Integrated Perspectives on Clinical Decision Support: A Comparative Analysis of Knowledge Management Approaches.

We analyze five approaches to knowledge management in clinical decision support (CDS) systems: pattern recognition based on annotated imaging data, mining of stored structured medical data, text mining of published texts, computable knowledge design, and general or specific text corpora for large language models. Each method's strengths and limitations in automating clinical knowledge management while striving for a zero-error policy are evaluated, offering insights into their roles in enhancing healthcare through intelligent decision support. The study aims to inform decisions in the development of effective, transparent CDS systems in clinical and patient care settings.

A Microbiology Analytics Tool to Evaluate the Burden of Antibiotic-Resistant Infections.

Leveraging the capabilities of a microbiological clinical analytics tool, this study delves into quantifying the public health impact of antibiotic-resistant bacteria. Focusing on eight predominant antibiotic-resistant bacteria, the study utilizes University Hospital Vienna's data to calculate the burden of antibiotic-resistant infections in disability-adjusted life years. The results highlight the potential of extended analytics tools in epidemiological research and underscore the pressing challenge of antimicrobial drug resistance.

Health Digital Twins with Clinical Decision Support.

This paper studies the feasibility of incorporating clinical decision support (CDS) into health digital twins (HDTs). A HDT is visualized in a web application, health data are stored in a FHIR-based electronic health record, and an Arden-Syntax-based CDS interpretation and alert service is connected. The prototype focuses on interoperability of these components. The study confirms the feasibility of CDS integration into HDTs and provides insight into possibilities for further expansion.