Real-world complexities in opioid use disorder treatment: understanding family comorbidity, high-risk medication use, and costs related to treatment adherence and health outcomes

阿片类药物使用障碍治疗的现实复杂性：了解家庭合并症、高风险药物使用以及与治疗依从性和健康结果相关的成本

• 批准号: 10449784
• 负责人: Marissa J Seamans
• 金额: $ 18.29万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10449784
• 关键词: Address; Adherence; Adverse event; American; Anxiety; Benzodiazepines; Buprenorphine; Child; Clinical; Clinical assessments; Data; Data Analyses; Databases; Development; Drug Prescriptions; Educational workshop; Emergency department visit; Environmental Risk Factor; Family; Family health status; Family member; Foundations; Genetic; Goals; Health; Health Benefit; Health Care Costs; Health Insurance; Health Insurance Reimbursement; Health Services Research; Health Status; Healthcare; Hospitalization; Household; Improve Access; Incidence; Individual; Insurance Carriers; Intervention; Knowledge; Learning; Life; Medicine; Mental Depression; Mental Health; Mental disorders; Mentored Research Scientist Development Award; Mentors; Mentorship; Methods; Muscle relaxants; Opiate Addiction; Opioid; Outcome; Overdose; Pain; Parents; Patient-Focused Outcomes; Patients; Personal Satisfaction; Persons; Pharmaceutical Preparations; Pharmacoepidemiology; Pharmacotherapy; Play; Policies; Psychiatry; Public Health; Publishing; Recording of previous events; Research; Research Personnel; Risk; Risk Factors; Role; Savings; Serious Adverse Event; Siblings; Spouses; Stimulant; Substance Use Disorder; Time; Training; addiction; adverse outcome; alcohol use disorder; beneficiary; buprenorphine treatment; career; chronic depression; chronic pain; clinical decision support; clinical diagnosis; clinical practice; clinically relevant; comorbidity; contextual factors; cost; data warehouse; design; drug misuse; economic evaluation; health care service utilization; health plan; high risk; improved; indexing; innovation; insight; insurance claims; medication compliance; meetings; opioid overdose; opioid use; opioid use disorder; predictive modeling; psychosocial; responsible research conduct; sedative; skills; substance use treatment; support tools; treatment adherence

PROJECT SUMMARY Medications for opioid use disorder (MOUD) have the potential to improve the health and well-being of more than 2.1 million Americans with OUD, however, long-term adherence particularly to buprenorphine is alarmingly poor. Pain, mental health, and substance use disorders are increasingly recognized as risk factors for inadequate treatment adherence and often co-occur in families due to shared genetic and environmental factors. Understanding comorbidities in patients with OUD and their family members, and the impact of these comorbidities on poor opioid use outcomes, can help identify patients at risk for inadequate treatment adherence and serious adverse events. Further, information on the costs associated with buprenorphine non-adherence and family comorbidities can inform health insurance reimbursement policies. The overall career goal of the recipient is to become a leading pharmacoepidemiologist focused on improving treatment for substance use disorders, particularly opioid use disorders. The goal of this K01 is to train the recipient to investigate associations between family comorbidities and/or prescription medications with a high risk of misuse and buprenorphine treatment adherence, opioid use outcomes, and costs to the family unit and health insurer. Research aims of this project are to: (1) develop a clinically relevant prediction model to identify patients prescribed buprenorphine at risk of inadequate adherence; (2) determine whether other prescriptions in the family are associated with poor buprenorphine adherence and opioid-related adverse events; and (3) compare overall healthcare costs to the family and health insurer across varying levels of buprenorphine adherence. The training aims of this project are to: (1) gain understanding of the clinical assessment and diagnosis of opioid use disorders and comorbid mental health conditions; (2) learn and apply innovative methods for dyadic data analyses; (3) learn and apply methods for conducting economic evaluations of substance use treatment; (4) hone professional skills in research, publishing, and project administration; and (5) responsible conduct of research. Training aims will be pursued through tutorials with world-renowned experts forming the recipient's mentorship team, graduate-level coursework, workshops and seminars, participation in scientific meetings, and mentored research. Research aims will be accomplished using the OptumLabs Data Warehouse, a large integrated commercial healthcare insurance claims database that tracks beneficiaries, spouses, and dependents across health plans and over time. This project will fill an important gap in our understanding of how family comorbidities and medication use by family members influence MOUD treatment adherence, outcomes, and costs, and will provide evidence to support interventions by clinicians and health insurers to improve MOUD adherence outcomes.

项目摘要 阿片类药物使用障碍（MOUD）有可能改善更多人的健康和福祉。 然而，超过210万患有OUD的美国人，特别是对丁丙诺啡的长期坚持令人担忧 扶贫疼痛、精神健康和物质使用障碍越来越被认为是不充分的危险因素。 治疗依从性，并且由于共同的遗传和环境因素，经常在家庭中共同发生。 了解OUD患者及其家庭成员的合并症及其影响 阿片类药物使用结局不良的合并症，可以帮助识别存在治疗依从性不足风险的患者 和严重不良事件。此外，有关丁丙诺啡不依从相关费用的信息 和家庭合并症可以告知健康保险报销政策。总的职业目标 获奖者将成为专注于改善物质使用治疗的领先药物流行病学家 特别是阿片类药物使用障碍。本K 01的目标是培训接受者调查关联 家族合并症和/或具有高误用风险的处方药与丁丙诺啡之间的关系 治疗依从性、阿片类药物使用结果以及家庭单位和健康保险公司的成本。研究目的 本项目的目的是：（1）开发一个临床相关的预测模型，以确定患者是否处方丁丙诺啡 （2）确定家庭中的其他处方是否与贫困有关; 丁丙诺啡依从性和阿片类药物相关不良事件;以及（3）将总体医疗保健费用与 家庭和健康保险公司在不同程度的丁丙诺啡坚持。该项目的培训目标是 目的：（1）了解阿片类药物使用障碍和共病精神障碍的临床评估和诊断 健康状况;（2）学习和应用二元数据分析的创新方法;（3）学习和应用方法 进行物质使用治疗的经济评估;（4）磨练研究的专业技能， 出版和项目管理;（5）负责任地进行研究。将追求培训目标 通过与世界知名专家组成的导师团队，研究生水平的教程 课程作业、讲习班和研讨会、参加科学会议和指导研究。研究 目标将使用OptumLabs数据仓库来实现，OptumLabs数据仓库是一个大型综合商业医疗保健系统， 一个保险索赔数据库，用于跟踪整个健康计划的受益人、配偶和家属 时间这个项目将填补我们对家庭合并症和药物使用的理解的重要空白 家庭成员影响MOUD治疗依从性，结果和成本，并将提供证据， 支持临床医生和医疗保险公司的干预措施，以改善MOUD依从性结果。