Hospital-wide ELectronic medical record evaluated computerised decision support system to improve outcomes of Patients with staphylococcal bloodstream infection (HELP): study protocol for a multicentre stepped-wedge cluster randomised trial

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

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.

"fhircrackr": An R Package Unlocking Fast Healthcare Interoperability Resources for Statistical Analysis

BACKGROUND

The growing interest in the secondary use of electronic health record (EHR) data has increased the number of new data integration and data sharing infrastructures. The present work has been developed in the context of the German Medical Informatics Initiative, where 29 university hospitals agreed to the usage of the Health Level Seven Fast Healthcare Interoperability Resources (FHIR) standard for their newly established data integration centers. This standard is optimized to describe and exchange medical data but less suitable for standard statistical analysis which mostly requires tabular data formats.

OBJECTIVES

The objective of this work is to establish a tool that makes FHIR data accessible for standard statistical analysis by providing means to retrieve and transform data from a FHIR server. The tool should be implemented in a programming environment known to most data analysts and offer functions with variable degrees of flexibility and automation catering to users with different levels of FHIR expertise.

METHODS

We propose the fhircrackr framework, which allows downloading and flattening FHIR resources for data analysis. The framework supports different download and authentication protocols and gives the user full control over the data that is extracted from the FHIR resources and transformed into tables. We implemented it using the programming language R [1] and published it under the GPL-3 open source license.

RESULTS

The framework was successfully applied to both publicly available test data and real-world data from several ongoing studies. While the processing of larger real-world data sets puts a considerable burden on computation time and memory consumption, those challenges can be attenuated with a number of suitable measures like parallelization and temporary storage mechanisms.

CONCLUSION

The fhircrackr R package provides an open source solution within an environment that is familiar to most data scientists and helps overcome the practical challenges that still hamper the usage of EHR data for research.

System for Context-Specific Visualization of Clinical Practice Guidelines (GuLiNav): Concept and Software Implementation

Background

Clinical decision support systems often adopt and operationalize existing clinical practice guidelines leading to higher guideline availability, increased guideline adherence, and data integration. Most of these systems use an internal state-based model of a clinical practice guideline to derive recommendations but do not provide the user with comprehensive insight into the model.

Objective

Here we present a novel approach based on dynamic guideline visualization that incorporates the individual patient’s current treatment context.

Methods

We derived multiple requirements to be fulfilled by such an enhanced guideline visualization. Using business process and model notation as the representation format for computer-interpretable guidelines, a combination of graph-based representation and logical inferences is adopted for guideline processing. A context-specific guideline visualization is inferred using a business rules engine.

Results

We implemented and piloted an algorithmic approach for guideline interpretation and processing. As a result of this interpretation, a context-specific guideline is derived and visualized. Our implementation can be used as a software library but also provides a representational state transfer interface. Spring, Camunda, and Drools served as the main frameworks for implementation. A formative usability evaluation of a demonstrator tool that uses the visualization yielded high acceptance among clinicians.

Conclusions

The novel guideline processing and visualization concept proved to be technically feasible. The approach addresses known problems of guideline-based clinical decision support systems. Further research is necessary to evaluate the applicability of the approach in specific medical use cases.

How to use new antibiotics in the therapy of ventilator-associated pneumonia

PURPOSE OF REVIEW

Ventilator-associated pneumonia (VAP) is a common nosocomial infection in critically ill patients requiring endotracheal intubation and mechanical ventilation. Recently, the emergence of multidrug-resistant Gram-negative bacteria, including carbapenem-resistant Enterobacterales, multidrug-resistant Pseudomonas aeruginosa and Acinetobacter species, has complicated the selection of appropriate antimicrobials and contributed to treatment failure. Although novel antimicrobials are crucial to treating VAP caused by these multidrug-resistant organisms, knowledge of how to optimize their efficacy while minimizing the development of resistance should be a requirement for their use.

RECENT FINDINGS

Several studies have assessed the efficacy of novel antimicrobials against multidrug-resistant organisms, but high-quality studies focusing on optimal dosing, infusion time and duration of therapy in patients with VAP are still lacking. Antimicrobial and diagnostic stewardship should be combined to optimize the use of these novel agents.

SUMMARY

Improvements in diagnostic tests, stewardship practices and a better understanding of dosing, infusion time, duration of treatment and the effects of combining various antimicrobials should help optimize the use of novel antimicrobials for VAP and maximize clinical outcomes while minimizing the development of resistance.

Management of Staphylococcus aureus Bloodstream Infections

Staphylococcus aureus bloodstream infections are associated with a high morbidity and mortality. Nevertheless, significance of a positive blood culture with this pathogen is often underestimated or findings are misinterpreted as contamination, which can result in inadequate diagnostic and therapeutic consequences. We here review and discuss current diagnostic and therapeutic key elements and open questions for the management of Staphylococcus aureus bloodstream infections.