Dataset Information

Towards interoperability in infection control: a standard data model for microbiology.

ABSTRACT: The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declared antimicrobial resistance one of the top global public health threats that humanity is facing. In this article, we describe how we developed a common model for microbiology data in an interdisciplinary collaborative effort and how we make use of the standard HL7 FHIR and terminologies such as SNOMED CT or LOINC to ensure syntactic and semantic interoperability. The use of international healthcare standards qualifies our data model to be adopted beyond the environment where it was first developed and used at an international level.

SUBMITTER: Rinaldi E

PROVIDER: S-EPMC10517923 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Towards interoperability in infection control: a standard data model for microbiology.

Rinaldi Eugenia E Drenkhahn Cora C Gebel Benjamin B Saleh Kutaiba K Tönnies Hauke H von Loewenich Friederike D FD Thoma Norbert N Baier Claas C Boeker Martin M Hinske Ludwig Christian LC Diaz Luis Alberto Peña LAP Behnke Michael M Ingenerf Josef J Thun Sylvia S

Scientific data 20230923 1

The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declar ...[more]

PMID: 37741862

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Project description:Whole genome sequencing (WGS) has become a vital tool in clinical microbiology, playing an important role in outbreak investigations, molecular surveillance, and identification of bacterial species, resistance mechanisms and virulence factors. However, the complexity of WGS data presents challenges in interpretation and reporting, requiring tailored strategies to enhance efficiency and impact. This study explores the diverse needs of key stakeholders in healthcare, including clinical management, laboratory work, public surveillance and epidemiology, infection prevention and control, and academic research, regarding WGS-based reporting of clinically relevant bacterial species. In order to determine preferences regarding WGS reports, human-centered design approach was employed, involving an online survey and a subsequent workshop with stakeholders. The survey gathered responses from 64 participants representing the above mentioned healthcare sectors across geographical regions. Key findings include the identification of barriers related to data accessibility, integration with patient records, and the complexity of interpreting WGS results. As the participants designed their ideal report using nine pre-defined sections of a typical WGS report, differences in needs regarding report structure and content across stakeholders became evident. The workshop discussions further highlighted the need to feature critical findings and quality metrics prominently in reports, as well as the demand for flexible report designs. Commonalities were observed across stakeholder-specific reporting templates, such as the uniform ranking of certain report sections, but preferences regarding the depth of content within these sections varied. Using these findings, we suggest stakeholder-specific structures which should be considered when designing customized reporting templates. In conclusion, this study underscores the importance of tailoring WGS-based reports of clinically relevant bacteria to meet the distinct needs of diverse healthcare stakeholders. The evolving landscape of digital reporting increases the opportunities with respect to WGS reporting and its utility in managing infectious diseases and public health surveillance.

Dataset Information

Towards interoperability in infection control: a standard data model for microbiology.

Publications

Towards interoperability in infection control: a standard data model for microbiology.

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