Health Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University, Health Sciences Centre, 1280 Main Street West, Hamilton, Ontario, Canada.
Implement Sci. 2010 Feb 5;5:12. doi: 10.1186/1748-5908-5-12.
Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit.
The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system.
Data will be summarized using descriptive summary measures, including proportions for categorical variables and means for continuous variables. Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates. When reporting results from individual studies, we will cite the measures of association and p-values reported in the studies. If appropriate for groups of studies with similar features, we will conduct meta-analyses.
A decision-maker-researcher partnership provides a model for systematic reviews that may foster knowledge translation and uptake.
计算机临床决策支持系统是一种基于信息技术的系统，旨在改善临床决策。与任何声称可以改善护理过程或患者结局的医疗干预措施一样，决策支持系统在广泛应用于临床实践之前，应进行严格评估。让医疗保健提供者和管理者参与审查过程可以促进知识转化和应用。本研究的目的是建立一个医疗保健提供者、管理者和研究人员的合作伙伴关系，以审查评估计算机化决策支持对六个临床应用领域（初级预防保健、治疗药物监测和剂量、药物处方、慢性病管理、诊断测试订购和解释以及急性护理管理）影响的随机对照试验，并确定预测获益的研究特征。
该研究由麦克马斯特大学健康信息研究小组与汉密尔顿健康科学中心、汉密尔顿、尼亚加拉、哈尔迪曼德和布兰特地方卫生集成网络以及相关医疗服务团队合作进行。在与决策者就信息需求和利益达成一致后，我们根据决策者的意见扩展了先前的系统综述，检索了 Medline、EMBASE、EBM Review 数据库和 Inspec，并在 2010 年 1 月 6 日之前审查了参考文献列表。根据决策者的意见扩展了数据提取项目。联系了主要研究的作者以确认数据并提供更多信息。将符合条件的试验根据临床应用领域进行分类。我们纳入了评估计算机化临床决策支持系统提供的患者护理与没有这种系统的患者护理相比对医生绩效或患者结局影响的随机对照试验。
将使用描述性汇总措施（包括分类变量的比例和连续变量的平均值）汇总数据。将使用单变量和多变量逻辑回归模型来研究与感兴趣的结局相关的研究特定协变量之间的关联。在报告单个研究的结果时，我们将引用研究报告的关联测量和 p 值。如果具有相似特征的研究组合适，我们将进行荟萃分析。
决策者-研究人员的伙伴关系为系统综述提供了一种模式，可能促进知识转化和应用。
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