IEEE Rev Biomed Eng. 2019;12:303-318. doi: 10.1109/RBME.2018.2855055. Epub 2018 Jul 11.
In this review, the critical parts and milestones for data harmonization, from the biomedical engineering perspective, are outlined. The need for data sharing between heterogeneous sources paves the way for cohort harmonization; thus, fostering data integration and interdisciplinary research. Unmet needs in chronic diseases, as well as in other diseases, can be addressed based on the integration of patient health records and the sharing of information of the clinical picture and outcome. The stratification of patients, the determination of various clinical and outcome features, and the identification of novel biomarkers for the different phenotypes of the disease characterize the impact of cohort harmonization in patient-centered clinical research and in precision medicine. Subsequently, the establishment of matching techniques and ontologies for the creation of data schemas are also presented. The exploitation of web technologies and data-collection tools supports the opportunities to achieve new levels of integration and interoperability. Ethical and legal issues that arise when sharing and harmonizing individual-level data are discussed in order to evaluate the harmonization potential. Use cases that shape and test the harmonization approach are explicitly analyzed along with their significant results on their research objectives. Finally, future trends and directions are discussed and critically reviewed toward a roadmap in cohort harmonization for clinical medicine.
在这篇综述中，从生物医学工程的角度概述了数据协调的关键部分和里程碑。不同来源之间的数据共享需要促进队列协调，从而促进数据集成和跨学科研究。基于患者健康记录的整合和临床情况及结果信息的共享，可以解决慢性病以及其他疾病的未满足需求。患者分层、确定各种临床和结果特征以及确定疾病不同表型的新型生物标志物，是队列协调对以患者为中心的临床研究和精准医学的影响的特征。随后，还介绍了用于创建数据模式的匹配技术和本体。网络技术和数据收集工具的利用支持实现新的集成和互操作性水平的机会。讨论了在共享和协调个人层面数据时出现的伦理和法律问题，以评估协调的潜力。明确分析了塑造和测试协调方法的用例，以及它们在研究目标方面的重要结果。最后，讨论了未来的趋势和方向，并对临床医学中的队列协调路线图进行了批判性审查。
