
• 作者: Shiau, Stephanie;Jacobson, Denise L;Huo, Yanling;Kacanek, Deborah;Yee, Lynn M;Williams, David B;Haddad, Lisa B;Serghides, Lena;Powis, Kathleen;Sperling, Rhoda S;Williams, Paige L;Jao, Jennifer;Pediatric HIV/AIDS Cohort Study
• 通讯作者: Pediatric HIV/AIDS Cohort Study