Berenspöhler Sarah, Minnerup Jens, Dugas Martin, Varghese Julian
Institute of Medical Informatics, Westfälische Wilhelms-University Münster, Münster, Germany.
Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Münster, Germany.
JMIR Med Inform. 2021 Oct 12;9(10):e27396. doi: 10.2196/27396.
Medical information management for stroke patients is currently a very time-consuming endeavor. There are clear guidelines and procedures to treat patients having acute stroke, but it is not known how well these established practices are reflected in patient documentation.
This study compares a variety of documentation processes regarding stroke. The main objective of this work is to provide an overview of the most commonly occurring medical concepts in stroke documentation and identify overlaps between different documentation contexts to allow for the definition of a core data set that could be used in potential data interfaces.
Medical source documentation forms from different documentation contexts, including hospitals, clinical trials, registries, and international standards, regarding stroke treatment followed by rehabilitation were digitized in the operational data model. Each source data element was semantically annotated using the Unified Medical Language System. The concept codes were analyzed for semantic overlaps. A concept was considered common if it appeared in at least two documentation contexts. The resulting common concepts were extended with implementation details, including data types and permissible values based on frequent patterns of source data elements, using an established expert-based and semiautomatic approach.
In total, 3287 data elements were identified, and 1051 of these emerged as unique medical concepts. The 100 most frequent medical concepts cover 9.51% (100/1051) of all concept occurrences in stroke documentation, and the 50 most frequent concepts cover 4.75% (50/1051). A list of common data elements was implemented in different standardized machine-readable formats on a public metadata repository for interoperable reuse.
Standardization of medical documentation is a prerequisite for data exchange as well as the transferability and reuse of data. In the long run, standardization would save time and money and extend the capabilities for which such data could be used. In the context of this work, a lack of standardization was observed regarding current information management. Free-form text fields and intricate questions complicate automated data access and transfer between institutions. This work also revealed the potential of a unified documentation process as a core data set of the 50 most frequent common data elements, accounting for 34% of the documentation in medical information management. Such a data set offers a starting point for standardized and interoperable data collection in routine care, quality management, and clinical research.
目前，中风患者的医疗信息管理是一项非常耗时的工作。对于急性中风患者的治疗有明确的指南和程序，但尚不清楚这些既定做法在患者文档中的体现程度。
本研究比较了多种关于中风的文档流程。这项工作的主要目的是概述中风文档中最常见的医学概念，并识别不同文档背景之间的重叠部分，以便定义一个可用于潜在数据接口的核心数据集。
将来自不同文档背景（包括医院、临床试验、登记处和国际标准）的关于中风治疗及后续康复的医学源文档表单，按照操作数据模型进行数字化处理。使用统一医学语言系统对每个源数据元素进行语义标注。对概念代码进行语义重叠分析。如果一个概念出现在至少两个文档背景中，则认为它是常见的。使用既定的基于专家的半自动方法，根据源数据元素的频繁模式，为生成的常见概念扩展实施细节，包括数据类型和允许值。
总共识别出3287个数据元素，其中1051个成为独特的医学概念。中风文档中出现频率最高的100个医学概念占所有概念出现次数的9.51%（100/1051），出现频率最高的50个概念占4.75%（50/1051）。一份常见数据元素列表以不同的标准化机器可读格式在公共元数据存储库中实现，以便进行可互操作的重用。
医学文档标准化是数据交换以及数据可转移性和重用性的前提条件。从长远来看，标准化将节省时间和金钱，并扩展此类数据的使用能力。在这项工作的背景下，观察到当前信息管理缺乏标准化。自由格式文本字段和复杂问题使机构之间的自动数据访问和传输变得复杂。这项工作还揭示了统一文档流程作为50个最常见数据元素的核心数据集的潜力，占医学信息管理文档的34%。这样一个数据集为常规护理、质量管理和临床研究中的标准化和可互操作数据收集提供了一个起点。
