Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language

BackgroundEffective shared decision-making between patients and physicians is crucial for enhancing health care quality and reducing medical errors. The literature shows that the absence of effective methods to facilitate shared decision-making can result in poor patient enga...

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Main Authors: XiaoRui Guo, Liang Xiao, Xinyu Liu, Jianxia Chen, Zefang Tong, Ziji Liu
Format: Article
Language:English
Published: JMIR Publications 2025-03-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2025/1/e55341
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author XiaoRui Guo
Liang Xiao
Xinyu Liu
Jianxia Chen
Zefang Tong
Ziji Liu
author_facet XiaoRui Guo
Liang Xiao
Xinyu Liu
Jianxia Chen
Zefang Tong
Ziji Liu
author_sort XiaoRui Guo
collection DOAJ
description BackgroundEffective shared decision-making between patients and physicians is crucial for enhancing health care quality and reducing medical errors. The literature shows that the absence of effective methods to facilitate shared decision-making can result in poor patient engagement and unfavorable decision outcomes. ObjectiveIn this paper, we propose a Collaborative Decision Description Language (CoDeL) to model shared decision-making between patients and physicians, offering a theoretical foundation for studying various shared decision scenarios. MethodsCoDeL is based on an extension of the interaction protocol language of Lightweight Social Calculus. The language utilizes speech acts to represent the attitudes of shared decision-makers toward decision propositions, as well as their semantic relationships within dialogues. It supports interactive argumentation among decision makers by embedding clinical evidence into each segment of decision protocols. Furthermore, CoDeL enables personalized decision-making, allowing for the demonstration of characteristics such as persistence, critical thinking, and openness. ResultsThe feasibility of the approach is demonstrated through a case study of shared decision-making in the disease domain of atrial fibrillation. Our experimental results show that integrating the proposed language with GPT can further enhance its capabilities in interactive decision-making, improving interpretability. ConclusionsThe proposed novel CoDeL can enhance doctor-patient shared decision-making in a rational, personalized, and interpretable manner.
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publishDate 2025-03-01
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series Journal of Medical Internet Research
spelling doaj-art-e4928f4805dc4ac3b8104474081fd9c22025-08-20T02:02:21ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-03-0127e5534110.2196/55341Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description LanguageXiaoRui Guohttps://orcid.org/0009-0002-9860-2538Liang Xiaohttps://orcid.org/0000-0002-1564-2466Xinyu Liuhttps://orcid.org/0009-0001-3616-9436Jianxia Chenhttps://orcid.org/0000-0001-6662-1895Zefang Tonghttps://orcid.org/0009-0003-7766-362XZiji Liuhttps://orcid.org/0009-0004-6256-6293 BackgroundEffective shared decision-making between patients and physicians is crucial for enhancing health care quality and reducing medical errors. The literature shows that the absence of effective methods to facilitate shared decision-making can result in poor patient engagement and unfavorable decision outcomes. ObjectiveIn this paper, we propose a Collaborative Decision Description Language (CoDeL) to model shared decision-making between patients and physicians, offering a theoretical foundation for studying various shared decision scenarios. MethodsCoDeL is based on an extension of the interaction protocol language of Lightweight Social Calculus. The language utilizes speech acts to represent the attitudes of shared decision-makers toward decision propositions, as well as their semantic relationships within dialogues. It supports interactive argumentation among decision makers by embedding clinical evidence into each segment of decision protocols. Furthermore, CoDeL enables personalized decision-making, allowing for the demonstration of characteristics such as persistence, critical thinking, and openness. ResultsThe feasibility of the approach is demonstrated through a case study of shared decision-making in the disease domain of atrial fibrillation. Our experimental results show that integrating the proposed language with GPT can further enhance its capabilities in interactive decision-making, improving interpretability. ConclusionsThe proposed novel CoDeL can enhance doctor-patient shared decision-making in a rational, personalized, and interpretable manner.https://www.jmir.org/2025/1/e55341
spellingShingle XiaoRui Guo
Liang Xiao
Xinyu Liu
Jianxia Chen
Zefang Tong
Ziji Liu
Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
Journal of Medical Internet Research
title Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
title_full Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
title_fullStr Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
title_full_unstemmed Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
title_short Enhancing Doctor-Patient Shared Decision-Making: Design of a Novel Collaborative Decision Description Language
title_sort enhancing doctor patient shared decision making design of a novel collaborative decision description language
url https://www.jmir.org/2025/1/e55341
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