Abstract

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.

Highlights

  • The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge

  • We focus on the modelling and integration of the microbiology data

  • A minimal data set for general patient data and the representation of movement data (e. g. patient admission, discharge and all locations the patient visited during a hospital stay) were defined for the future work towards the smart infection control system (SmICS) application

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Summary

Introduction

The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. The publicly available data models can be used across institutions to transform real-life microbiology reports into standardised representations. 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. Relevant information can be provided for the clinical staff at the right time and clusters can be stopped before developing outbreaks. Such approaches require availability and accessibility of data in a high quality manner. For outbreak control, the synthesis of both clinical microbiologic laboratory data and fine granular patient movement data is crucial to detect, analyse and interrupt transmission pathways. The overall amount of data is increasing, harmonizing these data sets (which are often generated in various hospital information systems and applications without any interconnections, standardized definitions and open interfaces) remains c­ hallenging[9]

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