Aubry Wade M
University of California, San Francisco.
EGEMS (Wash DC). 2013 Oct 28;1(2):1050. doi: 10.13063/2327-9214.1050. eCollection 2013.
A learning health system is one in which clinical information and research are continually used to improve the processes, outcomes, and quality of care. No matter which definition of comparative effectiveness research (CER) or patient-centered outcomes research (PCOR) is preferred, there is nearly universal agreement that a core feature of these research efforts is the need to engage decision makers, such as patients, providers, and policymakers, in prioritizing and defining research that addresses and resolves important evidence gaps to improve patient care and outcomes. In this set of eGEMs papers focused on decision-making, leaders in scientific fields with an interest in developing the next generation of CER, PCOR, and quality improvement (QI) studies share their perspectives on the potential applications, as well as the short-and longterm challenges, of using electronic clinical data (ECD) to address health care information needs within a learning health system. This commentary introduce eGEMs’ first special issue, which was developed through a series of conversations with leading experts, as well as an open call for papers in early summer 2013. The six papers presented represent a first set of papers on decision makers and decision-making using these new data, with other papers (to follow) being currently under development to add to the perspectives provided here.
学习型健康系统是一种临床信息与研究持续用于改进医疗过程、结果及护理质量的系统。无论比较效果研究(CER)或以患者为中心的结果研究(PCOR)采用哪种定义,几乎普遍达成的共识是,这些研究工作的一个核心特征是需要让决策者(如患者、医疗服务提供者和政策制定者)参与到对研究的优先级确定和定义中,这些研究旨在解决并弥合重要的证据差距,以改善患者护理和结果。在这组聚焦于决策制定的电子生成证据与方法(eGEMs)论文中,对开发下一代CER、PCOR和质量改进(QI)研究感兴趣的科学领域领导者分享了他们对于在学习型健康系统中使用电子临床数据(ECD)来满足医疗保健信息需求的潜在应用以及短期和长期挑战的看法。本评论介绍了eGEMs的首个特刊,该特刊是通过与顶尖专家的一系列对话以及2013年初夏的公开征稿而形成的。所呈现的六篇论文代表了关于使用这些新数据的决策者和决策制定的首批论文集,其他论文(随后)正在撰写中,以补充此处提供的观点。