Systems Approach to Modeling of Drug Use Recovery

药物使用回收建模的系统方法

• 批准号: 8416409
• 负责人: GEORGIY BOBASHEV
• 金额: $ 24.13万
• 依托单位: RESEARCH TRIANGLE INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-15 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8416409
• 关键词: Accounting; Address; Affect; Alcohols; Attention; Biological Models; Case Management; Characteristics; Chronic; Chronic Disease; Collaborations; Communicable Diseases; Communities; Complex; Continuity of Patient Care; Crack Cocaine; Data Set; Databases; Development; Disease; Drug usage; Environment; Environmental Policy; Goals; Health system; Heroin; Heroin Dependence; Illicit Drugs; Imprisonment; Individual; Influentials; Inpatients; Intervention; Knowledge; Law Enforcement; Lead; Link; Literature; Maintenance Therapy; Marketing; Methadone; Methamphetamine; Modality; Modeling; Monitor; Outcome; Outpatients; Patients; Pattern; Peer Review; Pharmaceutical Preparations; Pilot Projects; Policies; Prevention; Process; Publications; Recovery; Relapse; Research; Research Personnel; Resistance; Services; Simulate; Social Network; Staging; Structure; System; Testing; Treatment Effectiveness; Typology; Work; addiction; base; contextual factors; drug market; experience; methadone maintenance; prevent; research study; success; treatment strategy

DESCRIPTION (provided by applicant): This pilot study will build an agent-based model that will describe heroin use and recovery trajectories in the context of complex interconnections with current treatment practices, recovery-oriented services, and the illicit drug market. Treatment of heroin addiction is associated with a chronic cycle of relapse, treatment reentry, and recovery, often lasting for decades. The most commonly used treatment for heroin addiction is methadone therapy, which is pharmacologically efficient, but due to a complex interaction of organizational, community, and policy factors that affect relapse to heroin use, it is not always optimally effective and is thus unable to prevent relapse in many addicts. To date, a number of studies have collected information about heroin addiction recovery trajectories; however no model has yet been developed to integrate influential factors into one model, considering them as part of a system. The proposed effort represents the first systems modeling approach to address the topic of heroin recovery, including influences from contextual factors. Accordingly, the development of the proposed model simultaneously takes into account characteristics of heroin addiction treatment strategies (e.g., residential vs. outpatient modality) and the user's contextual environment (e.g., social networks, illicit drug markets) to more aptly assess the processes that promote or, conversely, interfere with recovery. Model parameters will be obtained from well studied datasets on heroin use trajectories identified by leading experts from UCLA and Chestnut Health Systems, as well as from other relevant studies. The resulting model will be used to address questions about the optimal combination and staging of treatment approaches and to explore whether some combinations could lead to qualitative (e.g., cessation) rather than simply quantitative (e.g., delayed relapse) changes in recovery cycle. Specifically, we aim to (1) Develop an agent-based model of heroin use and recovery process that would describe the main systems components influencing the success of recovery, (2) Through simulated experiments, evaluate the success of specific complex strategies aimed to increase treatment effectiveness, and (3) Evaluate the feasibility of approaches that show the most promise, address potential resistance to policy strategies, and evaluate generalizability of the model in regard to other drug treatments.

描述（由申请人提供）：这项试点研究将建立一个基于代理的模型，该模型将在与当前治疗实践、面向康复的服务和非法药物市场的复杂相互联系的背景下描述海洛因的使用和康复轨迹。海洛因成瘾的治疗与复发、重新治疗和康复的慢性循环有关，通常持续数十年。海洛因成瘾最常用的治疗方法是美沙酮疗法，其药理学上有效，但由于影响海洛因吸毒复吸的组织、社区和政策因素之间复杂的相互作用，它并不总是最有效的，因此无法防止许多成瘾者复吸。迄今为止，许多研究已经收集了有关海洛因成瘾康复轨迹的信息；然而，尚未开发出将影响因素整合到一个模型中并将其视为系统一部分的模型。拟议的工作代表了第一个解决海洛因回收主题的系统建模方法，包括背景因素的影响。因此，所提出的模型的开发同时考虑了海洛因成瘾治疗策略的特征（例如，住院与门诊模式）和用户的背景环境（例如，社交网络、非法药物市场），以更恰当地评估促进或相反干扰康复的过程。模型参数将从加州大学洛杉矶分校和 Chestnut Health Systems 的领先专家确定的海洛因使用轨迹数据集以及其他相关研究中获得。由此产生的模型将用于解决有关治疗方法的最佳组合和分期的问题，并探索某些组合是否会导致恢复周期的定性（例如，戒烟）而不是简单的定量（例如，延迟复发）变化。具体来说，我们的目标是（1）开发基于代理的海洛因使用和康复过程模型，该模型将描述影响康复成功的主要系统组件，（2）通过模拟实验，评估旨在提高治疗效果的特定复杂策略的成功，以及（3）评估最有希望的方法的可行性，解决对政策策略的潜在阻力，并评估该模型在其他药物治疗方面的普遍性。