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Supporting Hospitalized Patients Thr...

Khelifi, Maher.

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Supporting Hospitalized Patients Through AI Technologies.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Supporting Hospitalized Patients Through AI Technologies./
作者:	Khelifi, Maher.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	174 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-05, Section: B.
Contained By:	Dissertations Abstracts International82-05B.
標題:	Medicine. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28094832
ISBN:	9798684670626

Supporting Hospitalized Patients Through AI Technologies.
Khelifi, Maher.

Supporting Hospitalized Patients Through AI Technologies. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 174 p.

Source: Dissertations Abstracts International, Volume: 82-05, Section: B.

Thesis (Ph.D.)--University of Washington, 2020.

This item must not be sold to any third party vendors.

Involving hospitalized patients in their care has been shown to be valuable in terms of achieving better health outcomes for them. Therefore, hospitalized patients are encouraged to actively engage in their own care, manage their safety, make medical decisions, and monitor their treatments' quality. However, engaged hospitalized patients face a dilemma. The complexity of their care makes their engagement more important, yet harder to achieve. During their hospitalization, engagement quality requires awareness and education about illness and treatments. However, achieving comprehension can be challenging for complex healthcare situations, especially when patients may not have a complete understanding of their health data. Furthermore, with complex health problems, patients are cognitively and physically impaired because of pain, stress, and medications. Simultaneously, they face a steep learning curve in utilizing and absorbing the abundant information related to their health situation. Thus, hospitalized patients face an engagement gap that grows deeper with the complexity of their health problems. Artificial intelligence (AI) agents, technologies that automate information processing and its communication, could be a promising solution to providing patients with understanding and insights about their illness and its treatment, yet research into how AI agents could support patients in hospital settings has been limited. In this dissertation, I attempt to address this research gap by first defining technological opportunities, particularly via AI applications, that can support patient and information needs in hospital settings. To do so, I first introduce a user-centered research methodology called "Muse cards." This method aims to inspire patients and their family caregivers to envision hospital technologies that could provide them with enhanced support and to create new tools that can accommodate their evolving situation and roles in hospital settings. Second, I focus on the patient-clinician conversation, a core source of information in hospital settings, and describe the factors that influence the importance of verbally communicated information from the patients' perspective and from the clinicians' perspective. Third, I report the results found by testing NURI, an AI agent that I constructed to help hospitalized patients understand medical conversations with their clinicians, and the patients', caregivers', and clinicians' acceptance of NURI and perceptions of its usefulness. This work contributes to human-computer interaction research by giving patients a toolkit designed to help them to reimagine existing technologies and to contribute to our understanding of the role and value of automated agents for helping patients and their families in hospital settings. Furthermore, this work contributes to Personal Health Informatics research by providing an annotation framework to turn patient-clinician conversations into patient-facing notes. Lastly, this work contributes more broadly to evolving research and understanding about uses of AI agents in hospital settings by serving as a source of design and implementation guidelines.

ISBN: 9798684670626Subjects--Topical Terms:

641104
Medicine.
Subjects--Index Terms:

AI agents

Supporting Hospitalized Patients Through AI Technologies.
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