SAGEDesktop: An Environment for Testing Clinical Practice Guidelines

Berg, David N.; Ram, Prabhu; Glasgow, Julie; Castro, Julio O. De

doi:10.1109/iembs.2004.1403906

Cited by 9 publications

(7 citation statements)

References 5 publications

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“…Finally, the SAGE project [7,54,56,57] pursues two main goals: to create an infrastructure that allows medical experts to author and encode guidelines using a standard representation, and to use this infrastructure to deploy these guidelines across heterogeneous clinical information systems. The internal representation of guidelines in SAGE is made using the EON formalism, which is comprised of a set of Protégé classes and plug-ins [55].…”

Section: Clinical Guideline Execution Environmentsmentioning

confidence: 99%

“…The internal representation of guidelines in SAGE is made using the EON formalism, which is comprised of a set of Protégé classes and plug-ins [55]. The execution engine, called SAGEDesktop [7] is a centralised component that collects the required data from an internal repository and allows medical experts to emulate the real guideline behaviour. The execution engine interacts with the clinical information system (CIS) via an event listener and a set of services (terminology, patient record and general applications).…”

Section: Clinical Guideline Execution Environmentsmentioning

confidence: 99%

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Agent-based execution of personalised home care treatments

et al. 2009

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Home Care services are notoriously difficult to deliver efficiently, due to the heterogeneity of the involved actors and the usual co-morbidity of the patients assisted at home. The K4Care platform proposes an agent-based threelayered architecture aimed at addressing these two issues and facilitate the provision of these services. The development of the platform was supported by a methodology to help the automation of the modelling and implementation of the multi-agent system. The intelligent agents of the platform, which personify the Home Care domain actors, have the capability to guide the execution of administrative and medical processes, driving the flux of knowledge and control among all the involved professionals, simplifying their interactions and capturing new medical knowledge emerging from physicians. The platform also provides tools that allow medical practitioners to develop personalised treatments, adapted to the clinical and social circumstances of each patient and based on the standard international recommendations for the most frequent Home Care pathologies. The paper describes the architecture of the system, how personalised treatments are created, and how they are executed through the co-ordinated work of agents. A comparison with other relevant guideline execution systems and an evaluation of the actual state of the work are also provided.

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Section: Clinical Guideline Execution Environmentsmentioning

confidence: 99%

Section: Clinical Guideline Execution Environmentsmentioning

confidence: 99%

Agent-based execution of personalised home care treatments

et al. 2009

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“…Like GLIF3, SAGE is also supported by GELLO 113 , based on HL7 reference information model (RIM). SAGEDesktop 114 is the testing tool of SAGE that can test one CIG implementation at a time.…”

Section: The Role Of Cigs In Cdss-augmented Delivery Of Carementioning

confidence: 99%

The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review

2018

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Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS.

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“…From the selected tools, SAGE Workbench is arguably the most interesting example in this regard. The SAGE project, of which the SAGE Workbench is part, has a guideline visualisation and execution tool called SAGE Desktop (Berg, Ram, Glasgow, & Castro, ) that allows running CIGs encoded in the SAGE Workbench against a patient profile. Additionally, the SAGE project also proposes a guideline deployment system consisting of a technology to enable the electronic guidelines to be imported into any clinical information system.…”

Section: Cig Creation and Editingmentioning

confidence: 99%

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

et al. 2018

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Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.

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SAGEDesktop: An Environment for Testing Clinical Practice Guidelines

Cited by 9 publications

References 5 publications

Agent-based execution of personalised home care treatments

Agent-based execution of personalised home care treatments

The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

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