Transformation of microbiology data into a standardised data representation using OpenEHR

Area of Science:

• Health Informatics
• Microbiology
• Computer Science

Background:

• Multidrug-resistant organisms (MDRO) pose a significant global healthcare threat, with nosocomial outbreaks being a major concern.
• Effective detection of these outbreaks requires computer-based applications, but data heterogeneity across institutions hinders reusability.

Purpose of the Study:

• To develop standardized and interoperable microbiology data models using openEHR.
• To establish a foundation for cross-institutional, automated outbreak detection systems.

Main Methods:

• A multi-centric standardization approach using openEHR as the modeling standard was employed.
• Microbiology reports from multiple international sites were integrated into an openEHR-based data platform.
• A prototypical application was developed for evaluation, including data comparison and automated quality checks.

Main Results:

• Standardized and interoperable microbiology data models were successfully developed and consented.
• Publicly available data models facilitate the transformation of real-life microbiology reports into standardized formats.
• Proof-of-principle application implementation confirmed the feasibility of the data transformation and integration processes.

Conclusions:

• Holistic transformation of microbiological data into standardized openEHR formats is feasible in real-world, multi-center settings.
• The developed data models and integration processes lay the groundwork for automated, cross-institutional outbreak detection.
• This standardization is essential for addressing the global challenge of multidrug-resistant organisms.