Critical Care Informatics

摘要 重症监护病房是医院内一些最复杂的病人技术的所在地。结果- 收集数据有可能提高我们对疾病的理解，改善临床护理。危重 患者是临床数据库研究的理想人群，因为许多治疗的价值和 他们接受的干预措施在很大程度上尚未得到证实，高质量的研究支持或阻止了特定的干预措施。 实践相对较少[4]。目前使用的标准化重症监护指南依赖于 考虑到ICU中生成的数据量，证据基础出奇地薄弱[13]。 麻省理工学院计算生理学实验室（LCP）开发并维护了 重症监护医学信息市场（MIMIC），包含与53，423相关的高度详细的数据 波士顿贝斯以色列女执事医疗中心的不同成人ICU入院[21]。MIMIC现在是 在全球范围内广泛使用的资源，用于临床研究、探索性和验证分析， 制药和医疗技术公司，以及大学，会议和在线课程， 教程和讲习班。 LCP最近与Philips合作发布了开放式eICU协作研究数据库[24] 医疗保健，包括与约200，000例重症监护入院相关的去识别艾德临床数据 全美两百多家医院我们现在打算扩大我们的成功， 开放获取，开源的方法，通过发布大型新的术中，紧急 部门和成像数据集。重要的是，我们与全球联盟取得了令人兴奋的进展， 该小组正带头开发高分辨率重症监护数据库。在我们的帮助下， 牛津、伦敦、巴黎、圣保罗、马德里和北京的同事们在建立 他们自己的MIMIC版本，并将其转换为OMOP公共数据模型。 多中心研究具有挑战性，因为不同的机构收集和存储数据（有时是dras- 不同的格式。采用和统一数据标准是一项关键要求， 数据要妥善存档，跨机构整合，并共享以供重复使用。 该提案寻求资金：（a）支持和扩大我们的公共可用重症监护数据资源， 新领域，包括艾德和OR中的ICU前护理，以及连续胸部X射线成像; B）开发技术 整合来自国际重症监护病房的数据所需的基础设施;以及c）开展研究， 理解和解决在开发中使用多中心和联合数据集的复杂性 预测和临床决策支持工具，以及观察性回顾性研究。

Abstract Critical care units are home to some of the most sophisticated patient technology within hospitals. The result- ing data have the potential to improve our understanding of disease and to improve clinical care. Critically ill patients are an ideal population for clinical database investigations because the value of many treatments and interventions they receive remains largely unproven, and high-quality studies supporting or discouraging specific practices are relatively sparse [4]. Standardized critical care guidelines currently in use are dependent on an evidence base that is surprisingly weak considering the amount of data generated in the ICU [13]. The MIT Laboratory for Computational Physiology (LCP) developed and maintains the publicly available Medical Information Mart for Intensive Care (MIMIC), containing highly detailed data associated with 53,423 distinct adult ICU admissions at the Beth Israel Deaconess Medical Center in Boston [21]. MIMIC is now a widely used resource worldwide for clinical research studies, exploratory and validation analyses performed by pharmaceutical and medical technology companies, as well as for university, conference and online courses, tutorials and workshops. LCP recently released the open eICU Collaborative Research Database [24] in collaboration with Philips Healthcare, comprising de-identified clinical data associated with approximately 200,000 critical care admissions to over two hundred hospitals throughout the United States. We now intend to expand the success of our open-access, open-source approach to critical care research by releasing large new intra-operative, emergency department and imaging datasets. Importantly, we have made exciting progress with the global consortium our group is spearheading around the development of high resolution critical care databases. With our assistance, colleagues at Oxford, London, Paris, Sao Paulo, Madrid, and Beijing have made significant progress in building their own versions of MIMIC and transforming them into the OMOP common data model. Multi-center research is challenging, because different institutions collect and store data in (sometimes dras- tically) different formats. The adoption and harmonization of data standards is a critical requirement in order for the data to be properly archived, integrated across institutions, and shared for reuse. This proposal seeks funding to: (a) support and expand our publicly available critical care data resources into new domains including pre-ICU care in the ED and OR, and serial chest X-ray imaging; b) develop the technical infrastructure needed to integrate data from international critical care units; and c) conduct research aimed at understanding and addressing the complexities of using multicenter and federated datasets in the development of predictive and clinical decision support tools, as well as in observational retrospective studies.