Salgado-Baez Eduardo, Heidepriem Raphael, Delucchi Danhier Renate, Rinaldi Eugenia, Ravi Vishnu, Poncette Akira-Sebastian, Dahlhaus Iris, Fürstenau Daniel, Balzer Felix, Thun Sylvia, Sass Julian
Department of Anesthesiology and Intensive Care Medicine (CVK/CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Core Unit Digital Medicine and Interoperability, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
JMIR Med Inform. 2025 May 9;13:e64099. doi: 10.2196/64099.
Medication errors represent a widespread, hazardous, and costly challenge in health care settings. The lack of interoperable medication data within and across hospitals not only creates an administrative burden through redundant data entry but also increases the risk of errors due to human mistakes, imprecise data transformations, and misinterpretations. While digital solutions exist, fragmented systems and nonstandardized data hinder effective medication management.
This study aimed to assess medication data available across the multiple systems of a large university hospital, identify a minimum dataset with the most relevant information, and propose a standard interoperable FHIR-based solution that can import and transfer information from a standardized drug master database to various target systems.
Medication data from all relevant departments of a large German hospital were thoroughly analyzed. To ensure interoperability, data elements for developing a minimum dataset were defined based on relevant medication identifiers, the Health Level 7 Fast Health Interoperability Resources (HL7 FHIR) standard, and the German Medical Informatics Initiative (MII) specifications. To enhance medication identification accuracy, the dataset was further enriched with information from Germany's most comprehensive drug database and European Standard Drug Terms (EDQM) to further enrich medication identification accuracy. Finally, data on 60 frequently used medications in the institution were systematically extracted from multiple medication systems used in the institution and integrated into a new structured, dedicated database.
The analysis of all the available medication datasets within the institution identified 7964 drugs. However, limited interoperability was observed due to a fragmented local IT infrastructure and challenges in medication data standardization. Data integrated and available in the new structured medication dataset with key elements to ensure data identification accuracy and interoperability, successfully enabled the generation of medication order messages, ensuring medication interoperability, and standardized data exchange.
Our approach addresses the lack of interoperability in medication data and the need for standardized data exchange. We propose a minimum set of data elements aligned with German and international coding systems to be used in combination with the FHIR standard for processes such as the digital transfer of discharge medication prescriptions from intensive care units to general wards, which can help to reduce medication errors and enhance patient safety.
用药错误在医疗环境中是一个普遍存在、具有危险性且成本高昂的挑战。医院内部和医院之间缺乏可互操作的用药数据，不仅会因重复录入数据而带来管理负担，还会因人为失误、不精确的数据转换和误解而增加出错风险。虽然存在数字解决方案，但系统碎片化和数据不标准化阻碍了有效的用药管理。
本研究旨在评估一家大型大学医院多个系统中的可用用药数据，确定包含最相关信息的最小数据集，并提出一种基于FHIR的标准可互操作解决方案，该方案可从标准化药品主数据库导入和传输信息到各种目标系统。
对一家大型德国医院所有相关科室的用药数据进行了全面分析。为确保可互操作性，基于相关用药标识符、健康等级7快速健康互操作性资源（HL7 FHIR）标准和德国医学信息学倡议（MII）规范，定义了用于开发最小数据集的数据元素。为提高用药识别准确性，该数据集还通过来自德国最全面的药品数据库和欧洲标准药品术语（EDQM）的信息进一步丰富。最后，从该机构使用的多个用药系统中系统地提取了该机构60种常用药物的数据，并整合到一个新的结构化专用数据库中。
对该机构内所有可用用药数据集的分析识别出7964种药物。然而，由于本地IT基础设施碎片化以及用药数据标准化方面的挑战，观察到互操作性有限。新的结构化用药数据集中整合并可用的关键元素数据，成功实现了用药医嘱消息的生成，确保了用药互操作性和标准化数据交换。
我们的方法解决了用药数据缺乏互操作性以及标准化数据交换的需求。我们提出了一套与德国和国际编码系统一致的最小数据元素集，用于与FHIR标准结合，应用于诸如从重症监护病房到普通病房的出院用药处方数字传输等流程，这有助于减少用药错误并提高患者安全性。
