Understanding the Impact of Opioid Policies on the Opioid Epidemic Using Graphical Causal Models and Causal Discovery

使用图形因果模型和因果发现了解阿片类药物政策对阿片类药物流行的影响

• 批准号: 9975979
• 负责人: Hawre Jalal
• 金额: $ 18万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9975979
• 关键词: Address; Adopted; Age; Alcohol or Other Drugs use; Algorithms; Area; Award; Biological Models; Centers for Disease Control and Prevention (U.S.); Chronic; Clinical; Complement; Complex; Data; Decision Aid; Development; Development Plans; Drug usage; Epidemic; Epidemiology; Evaluation; Feedback; Foundations; Funding; Gender; Geography; Goals; HIV; Health; Health Policy; Health Services; Health Services Research; Hepatitis; K-Series Research Career Programs; Knowledge; Learning; Marijuana; Mathematical Model Simulation; Mentors; Mentorship; Methodology; Methods; Modeling; Modernization; Naloxone; National Institute of Drug Abuse; Opioid; Outcome; Overdose; Pain; Paper; Pharmaceutical Preparations; Policies; Policy Maker; Policy Research; Productivity; Public Health; Public Health Schools; Quality of life; Race; Research; Research Personnel; Research Priority; Risk; Scholarship; Science; Scientist; Shapes; Source; Strategic Planning; Subgroup; Substance Use Disorder; System; Time; Training; Translating; United States; Universities; Variant; Work; base; biomedical informatics; career; career development; causal model; disorder prevention; health management; illicit opioid; innovation; longitudinal dataset; marijuana legalization; mathematical methods; models and simulation; mortality; opioid epidemic; opioid mortality; opioid overdose; opioid policy; opioid use disorder; overdose death; policy implication; prescription drug abuse; prescription monitoring program; prescription opioid; professor; programs; sex; success; tool

ABSTRACT This NIDA Mentored Research Scientist Career Development Award (K01) for Dr. Hawre Jalal, an Assistant Professor of Health Policy and Management at the University of Pittsburgh Graduate School of Public Health, will establish Dr. Jalal as a health decision scientist with expertise in the impact of opioid- related policies using advanced methods in causal analyses. The opioid epidemic is a modern public health crisis responsible for reduced quality of life, decreased productivity, and increased risk of chronic conditions and mortality. State opioid policies may have shaped the outcome of the epidemic by benefiting some groups while having unintended consequences on other groups, such as the impact of limiting opioid prescribing to treat legitimate pain. However, most prior studies of these policies have been limited by (1) focusing on a single policy at a time, (2) ignoring the time it may take for a policy to be implemented and effective, and (3) treating the policies as binary variables (yes/no) even though policies vary widely across states. The research proposed in this award focuses on rigorously evaluating the benefits and the unintended consequences of state-opioid policies, such as prescription drug monitoring programs, on important outcomes, such as opioid-related overdose deaths. We propose (1) to use state-of-the-art causal models and causal discovery algorithms to systematically search for causal influences of policy components on the observed outcomes of opioid use disorder (Aim 1), (2) to identify policy combinations that likely increase benefits and reduce harms (Aim 2), and (3) to reveal priority research areas in the policy space by conducting formal value of information (VOI) analysis (Aim 3). The scientific premise for this proposal is strong. Evaluation of opioid policies are one of the top priorities for the NIDA 2016-2020 strategic plan. This project draws on Dr. Jalal’s extensive quantitative training, and knowledge of the epidemiology of the opioid use disorder and overdose deaths. This work will extend Dr. Jalal’s scholarship into the field of policy evaluation while incorporating advanced methods of causal discovery from observational data in health services research. Dr. Jalal will thus engage in training and career development activities that focus on acquiring expertise in causal modeling and in the interpretation and assessment of licit and illicit opioid-related policies. Through mentorship from bioinformaticians, health decision scientists and policy and clinical experts, Dr. Jalal will also focus on applying training in these content areas to health policy research. This training plan complements the proposed research and will equip Dr. Jalal to establish an independent research program examining the broader impact of the various policies on outcomes, such as HIV and hepatitis.

抽象的 NIDA指导了研究科学家职业发展奖（K01） 匹兹堡大学卫生政策与管理助理教授 公共卫生将建立Jalal博士为健康决策科学家 在因果分析中使用高级方法的相关策略。 阿片类药物流行是一种现代公共卫生危机，导致生活质量降低， 国家阿片类药物政策 可能通过使某些群体受益的同时使某些群体受益，从而塑造了流行病的结果 对其他群体的后果，例如限制阿片类药物处方以治疗合法的影响 疼痛。但是，大多数对这些政策的先前研究都受到（1）关注单一政策的限制 一次，（2）忽略实施策略可能需要的时间，以及（3）治疗 即使在各州之间的策略差异很大，政策也作为二进制变量（是/否）。 该奖项提出的研究重点是严格评估收益和 国家阿片类药物政策的意外后果，例如处方药监测计划， 重要的结果，例如阿片类药物相关的过量死亡。我们建议（1）使用最先进的 因果模型和因果发现算法系统地搜索政策的因果影响 观察到的阿片类药物使用障碍结果的组成部分（目标1），（2）确定政策 可能增加收益并减少危害的组合（目标2），以及（3）揭示优先研究 通过进行正式信息（VOI）分析（AIM 3）来进行政策空间中的领域。 该提议的科学前提很强。阿片类药物政策的评估是最重要的 NIDA 2016-2020战略计划的优先事项。该项目借鉴了贾拉尔博士的广泛定量 训练以及对阿片类药物使用障碍和过量死亡的流行病学知识。这项工作 将贾拉尔博士的科学扩展到政策评估领域，同时纳入高级 卫生服务研究中观察数据的因果发现方法。因此，贾拉尔博士将 从事培训和职业发展活动，专注于促进催化专业知识 建模以及与阿片类药物相关政策的解释和评估。通过 生物信息学家，健康决策科学家和政策以及临床专家的遗产，贾拉尔博士 还将着重于将这些内容领域的培训应用于卫生政策研究。这个培训计划 完成拟议的研究，并将装备Jalal博士建立独立研究 计划研究各种政策对艾滋病毒和肝炎等结果的更广泛影响。