Systems Approach to Modeling of Drug Use Recovery

描述(由申请人提供)：这项初步研究将建立一个以药剂为基础的模型，在与当前治疗做法、以康复为导向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回收轨迹。海洛因成瘾的治疗与复发、重新接受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，它在药理上是有效的，但由于影响海洛因复吸的组织、社区和政策因素的复杂相互作用，它并不总是最有效的，因此无法防止许多吸毒者复发。到目前为止，一些研究已经收集了有关海洛因成瘾恢复轨迹的信息；然而，还没有开发出将影响因素纳入一个模型的模型，将它们视为系统的一部分。拟议的工作是解决海洛因回收问题的第一个系统建模方法，包括背景因素的影响。因此，拟议模式的制定同时考虑到海洛因成瘾治疗战略的特点(例如，住院式与门诊式)和使用者的背景环境(例如，社会网络、非法药物市场)，以更恰当地评估促进康复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栗子健康系统的主要专家确定的海洛因使用轨迹的经过充分研究的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可能导致康复周期的质的(例如，停止)而不是简单的数量(例如，延迟复发)的变化。具体地说，我们的目标是(1)开发一个基于药物的海洛因使用和回收过程模型，该模型将描述影响戒毒成功的主要系统组件，(2)通过模拟实验，评估旨在提高治疗有效性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，并评估该模型对其他药物治疗的普适性。

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.