An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs

• Published in: AMIA ... Annual Symposium proceedings Vol. 2014; pp. 1115 - 1124
• Main Authors: Tsopra, R, Venot, A, Duclos, C
• Format: Journal Article
• Language: English
• Published: United States American Medical Informatics Association 2014
• Subjects: Algorithms; Anti-Bacterial Agents; Anti-Bacterial Agents - therapeutic use; Computation and Language; Computer Science; Decision Support Systems, Clinical; Drug Therapy, Computer-Assisted; Evidence-Based Medicine; Humans; Practice Guidelines as Topic
• ISSN: 1559-4076; 1559-4076

Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties. The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs.