Design of a JAIN SLEE/ESB-based platform for routing medical data in the ICU

Bossche, Bruno Van Den; Hoecke, Sofie Van; Danneels, Chris; Decruyenaere, Johan; Dhoedt, Bart; Turck, Filip De

doi:10.1016/j.cmpb.2008.05.003

Cited by 11 publications

(2 citation statements)

References 15 publications

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“…The Intensive Care Information System of the ICUin Ghent [9,10] facilitates the abstraction of relevant information and supports the physicians through several medical support services, such as kidney dysfunction based on the RIFLE criteria (Risk Injury Failure Loss End-Stage Kidney Disease), CPIS (Clinical Pulmonary Infection Score), prescribing antibiotics and calculating the SOFA score (Sequential Organ Failure Assessment score) as predictors for the patients’ outcome. Laboratories and monitors provide medical data for processing, and depending on the priority, the results are sent to the patients’ bedside terminal, the physicians’ tablet or e-mail address.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert

Hristoskova

Sakkalis

Zacharioudakis

et al. 2014

Sensors

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A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs’ monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient's condition on the most suited device within the physician's reach.

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Section: Related Workmentioning

confidence: 99%

Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert

Hristoskova

Sakkalis

Zacharioudakis

et al. 2014

Sensors

Self Cite

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“…We chose an asynchronous data-driven design to support the real-time goals of our requirements, similar to the approach taken in (Van Den Bossche, et al 2008). This allows each piece of physiological data or user input to be handled and received by the protocol modules as soon as it is available, along with allowing the recommendations of the protocols to be available to the user as frequently as possible, which is a key component of CDSS design.…”

Section: System Overviewmentioning

confidence: 99%

A modular framework for clinical decision support systems

Williams

Kazanzides

et al. 2009

SIGBED Rev.

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This paper describes the design and initial implementation of a modular framework for Clinical Decision Support Systems and highlights the need for medical device plug-and-play standards.The software handles the tasks of data acquisition and validation, visualization, and treatment management in order to enable the development of protocol guideline modules as "plug-ins" to the framework. The system utilizes an asynchronous data-driven design to support real-time information flow and user interaction. All components of the framework are modular and easily extendible, allowing for new data sources, visualization methods, and protocols to be inserted.The system is configured by assigning each protocol a manager that handles decision communication with the rest of the framework. A set of classes has been created to allow communication between the different modules along with persistence of all data, decisions, and treatments to a database. The initial prototype is a Clinical Decision Support System focusing on the treatment of Traumatic Brain Injury.

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COSARA: Integrated Service Platform for Infection Surveillance and Antibiotic Management in the ICU

et al. 2012

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The Intensive Care Unit is a data intensive environment where large volumes of patient monitoring and observational data are daily generated. Today, there is a lack of an integrated clinical platform for automated decision support and analysis. Despite the potential of electronic records for infection surveillance and antibiotic management, different parts of the clinical data are stored across databases in their own formats with specific parameters, making access to all data a complex and time-consuming challenge. Moreover, the motivation behind physicians' therapy decisions is currently not captured in existing information systems. The COSARA research project offers automated data integration and services for infection control and antibiotic management for Ghent University Hospital. The platform not only gathers and integrates all relevant data, it also presents the information visually at the point of care. In this paper, we describe the design and value of COSARA for clinical treatment and infectious diseases monitoring. On the one hand, this platform can facilitate daily bedside follow-up of infections, antibiotic therapies and clinical decisions for the individual patient, while on the other hand, the platform serves as management view for infection surveillance and care quality improvement within the complete ICU ward. It is shown that COSARA is valuable for registration, real-time presentation and management of infection-related and antibiotics data.

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Design of a JAIN SLEE/ESB-based platform for routing medical data in the ICU

Cited by 11 publications

References 15 publications

Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert

Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert

A modular framework for clinical decision support systems

COSARA: Integrated Service Platform for Infection Surveillance and Antibiotic Management in the ICU

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