Design of a clinical decision support system for assisting in empiric antibiotic treatments

Abstract

The administration of antibiotics is a task that often must be performed in an empiric way due to the pressing urgency of controlling the infection with no possibility of waiting for culture results. Empiric antibiotic treatment is dataintensive, and healthcare professionals must take into account numerous factors (e.g., evidence-based knowledge, economic directives, ecological effects, local conditions and protocols, etc.) before ordering a treatment. Clinical Decision Support Systems (CDSS) have risen with the aim of influencing medical practice and can be an interesting element of knowledge generation in the health information ecosystem. Several examples of CDSS have been developed in the antibiotic prescription field but their lack of flexibility to different settings, and poor adaptability to evolution have been important obstacles for a wider deployment. In this work a design of CDSS focused on empiric antibiotic treatment is approached. The design considers the integration of the CDSS in a standard-based healthcare system federation, from which collects real-time data in order to adapt evidencebased guidelines to specific patients, organizational directives and other factors. Semantic technologies have been used as basis of design for enhancing the reuse and flexibility of the system to different scenarios and organizations.