Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
Institute for Medical Microbiology and Hospital Epidemiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
Sci Rep. 2021 May 18;11(1):10556. doi: 10.1038/s41598-021-89796-y.
The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. Computer-based applications facilitating outbreak detection can be essential to address this issue. To allow application reusability across institutions, the various heterogeneous microbiology data representations needs to be transformed into standardised, unambiguous data models. In this work, we present a multi-centric standardisation approach by using openEHR as modelling standard. Data models have been consented in a multicentre and international approach. Participating sites integrated microbiology reports from primary source systems into an openEHR-based data platform. For evaluation, we implemented a prototypical application, compared the transformed data with original reports and conducted automated data quality checks. We were able to develop standardised and interoperable microbiology data models. The publicly available data models can be used across institutions to transform real-life microbiology reports into standardised representations. The implementation of a proof-of-principle and quality control application demonstrated that the new formats as well as the integration processes are feasible. Holistic transformation of microbiological data into standardised openEHR based formats is feasible in a real-life multicentre setting and lays the foundation for developing cross-institutional, automated outbreak detection systems.
多药耐药菌(MDRO)的传播是一个全球性的医疗保健挑战。由 MDRO 引起的医院感染暴发是这一威胁的重要因素。基于计算机的应用程序有助于发现暴发,可以解决这个问题。为了允许跨机构的应用程序重用,需要将各种异构的微生物学数据表示形式转换为标准化的、明确的数据模型。在这项工作中,我们提出了一种多中心的标准化方法,使用 openEHR 作为建模标准。数据模型已经在多中心和国际方法中得到了同意。参与的站点将微生物学报告从原始源系统集成到基于 openEHR 的数据平台中。为了进行评估,我们实现了一个原型应用程序,将转换后的数据与原始报告进行了比较,并进行了自动数据质量检查。我们能够开发标准化和互操作的微生物学数据模型。可公开获得的数据模型可在机构间使用,将实际的微生物学报告转换为标准化表示。原则验证和质量控制应用程序的实现表明,新格式以及集成过程是可行的。在实际的多中心环境中将微生物数据整体转换为标准化的 openEHR 格式是可行的,并为开发跨机构的自动暴发检测系统奠定了基础。