The Texas Medication Algorithm Project: Report of the Texas Consensus Conference Panel on medication treatment of major depressive disorder
The Texas Medication Algorithm Project: Report of the Texas Consensus Conference Panel on medication treatment of major depressive disorder
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DOI：
10.4088/jcp.v60n0302
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发表时间：
1999-03-01
影响因子：
5.3
通讯作者：
Thase, ME
中科院分区：
文献类型：
--
作者：
Crismon, ML;Trivedi, M;Thase, ME
背景：本文描述了德克萨斯州公共精神卫生系统中用于治疗严重抑郁障碍患者的共识用药算法的发展。据我们所知，德克萨斯药物算法项目(TMAP)是第一次尝试开发和前瞻性评估基于共识的药物算法，用于治疗患有严重和持续性精神疾病的个人。该算法项目的目标是增加对重度抑郁障碍患者适当治疗的一致性，并改善患者的临床结果。方法：召开由学术临床医生和研究人员、执业临床医生、管理者、消费者和家庭组成的共识会议，为德克萨斯州精神卫生系统中重度抑郁障碍的药物治疗开发基于证据的共识算法。经过一系列的陈述和小组讨论，共识小组开会并起草了算法，结果：小组一致同意为巴斯非精神病和精神病性抑郁症开发的算法。算法包括确定适当治疗干预措施的系统策略和确保策略最佳实施的策略，在协商一致的过程之后，算法被进一步修改和迭代扩展以便于在本地实施。结论：这些算法是开发和实施针对公共精神卫生系统中接受治疗的患者的药物治疗算法的初始基础。与药物治疗算法的适应、实施、可行性测试和结果评估相关的具体问题将在未来的文章中描述。
Background: This article describes the development of consensus medication algorithms for the treatment of patients with major depressive disorder in the Texas public mental health system. To the best of our knowledge, the Texas Medication Algorithm Project (TMAP) is the first attempt to develop and prospectively evaluate consensus-based medication algorithms for the treatment of individuals with severe and persistent mental illnesses. The goals of the algorithm project are to increase the consistency of appropriate treatment of major depressive disorder and to improve clinical outcomes of patients with the disorder.Method: A consensus conference composed of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families was convened to develop evidence-based consensus algorithms for the pharmacotherapy of major depressive disorder in the Texas mental health system. After a series of presentations and panel discussions, the consensus panel met and drafted the algorithms,Results: The panel consensually agreed on algorithms developed for bath nonpsychotic and psychotic depression. The algorithms consist of systematic strategies to define appropriate treatment interventions and tactics to assure optimal implementation of the strategies, Subsequent to the consensus process, the algorithms were further modified and expanded iteratively to facilitate implementation on a local basis.Conclusion: These algorithms serve as the initial foundation for the development and implementation of medication treatment algorithms for patients treated in public mental health systems. Specific issues related to adaptation, implementation, feasibility testing, and evaluation of outcomes with the pharmacotherapeutic algorithms will be described in future articles.