POINT OF CARE DELIVERY OF RESEARCH EVIDENCE

研究证据的护理点交付

• 批准号: 6391123
• 负责人: E Andrew Balas
• 金额: $ 51.79万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2002-07-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6391123
• 关键词: education evaluation /planning; educational resource design /development; health care personnel education; health science research analysis /evaluation; health services research tag; information systems; medical education

This is a revision of a grant application originally reviewed in July of 1999. Studies document that it takes an average of nearly two decades for research evidence to reach clinical practice. Relying on the passive diffusion of information to keep health professionals' knowledge up to date is doomed to failure in a global environment in which about two million medical research articles are published annually. The purpose of this revised project is to: (1) develop policies for the automated selection of credible and substantial evidence, and (2) match patient data with clinical evidence and (3) directly deliver high-quality evidence to the point of clinical decision making. The proposed project is a collaboration of researchers from the University of Missouri, Columbia University, and Duke University. Systematic reviews to evaluate eligibility criteria, outcomes variables, and overall quality of published evidence will be conducted. An automated evidence filtering system will be developed and selected randomized clinical trial evidence will be abstracted from the literature. The abstractions will contain eligibility criteria for matching, a recommendation to the clinician, and a suggested notice to the patient. A decision-support system to automatically match the literature with patient data will be created. Based on the abstracted literature evidence, an intelligent web-based agent will search the patient databases for lapses in care. Reminder recommendations and evidence behind them will be sent to the appropriate clinician. Reminder standards will be developed and evaluated with a randomized clinical trial. In addition there will be a subcontract to Duke University which will focus on developing a clinical decision support system that uses structures, electronically stored evidence logic modules (created by the other investigators in this project) to deliver evidence-based advice to clinicians. This decision support system will be evaluated in a randomized controlled trial that assesses the impact of the system on adherence with care standards.

这是对最初在年审查的赠款申请的修订。 1999年7月。 研究表明，平均需要近20年的时间 研究证据用于临床实践。依赖于被动 传播信息，使卫生专业人员的知识保持最新， 注定要失败，在全球环境中，约有200万医疗 研究文章每年出版。 本修订项目的目的 （1）制定自动选择可靠和 实质性证据，以及（2）将患者数据与临床证据相匹配， (3)直接将高质量证据提供给临床决策 制作。拟议的项目是一个合作的研究人员从 密苏里州大学、哥伦比亚大学和杜克大学。系统 审查以评估合格性标准、结局变量和总体 将对发表的证据进行质量检查。一个自动证据 筛选系统将被开发和选择随机临床试验 将从文献中提取证据。抽象将包含 匹配的资格标准、对临床医生的建议，以及 建议通知患者。一个决策支持系统， 将创建与患者数据匹配的文献。基于 抽象的文献证据，一个智能的基于网络的代理将搜索 护理失误的病人数据库。提醒建议和证据 将被发送到适当的临床医生。提醒标准将 通过随机临床试验进行开发和评估。此外， 将是一所以杜克大学为基础的大学， 临床决策支持系统，使用电子存储的结构 证据逻辑模块（由本项目中的其他研究人员创建）， 为临床医生提供循证医学建议。该决策支持系统将 在一项随机对照试验中进行评估， 遵守护理标准的制度。