50,177 research outputs found

    Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

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    Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

    Supporting Special-Purpose Health Care Models via Web Interfaces

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    The potential of the Web, via both the Internet and intranets, to facilitate development of clinical information systems has been evident for some time. Most Web-based clinical workstations interfaces, however, provide merely a loose collection of access channels. There are numerous examples of systems for access to either patient data or clinical guidelines, but only isolated cases where clinical decision support is presented integrally with the process of patient care, in particular, in the form of active alerts and reminders based on patient data. Moreover, pressures in the health industry are increasing the need for doctors to practice in accordance with ¿best practice¿ guidelines and often to operate under novel health-care arrangements. We present the Care Plan On-Line (CPOL) system, which provides intranet-based support for the SA HealthPlus Coordinated Care model for chronic disease management. We describe the interface design rationale of CPOL and its implementation framework, which is flexible and broadly applicable to support new health care models over intranets or the Internet

    Components of palliative care interventions addressing the needs of people with dementia living in long term care: a systematic review

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    © The Author(s) 2020. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Background: People with dementia requiring palliative care havemultiple needs that require complex, multicomponent interventions. Thisneed is amplified in the long term care setting. The European Associationfor Palliative Care (EAPC) White Paper offers recommendations forpalliative care in dementia and highlights domains of care integral forthis population, thus providing useful guidance to developing suchinterventions. This review maps components of palliative careinterventions for people with dementia in LTCFs, with a particular focuson shared decision-making.Peer reviewe

    User-centered visual analysis using a hybrid reasoning architecture for intensive care units

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    One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

    A decision support tool for supporting individuals living with long-term conditions make informed choices: LTC-Choices tool for continuous healthcare

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    An increasing number of individuals are now living with some form of chronic, long-term condition (LTC). The holistic perspective of LTCs makes it important to acknowledge that priorities and decisions are in fluctuation over the course of an individual’s life. The landscape of digital healthcare is full of information systems that capture individuals’ health data, clinical guidelines and/or advice on health conditions, which taken together can help create a comprehensive overview of suitable lifestyle choices to optimise health and well-being. Despite this, there is no evidence of existing frameworks to support individuals living with LTCs from a continuum of care perspective. In this paper, we propose such a multidimensional model for a decision support tool – LTC-Choices. This tool was developed from existing work conducted by the authors around use of multicriteria to support health decisionmaking. We illustrate how LTC-Choices can be implemented using the example of individuals living post-stroke
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