A Collaborative Decision Support Tool for Managing Chronic Conditions

Nadin Kokciyan; Martin Chapman; Panagiotis Balatsoukas; Isabel Sassoon; Kai Essers; Mark Ashworth; Vasa Curcin; Sanjay Modgil; Simon Parsons; Elizabeth I Sklar

doi:10.3233/SHTI190302

A Collaborative Decision Support Tool for Managing Chronic Conditions

Nadin Kokciyan, Martin Chapman, Panagiotis Balatsoukas, Isabel Sassoon, Kai Essers, Mark Ashworth, Vasa Curcin, Sanjay Modgil, Simon Parsons, Elizabeth I Sklar

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

20 Citations (Scopus)

314 Downloads (Pure)

Abstract

This paper describes work to assess the feasibility of using a decision support tool to help patients with chronic conditions, in particular 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, in particular: 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 providing further explanations about their overall well-being.

Original language	English
Title of host publication	The 17th World Congress of Medical and Health Informatics
DOIs	https://doi.org/10.3233/SHTI190302
Publication status	Published - 2019

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10.3233/SHTI190302

A Collaborative Decision Support_KOKCIYAN_Accepted10March2019_GREEN AAMAccepted author manuscript, 499 KB

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title = "A Collaborative Decision Support Tool for Managing Chronic Conditions",

abstract = "This paper describes work to assess the feasibility of using a decision support tool to help patients with chronic conditions, in particular 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, in particular: 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 providing further explanations about their overall well-being.",

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AU - Kokciyan, Nadin

AU - Chapman, Martin

AU - Balatsoukas, Panagiotis

AU - Sassoon, Isabel

AU - Essers, Kai

AU - Ashworth, Mark

AU - Curcin, Vasa

AU - Modgil, Sanjay

AU - Parsons, Simon

AU - Sklar, Elizabeth I

PY - 2019

Y1 - 2019

N2 - This paper describes work to assess the feasibility of using a decision support tool to help patients with chronic conditions, in particular 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, in particular: 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 providing further explanations about their overall well-being.

AB - This paper describes work to assess the feasibility of using a decision support tool to help patients with chronic conditions, in particular 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, in particular: 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 providing further explanations about their overall well-being.

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DO - 10.3233/SHTI190302

M3 - Conference paper

BT - The 17th World Congress of Medical and Health Informatics

ER -

A Collaborative Decision Support Tool for Managing Chronic Conditions

Abstract

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