Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making

Artificial intelligence (AI)-enabled decision aids can contribute to the shared decision-making process between patients and clinicians through personalised recommendations. This systematic review aims to understand users' perceptions on using AI-enabled decision aids to inform shared decision-making. Four databases were searched. The population, intervention, comparison, outcomes and study design tool was used to formulate eligibility criteria. Titles, abstracts and full texts were independently screened and PRISMA guidelines followed. A narrative synthesis was conducted. Twenty-six articles were included, with AI-enabled decision aids used for screening and prevention, prognosis, and treatment. Patients found the AI-enabled decision aids easy to understand and user-friendly, fostering a sense of ownership and promoting better adherence to recommended treatment. Clinicians expressed concerns about how up-to-date the information was and the potential for over- or under-treatment. Despite users' positive perceptions, they also acknowledged certain challenges relating to the usage and risk of bias that would need to be addressed.Registration: PROSPERO database: (CRD42020220320).

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Publication Details

Journal
npj Digital Medicine
Published
2024-11-21
DOI
https://doi.org/10.1038/s41746-024-01326-y
Citations
21
Primary Topic
Patient-Provider Communication in Healthcare
Type
article
Field-Weighted Citation Impact
17.84

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article

Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making

Akke Vellinga, David Westfall Bates, Kweku Bimpong, Sarah P. Slight et al.
21 citations
npj Digital Medicine
Patient-Provider Communication in Healthcare
17.84
article

Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making

Akke Vellinga, David Westfall Bates, Kweku Bimpong, Sarah P. Slight, Nehal Hassan, Daniel Weiand, Graham Morgan, Robert Slight
article en
21 citations

Abstract

Artificial intelligence (AI)-enabled decision aids can contribute to the shared decision-making process between patients and clinicians through personalised recommendations. This systematic review aims to understand users' perceptions on using AI-enabled decision aids to inform shared decision-making. Four databases were searched. The population, intervention, comparison, outcomes and study design tool was used to formulate eligibility criteria. Titles, abstracts and full texts were independently screened and PRISMA guidelines followed. A narrative synthesis was conducted. Twenty-six articles were included, with AI-enabled decision aids used for screening and prevention, prognosis, and treatment. Patients found the AI-enabled decision aids easy to understand and user-friendly, fostering a sense of ownership and promoting better adherence to recommended treatment. Clinicians expressed concerns about how up-to-date the information was and the potential for over- or under-treatment. Despite users' positive perceptions, they also acknowledged certain challenges relating to the usage and risk of bias that would need to be addressed.Registration: PROSPERO database: (CRD42020220320).

npj Digital MedicineVol. 7(1)
University College Dublin (IE), Brigham and Women's Hospital (US), Harvard University (US), Newcastle upon Tyne Hospitals NHS Foundation Trust (GB), Freeman Hospital (GB), Newcastle University (GB)
National Institute for Health and Care Research, Department of Health and Social Care, Newcastle University
Peace, Justice and strong institutions
Openalex Percentile: Top 1%
Patient-Provider Communication in Healthcare
17.84
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