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A Generic Approach for Data Management and End-User Development of Clinical Decision Support Systems
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2018 (English)Report (Other academic)
Abstract [en]

The main purposes of clinical decision-support systems (CDSS) are disseminating evidence-based medical knowledge (EBM), supporting a continued medical education, and improving clinical decision making and care. These purposes are traditionally achieved by using solutions that are relatively transparent and explainable to the end user. However, the development and maintenance of such solutions is resource demanding. Currently, there are four challenges existing in CDSSs when adapting to new circumstances. That is, when facing new knowledge, new diseases, different organizations and users with different skills, usually one needs to update the existing CDSS or develop a new CDSS, which requires lots of time and efforts. Hence, this paper aims for reusing an existing CDSS code by virtue of inputs from authorized medical domain expert users, and with minimal requirement of knowledge and software engineers. To facilitate knowledge elicitation and end-user development, an ACKTUS-based architecture for CDSS development and management is presented that contains: I) A knowledge base and a content management system built on Semantic Web technology to achieve modularity, reusability, customisation, and the possibility to allow medical experts to model the medical knowledge and to structure the information that builds up the design of the user interface; II) A user interface and an graphical user interface generator that automatically generates the user interface whenever the user logs in, so that the interface is synchronised with updates of the knowledge base; III) An inference engine that utilizes patient-specific data and applies various rules in the knowledge base to conduct the reasoning and decision making. These modules can be reused when adapting to new situations. A CDSS for dementia diagnosis is developed and used as an example in the presentation of the generic architecture. A pilot study of the CDSS is presented involving four medical professionals with different levels of expertise. The results show how the generic approach allows for easy knowledge representation and management of EBM, supports a continued medical education and may improve clinical decision making and care provision.

Place, publisher, year, edition, pages
Umeå universitet , 2018. , p. 25
Series
Report / UMINF, ISSN 0348-0542 ; 18.08
Keywords [en]
CDSS, Data Management, Knowledge Acquisition, Ontology, Semantic Web
National Category
Information Systems Human Computer Interaction
Identifiers
URN: urn:nbn:se:umu:diva-150968OAI: oai:DiVA.org:umu-150968DiVA, id: diva2:1240399
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-08-21Bibliographically approved
In thesis
1. Developing digital support for learning and diagnostic reasoning in clinical practice
Open this publication in new window or tab >>Developing digital support for learning and diagnostic reasoning in clinical practice
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The two main purposes of clinical decision-support systems (CDSSs) are to provide healthcare professionals decision-making support based on evidence-based medical knowledge, and a continuing medical education. This thesis focuses on both purposes and shows how fundamental theory in the field of artificial intelligence can be developed, adapted and implemented in a CDSS for supporting learning and diagnostic reasoning in clinical practice. The main research problems addressed in this thesis are how to represent and manage uncertain, incomplete, inconsistent and distributed knowledge in automated reasoning and decision-making with the clinicians in the loop, how to facilitate the knowledge engineering and maintenance process, and how to detect and support learning and skill development in CDSS users.

Research contributions include theories, methods, and algorithms based on possibilistic logic and formal argumentation for representing and managing uncertain, incomplete, inconsistent and distributed medical knowledge, and for supporting reasoning and decision-making when using a CDSS. The clinician is provided potentially conflicting arguments and their strength based on different diagnostic criteria and the available patient information in order to make an informed decision. The theoretical results were implemented in the Dementia Diagnosis and Management Support System - Web version (DMSS-W), in a multi-agent hypothesis-driven inquiry dialogue system, and in an inference engine serving as a module of ACKTUS.

CDSS maintenance is challenging since new knowledge about diseases and treatments are continuously developed. Typically, knowledge and software engineers are needed to bridge medical experts and CDSSs, leading to time-consuming system development. ACKTUS (Activity-Centered Knowledge and Interaction Tailored to Users) was, as part of this research, further developed as a generic web-based platform for knowledge management and end-user development of CDSSs. It includes the inference engine and a content management system that the medical expert can use to manage knowledge, design and evaluate CDSSs. A graphical user interface generator synchronizes the interface to the ontology serving as the knowledge base. ACKTUS was used for developing DMSS-W, and facilitated the system development and maintenance.

To offer person-tailored support for the clinician's learning, reasoning and decision-making, the CDSS design was based on theories of how novices and experts reason and make decisions. Pilot case studies involving physicians with different levels of expertise who applied DMSS-W in patient cases were conducted in clinical practice to explore methods for detecting skill levels and whether learning is taking place. The results indicated that the skill levels can be detected using the method. The novice was seen to develop reasoning strategies similar to an expert's, indicating that learning was taking place. In future work, tailored educational support will be developed, and evaluated using the methods.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2018. p. 49
Series
Report / UMINF, ISSN 0348-0542 ; 18.09
Keywords
Clinical decision-support systems, knowledge representation, possibilistic logic, multi-agent systems, formal argumentation, ontology, automated decision making, inquiry dialogue, end-user development, continuing medical education, dementia
National Category
Computer Systems
Identifiers
urn:nbn:se:umu:diva-150922 (URN)978-91-7601-918-4 (ISBN)
Public defence
2018-09-27, MA121, MIT-huset, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2018-08-23 Created: 2018-08-20 Last updated: 2018-08-21Bibliographically approved

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Yan, ChunliLindgren, Helena

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