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德克萨斯药物治疗算法项目:德克萨斯关于重度抑郁症药物治疗共识会议小组报告

The Texas Medication Algorithm Project: report of the Texas Consensus Conference Panel on Medication Treatment of Major Depressive Disorder.

作者信息

Crismon M L, Trivedi M, Pigott T A, Rush A J, Hirschfeld R M, Kahn D A, DeBattista C, Nelson J C, Nierenberg A A, Sackeim H A, Thase M E

机构信息

College of Pharmacy, University of Texas at Austin, 78712, USA.

出版信息

J Clin Psychiatry. 1999 Mar;60(3):142-56.

Abstract

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 both 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.

摘要

背景

本文介绍了得克萨斯州公共精神卫生系统中用于治疗重度抑郁症患者的共识药物治疗算法的开发情况。据我们所知,得克萨斯州药物算法项目(TMAP)是首次尝试开发并前瞻性评估基于共识的药物治疗算法,用于治疗严重和持续性精神疾病患者。该算法项目的目标是提高重度抑郁症适当治疗的一致性,并改善该疾病患者的临床结局。

方法

召开了一次由学术临床医生和研究人员、执业临床医生、管理人员、消费者及家属组成的共识会议,以制定得克萨斯州精神卫生系统中重度抑郁症药物治疗的循证共识算法。经过一系列报告和小组讨论后,共识小组开会并起草了这些算法。

结果

该小组就为非精神病性抑郁症和精神病性抑郁症制定的算法达成了共识。这些算法包括定义适当治疗干预措施的系统策略以及确保策略最佳实施的策略。在达成共识过程之后,这些算法经过反复修改和扩展,以促进在当地的实施。

结论

这些算法为公共精神卫生系统中患者药物治疗算法的开发和实施奠定了初步基础。未来的文章将描述与药物治疗算法的适应性、实施、可行性测试及结果评估相关的具体问题。

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