Over the last decades clinical research has been driven by informatics changes nourished by distinct research endeavors. Inherent to this evolution, several issues have been the focus of a variety of studies: multi-location patient data access, interoperability between terminological and classification systems and clinical practice and records harmonization. Having these problems in mind, the Data Safe Haven paradigm emerged to promote a newborn architecture, better reasoning and safe and easy access to distinct Clinical Data Repositories. This study aim is to present a novel solution for clinical search harmonization within a safe environment, making use of a hybrid coding taxonomy that enables researchers to collect information from multiple repositories based on a clinical domain query definition. Results show that is possible to query multiple repositories using a single query definition based on clinical domains and the capabilities of the Unified Medical Language System, although it leads to deterioration of the framework response times. Participants of a Focus Group and a System Usability Scale questionnaire rated the framework with a median value of 72.5, indicating the hybrid coding taxonomy could be enriched with additional metadata to further improve the refinement of the results and enable the possibility of using this system as data quality tagging mechanism.

在过去的几十年中，临床研究一直受到信息学变化的推动，而信息学变化是由独特的研究成果所滋养的。在这种发展过程中，固有的几个问题一直是各种研究的重点：多位置患者数据访问，术语和分类系统与临床实践和记录协调之间的互操作性。考虑到这些问题后，出现了“数据安全港”范式，以促进新生体系结构，更好的推理以及安全，便捷地访问不同的临床数据存储库。这项研究的目的是提供一种新的解决方案，用于在安全环境中协调临床搜索，利用混合编码分类法，使研究人员能够基于临床域查询定义从多个存储库收集信息。结果表明，可以使用基于临床领域和统一医学语言系统功能的单个查询定义来查询多个存储库，尽管这会导致框架响应时间缩短。焦点组和系统可用性量表调查问卷的参与者对该框架进行了评分，中位数为72.5，表明可以用其他元数据来丰富混合编码分类法，以进一步改善结果的细化程度，并有可能将该系统用作数据质量标记机制。