Towards a goal-oriented methodology for clinical-guideline-based management recommendations for patients with multimorbidity: GoCom and its preliminary evaluation

Kogan, Alexandra; Peleg, Mor; Tu, Samson W.; Allon, Raviv; Khaitov, Natanel; Hochberg, Irit

doi:10.1016/j.jbi.2020.103587

Cited by 20 publications

(7 citation statements)

References 39 publications

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“…In addition to the software systems utilized for RDF(S) and OWL ontology edition. The creation of the web [35]; in addition, there is a Protégé that is freely available and might make this study more repeatable. A system called Protégé was created at Stanford Medical Computing.…”

Section: Software Platforms For Semantic Web Ontology Developmentmentioning

confidence: 99%

Systematic Review of Web-Based Decision Support Systems for Clinical Applications: Enhancing Ontology with Unified Modeling Language and Ontology Web Language

Ahmed,

Layeb

2024

TEM Journal

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This article demonstrates an ontology-based technique that aids in envisioning the problem domain before software development, presenting an approach to assist decision-making for reliable and optimal healthcare administration. The proposed approach is designed for utilization by a Web-Based Decision Support System (WebDSS). The purpose of the study is to aid readers in comprehending how ontologies in healthcare management platforms can be modeled using UML and OWL. For the conceptualization and the design, service modelling and the semantics of the web language are crucial. We demonstrate the use of the Unified Modeling Language (UML) and the Ontology Web Language (OWL) in the administration of healthcare operations and key elements of the model-base of healthcare administration systems. Highly educated systems with automated assistance will allow decision-makers to more effectively incorporate aspects of sustainability into their decisions. In order to generate semantic ontologies for medical management, the present study proposes an ontology creation technique and a Semantic Web framework called Protégé. Web-based technologies, decision trees, data mining, and computational algorithms are implemented by WebDSS to assess medical resources administration information in real-time. These methods are employed to develop a decision making framework for this study. Time series graphs, email reports, and webpages are used to display the test findings. When healthcare thresholds are surpassed, the system uses text messages as email reports to automatically deliver warnings. Our study's primary contribution is the creation of a useful tool that makes it easier for academics studying medical concerns to locate online sites with information.

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Section: Software Platforms For Semantic Web Ontology Developmentmentioning

confidence: 99%

Systematic Review of Web-Based Decision Support Systems for Clinical Applications: Enhancing Ontology with Unified Modeling Language and Ontology Web Language

Ahmed,

Layeb

2024

TEM Journal

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“…The system was designed to represent the evolution of the patient's condition over time and also includes a computer-assisted design environment to draw time-oriented diagrams. Kogan et al (2018) tackled the problem of the conflict of guidelines for different diseases, which often occur in multimorbidity. Their system was designed to facilitate the integration of guidelines in multimorbid patients and can be used in virtual simulations.…”

Section: Knowledge Representation and Technology-enhanced Learningmentioning

confidence: 99%

Education of clinical reasoning in patients with multimorbidity: a scoping review and perspectives for technology-enhanced learning

Consorti,

Borcea,

Laca

et al. 2023

Front. Educ.

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Multimorbidity is defined as the co-existence of two or more chronic diseases in a patient, and it is increasing in prevalence. This condition poses new problems for clinical reasoning. Few studies inquire regarding the construct of reasoning in multimorbidity and the teaching/learning methods. The objectives of this scoping review were searching for a definition of the construct of clinical reasoning in multimorbidity and the related learning methods, and special ways in which information technology can help. We searched PubMed, Scopus, ERIC and CORE databases. After an iterative process of selection and thematic analysis, we selected 30 articles, that were thematized in three classes: the multimorbid patient as a teacher (8 articles), defining a framework of competence (11 articles), representing multimorbidity and related clinical reasoning (11 articles). In this last theme were also grouped studies using technology to enhance learning. The construct of clinical reasoning in multimorbidity expands over three domains: clinical (including managing uncertainty, anticipating, and detecting evolutions and conflicting guidelines, and setting priorities); relational (concerning communicating uncertainty and developing a feasible, shared plan of care with the patient; organizational) (managing the wide system of resources needed to take care of a multimorbid patient). The preferred teaching methods are based on the encounter with real or expert patients, technology enhanced case-based learning and graphical representations of clinical cases. Perspectives of research should be addressed to permit the learner to experience a patient’s life-long experience by moving forward and back over time while exploring interactions among diseases and social determinants with respect to possibly conflicting treatments. Perspectives on rich, technology-enhanced simulations should be researched.

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“…Goal ontologies can be used to standardise the specification of clinical goals. For example, in the Goal-based Comorbidity decision-support method [29] , goals specification follows the goal ontology developed by Fox et al. [30] that includes a verb and a noun phrase (eg, manage hypertension, prevent cardiovascular disease, treat fatigue), the HL7 FHIR [14] Goal resource, and relationships from the National Drug File - Reference Terminology (NDF-RT) ontology [31] , such as may-treat, may-prevent, and has_physiological_effect [increase/decrease State] e.g., Increase_Physical_Activity (NDF-RT Physiological Effect Goal).…”

Section: Dbci Design Stepsmentioning

confidence: 99%

SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications

Lisowska

Wilk

Peleg

2023

Journal of Biomedical Informatics

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Towards a goal-oriented methodology for clinical-guideline-based management recommendations for patients with multimorbidity: GoCom and its preliminary evaluation

Cited by 20 publications

References 39 publications

Systematic Review of Web-Based Decision Support Systems for Clinical Applications: Enhancing Ontology with Unified Modeling Language and Ontology Web Language

Systematic Review of Web-Based Decision Support Systems for Clinical Applications: Enhancing Ontology with Unified Modeling Language and Ontology Web Language

Education of clinical reasoning in patients with multimorbidity: a scoping review and perspectives for technology-enhanced learning

SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications

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