Data-driven Web-based Intelligent Decision Support System for Infection Management at Point-Of-Care: Case-Based Reasoning Benefits and Limitations

Bernard Hernandez, Pau Herrero, Timothy M. Rawson, Luke S. P. Moore, Esmita Charani, Alison H. Holmes, Pantelis Georgiou

Abstract

Antimicrobial Resistance (AMR) is a major patient safety issue. Attempts have been made to palliate its growth. Misuse of antibiotics to treat human infections is a main concern and therefore prescription behaviour needs to be studied and modified appropriately. A common approach relies on designing software tools to improve data visualization, promote knowledge transfer and provide decision-making support. This paper explains the design of a Decision Support System (DSS) for clinical environments to provide personalized, accurate and effective diagnostics at point-of-care (POC), improving continuity, interpersonal communication, education and knowledge transfer. Demographics, biochemical and susceptibility laboratory tests and individualized diagnostic/therapeutic advice are presented to clinicians in a handheld device. Case-Based Reasoning (CBR) is used as main reasoning engine to decision support for infection management at POC. A web-based CBR-inspired interface design focused on usability principles has also been developed. The proposed DSS is perceived as useful for patient monitoring and outcome review at POC by expert clinicians. The DSS was rated with a System Usability Scale (SUS) score of 68.5 which indicates good usability. Furthermore, three areas of improvement were identified from the feedback provided by clinicians: thorough guidance requirements for junior clinicians, reduction in time consumption and integration with prescription workflow.

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Paper Citation


in Harvard Style

Hernandez B., Herrero P., Rawson T., Moore L., Charani E., Holmes A. and Georgiou P. (2017). Data-driven Web-based Intelligent Decision Support System for Infection Management at Point-Of-Care: Case-Based Reasoning Benefits and Limitations . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017) ISBN 978-989-758-213-4, pages 119-127. DOI: 10.5220/0006148401190127


in Bibtex Style

@conference{healthinf17,
author={Bernard Hernandez and Pau Herrero and Timothy M. Rawson and Luke S. P. Moore and Esmita Charani and Alison H. Holmes and Pantelis Georgiou},
title={Data-driven Web-based Intelligent Decision Support System for Infection Management at Point-Of-Care: Case-Based Reasoning Benefits and Limitations},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)},
year={2017},
pages={119-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006148401190127},
isbn={978-989-758-213-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)
TI - Data-driven Web-based Intelligent Decision Support System for Infection Management at Point-Of-Care: Case-Based Reasoning Benefits and Limitations
SN - 978-989-758-213-4
AU - Hernandez B.
AU - Herrero P.
AU - Rawson T.
AU - Moore L.
AU - Charani E.
AU - Holmes A.
AU - Georgiou P.
PY - 2017
SP - 119
EP - 127
DO - 10.5220/0006148401190127