Etheredge Lynn M
Lynn M. Etheredge (
Health Aff (Millwood). 2014 Jul;33(7):1155-62. doi: 10.1377/hlthaff.2014.0043.
A "rapid-learning health system" was proposed in a 2007 thematic issue of Health Affairs. The system was envisioned as one that uses evidence-based medicine to quickly determine the best possible treatments for patients. It does so by drawing on electronic health records and the power of big data to access large volumes of information from a variety of sources at high speed. The foundation for a rapid-learning health system was laid during 2007-13 by workshops, policy papers, large public investments in databases and research programs, and developing learning systems. Challenges now include implementing a new clinical research system with several hundred million patients, modernizing clinical trials and registries, devising and funding research on national priorities, and analyzing genetic and other factors that influence diseases and responses to treatment. Next steps also should aim to improve comparative effectiveness research; build on investments in health information technology to standardize handling of genetic information and support information exchange through apps and software modules; and develop new tools, data, and information for clinical decision support. Further advances will require commitment, leadership, and public-private and global collaboration.
2007年《健康事务》的一期专题中提出了“快速学习型健康系统”。该系统被设想为一个利用循证医学来快速确定针对患者的最佳治疗方案的系统。它通过利用电子健康记录和大数据的力量，高速从各种来源获取大量信息来做到这一点。2007年至2013年期间，通过研讨会、政策文件、对数据库和研究项目的大量公共投资以及开发学习系统，奠定了快速学习型健康系统的基础。目前面临的挑战包括实施一个涵盖数亿患者的新临床研究系统、使临床试验和登记现代化、设计并资助关于国家优先事项的研究，以及分析影响疾病和治疗反应的基因及其他因素。后续步骤还应旨在改进比较效果研究；基于对健康信息技术的投资，规范遗传信息的处理，并通过应用程序和软件模块支持信息交换；以及开发用于临床决策支持的新工具、数据和信息。进一步的进展将需要承诺、领导力以及公私合作和全球合作。
