A Collaborative Decision Support Tool for Managing Chronic Conditions.


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
21 Aug 2019
Historique:
entrez: 24 8 2019
pubmed: 24 8 2019
medline: 12 9 2019
Statut: ppublish

Résumé

This paper describes work to assess the feasibility of using a decision support tool to help patients with chronic conditions, specifically stroke, manage their condition in collaboration with their carers and the health care professionals who are looking after them. The system contains several novel elements: the integration of data from commercial wellness sensors, electronic health records and clinical guidelines; the use of computational argumentation to track the source of data and to resolve conflicts and make recommendations; and argumentation-based dialogue to support interaction with patients. The proposed approach is implemented as an application that can run on smart devices (e.g. tablets). The users have personalised dashboards where they can visualise their health data and interact with a conversational chatbot that provides further explanations about their overall well-being.

Identifiants

pubmed: 31438003
pii: SHTI190302
doi: 10.3233/SHTI190302
doi:

Types de publication

Journal Article

Langues

eng

Pagination

644-648

Auteurs

Nadin Kökciyan (N)

Department of Informatics, King's College London, London, United Kingdom.

Martin Chapman (M)

Department of Population Health Sciences, King's College London, London, United Kingdom.

Panagiotis Balatsoukas (P)

Department of Population Health Sciences, King's College London, London, United Kingdom.

Isabel Sassoon (I)

Department of Informatics, King's College London, London, United Kingdom.

Kai Essers (K)

Department of Informatics, King's College London, London, United Kingdom.

Mark Ashworth (M)

Department of Population Health Sciences, King's College London, London, United Kingdom.

Vasa Curcin (V)

Department of Informatics, King's College London, London, United Kingdom.
Department of Population Health Sciences, King's College London, London, United Kingdom.

Sanjay Modgil (S)

Department of Informatics, King's College London, London, United Kingdom.

Simon Parsons (S)

Department of Informatics, King's College London, London, United Kingdom.

Elizabeth I Sklar (EI)

Department of Informatics, King's College London, London, United Kingdom.

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Classifications MeSH