COMPUTER BASED GUIDELINES TO PREVENT SUDDEN CARDIAC DEAT

指南为改善患者管理提供了一种系统的手段。它们的使用可以提高卫生保健的质量、适当性和有效性，还可以控制成本。然而，指南的最佳制定将包括临床医学、荟萃分析、决策分析、成本效益分析和证据合成方面的专家的投入；这些专家在地方一级往往无法获得，或者费用高得令人望而却步。因此，国家组织经常为具有“平均”特征的人口制定指导方针。这些指南可能需要根据患者群体或实践的特点不同的当地环境进行调整。此外，传统指南通常是静态的，因此可能会随着新信息的出现而过时。为了解决这些问题，我们建议开发人员根据决策模型创建指导方针。这些指南包含必要的知识，允许用户为当地患者或人群定制指南，并随着基本决策模型或证据的演变而随时间修改指南。为了实现这一目标，我们提议的研究有三个具体目标：(1)开发基于证据的决策模型的自动创建指南的方法，使用一个称为炼金师的网络系统，(2)基于心律失常端口的结果创建和评估指南，这是一个为期6年的预防心脏性猝死的方法的多机构研究，以及(3)在随机对照试验中，评估临床医生使用我们开发的基于网络的指南系统与传统指南相比的满意度，以针对一组假设的临床情景提出治疗建议。如果我们成功地完成了我们的特定目标，我们将拥有：(1)演示开发人员可以使用决策模型自动创建指南，(2)使用炼金师系统根据心律失常端口的发现创建基于证据的可定制预防心脏性猝死指南，(3)评估炼金师生成的指南的好处和质量，以及(4)为炼金师指南系统的临床实施的随机试验奠定基础。这些成就将有助于促进AHRQ和NLM的使命，导致形成一种结合证据创建指南的正式方法，并促进这些指南的传播和转化为临床实践。

Guidelines provide a systematic means to improve patient management. Their use can enhance the quality, appropriateness, and effectiveness of health care, and may also contain costs. Optimal development of guidelines, however, would include input from experts in clinical medicine, meta-analyses, decision analyses, cost-effectiveness analyses, and evidence synthesis; such experts often are not available, or are prohibitively costly, on a local level. Therefore, national organizations often develop guidelines for a population that has "average" characteristics. These guidelines may need to be adapted to local settings in which the characteristics of the patient population or practice are different. In addition, traditional guidelines are normally static and thus may become out of date as new information emerges. To address these problems, we propose that developers create guidelines from decision models. These guidelines contain the knowledge necessary to allow users to customize the guidelines to a local patient or population, and to modify the guidelines over time as the underlying decision model or evidence evolves. To achieve this goal, our proposed research has three specific aims: (1) to develop methods for the automated creation of guidelines from evidence-based decision models, using a web-based system called ALCHEMIST, (2) to create and evaluate guidelines based on the findings of the Cardiac Arrhythmia PORT, a 6-year multi-institutional study of methods to prevent sudden cardiac death, and (3) to evaluate, in a randomized controlled trial, clinicians' use of and their satisfaction with our developed web- based guideline system compared with traditional guidelines for making treatment recommendations on a set of hypothetical clinical scenarios. If we successfully complete our specific aims, we will have: (1) demonstrated that developers can use decision models to create guidelines automatically, (2) used the ALCHEMIST system to create an evidence-based customizable guideline for prevention of sudden cardiac death based on the findings of the Cardiac Arrhythmia PORT, (3) evaluated the benefits and quality of the ALCHEMIST- generated guidelines, and (4) laid the groundwork for a randomized trial of clinical implementation of the ALCHEMIST guideline system. These achievements will help further the missions of the AHRQ and the NLM by leading toward a formalized method for combining evidence to create guidelines, and facilitating dissemination and translation of these guidelines into clinical practice.