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: 10186725
• 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 2022-01-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10186725
• 关键词: Address; Adopted; Age; 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; substance use; 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.

摘要 这项NIDA指导研究科学家职业发展奖(K01)授予霍尔·贾拉尔博士 匹兹堡大学研究生院卫生政策和管理学助理教授 公共卫生，将使贾拉尔博士成为一名健康决策科学家，拥有阿片类药物影响方面的专业知识- 在因果分析中使用先进的方法进行相关政策。 阿片类药物的流行是一种现代公共卫生危机，导致生活质量下降， 生产力下降，慢性病和死亡率增加。国家阿片类药物政策 可能通过造福于一些群体而塑造了疫情的结果，同时意外地 对其他群体的后果，如限制阿片类药物处方治疗合法的影响 疼痛。然而，以前对这些政策的大多数研究都受到以下限制：(1)专注于单一的政策 一次，(2)忽略政策实施和生效可能需要的时间，以及(3)处理 这些政策是二元变量(是/否)，即使各州的政策差别很大。 该奖项中提出的研究重点是严格评估 国家阿片类药物政策的意外后果，如处方药监测方案， 重要结果，例如与阿片类药物有关的过量死亡。我们建议(1)使用最先进的 系统搜索政策因果影响的因果模型和因果发现算法 关于阿片类药物使用障碍观察结果的组成部分(目标1)，(2)确定政策 可能增加收益和减少危害的组合(目标2)，以及(3)揭示优先研究 通过进行正式的信息价值(VOI)分析(目标3)，确定政策空间中的各个领域。 这一提议的科学前提是强有力的。对阿片类药物政策的评估是排名靠前的 NIDA 2016-2020年战略计划的优先事项。这个项目利用了贾拉尔博士广泛的量化 培训，了解阿片类药物使用障碍和过量死亡的流行病学知识。这部作品 将把贾拉尔博士的奖学金扩展到政策评估领域，同时将先进的 卫生服务研究中从观测数据中发现原因的方法。贾拉尔博士将因此 参与培训和职业发展活动，重点是获得因果关系方面的专业知识 对合法和非法的阿片类药物相关政策进行建模、解释和评估。穿过 来自生物信息学家、健康决策科学家以及政策和临床专家的指导，Jalal博士 还将重点将这些内容领域的培训应用于卫生政策研究。这项培训计划 补充了拟议的研究，并将使贾拉尔博士能够建立一项独立的研究 审查各种政策对结果的更广泛影响的计划，如艾滋病毒和肝炎。

项目成果

Data Needs in Opioid Systems Modeling: Challenges and Future Directions.

• DOI: 10.1016/j.amepre.2020.08.017
• 发表时间: 2021-03
• 期刊: American journal of preventive medicine
• 影响因子: 5.5
• 作者: Jalali MS;Ewing E;Bannister CB;Glos L;Eggers S;Lim TY;Stringfellow E;Stafford CA;Pacula RL;Jalal H;Kazemi-Tabriz R
• 通讯作者: Kazemi-Tabriz R

A Tutorial on Time-Dependent Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.

• DOI: 10.1177/0272989x221121747
• 发表时间: 2023-01
• 期刊: MEDICAL DECISION MAKING
• 影响因子: 3.6
• 作者: Alarid-Escudero, Fernando;Krijkamp, Eline;Enns, Eva A.;Yang, Alan;Hunink, M. G. Myriam;Pechlivanoglou, Petros;Jalal, Hawre
• 通讯作者: Jalal, Hawre

Reply commentary by Jalal and Burke.

回复贾拉尔和伯克的评论。

• DOI: 10.1016/j.drugpo.2022.103674
• 发表时间: 2022
• 期刊: The International journal on drug policy
• 作者: Burke,DonaldS;Jalal,Hawre
• 通讯作者: Jalal,Hawre

An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.

• DOI: 10.1177/0272989x221103163
• 发表时间: 2023-01
• 期刊: MEDICAL DECISION MAKING
• 影响因子: 3.6
• 作者: Alarid-Escudero, Fernando;Krijkamp, Eline;Enns, Eva A.;Yang, Alan;Hunink, M. G. Myriam;Pechlivanoglou, Petros;Jalal, Hawre
• 通讯作者: Jalal, Hawre

Carfentanil and the rise and fall of overdose deaths in the United States.

• DOI: 10.1111/add.15260
• 发表时间: 2021-06
• 期刊: Addiction (Abingdon, England)
• 作者: Jalal H;Burke DS
• 通讯作者: Burke DS