Development of a clinical decision support system for antibiotic management in a hospital environment

Canovas-Segura, Bernardo; Campos, Manuel; Palácios, Francisco

doi:10.1007/s13748-016-0089-x

Cited by 31 publications

(17 citation statements)

References 65 publications

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“…WASPSS uses artificial intelligence techniques to provide proper support for ASP teams. In particular, WASPSS includes a knowledge module to incorporate clinical literature and daily practice knowledge [33,37,42]. To this end, the module implements a rule-based reasoning architecture composed of a knowledge base and a rulebased engine.…”

Section: System Architecture Overviewmentioning

confidence: 99%

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WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship

Canovas-Segura¹,

Morales²,

Juárez³

et al. 2021

Recent Advances in Digital System Diagnosis and Management of Healthcare

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The increase of infections caused by resistant bacteria has become one of the major health-care problems worldwide. The creation of multidisciplinary teams dedicated to the implementation of antimicrobial stewardship programmes (ASPs) is encouraged by all clinical institutions to cope with this problem. In this chapter, we describe the Wise Antimicrobial Stewardship Program Support System (WASPSS), a CDSS focused on providing support for ASP teams. WASPSS gathers the required information from other hospital systems in order to provide decision support in antimicrobial stewardship from both patient-centered and global perspectives. To achieve this, it combines business intelligence techniques with a rule-based inference engine to integrate the data and knowledge required in this scenario. The system provides functions such as alerts, recommendations, antimicrobial prescription support and global surveillance. Furthermore, it includes experimental modules for improving the adoption of clinical guidelines and applying prediction models related with antimicrobial resistance. All these functionalities are provided through a multiuser web interface, personalized for each role of the ASP team.

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Section: System Architecture Overviewmentioning

confidence: 99%

“…WASPSS is also designed to incorporate different kinds of knowledge related with antimicrobial resistance [33]. The main source for the knowledge included is the expert rules from the EUropean Committee on Antimicrobial Susceptibility Testing (EUCAST) [34,35].…”

Section: Incorporation Of Clinical Knowledgementioning

confidence: 99%

WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship

Canovas-Segura¹,

Morales²,

Juárez³

et al. 2021

Recent Advances in Digital System Diagnosis and Management of Healthcare

Self Cite

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“…This methodology works over ontologies that provide a formal representation of pharmacogenomic knowledge. In [16], a clinical decision support system for the antibiotic stewardship program is presented. This system implements production rules, ontologies, and workflow modelling techniques to provide a multi-user perspective and reactive and proactive behaviors.…”

Section: Related Workmentioning

confidence: 99%

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

et al. 2020

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In the agricultural context, there is a great diversity of insects and diseases that affect crops. Moreover, the amount of data available on data sources such as the Web regarding these topics increase every day. This fact can represent a problem when farmers want to make decisions based on this large and dynamic amount of information. This work presents AgriEnt, a knowledge-based Web platform focused on supporting farmers in the decision-making process concerning crop insect pest diagnosis and management. AgriEnt relies on a layered functional architecture comprising four layers: the data layer, the semantic layer, the web services layer, and the presentation layer. This platform takes advantage of ontologies to formally and explicitly describe agricultural entomology experts’ knowledge and to perform insect pest diagnosis. Finally, to validate the AgriEnt platform, we describe a case study on diagnosing the insect pest affecting a crop. The results show that AgriEnt, through the use of the ontology, has proven to produce similar answers as the professional advice given by the entomology experts involved in the evaluation process. Therefore, this platform can guide farmers to make better decisions concerning crop insect pest diagnosis and management.

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“…Visual analytics can be a powerful tool if used in combination with longitudinal models to analyze long time series (Mane et al, 2012;Gálvez et al, 2014) and to enhance pattern visualization to focus attention in monitoring clinical actions Cánovas-Segura et al, 2016), or to detect and show patients' behaviors to identify health-risk scenarios (Juarez et al, 2015).…”

Section: Use Of Big Data For Clinical Decision Support: Available Solmentioning

confidence: 99%

Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

Dagliati

Tibollo

Sacchi

et al. 2018

Front. Digit. Humanit.

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Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called "Learning Healthcare System Cycle," where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how "Big Data enabled" integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.

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Development of a clinical decision support system for antibiotic management in a hospital environment

Cited by 31 publications

References 65 publications

WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship

WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

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