Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol

被引:0
|
作者
Karunananthan, Sathya [1 ,2 ]
Rahgozar, Arya [3 ,4 ]
Hakimjavadi, Ramtin [2 ,5 ]
Yan, Hui [2 ,5 ]
Dalsania, Kunal A. [1 ,2 ]
Bergman, Howard [6 ]
Ghose, Bishwajit [7 ]
Laplante, Jim [8 ]
McCutcheon, Tess [9 ]
McIsaac, Daniel I. [10 ]
Rahimi, Samira Abbasgholizadeh [6 ]
Sourial, Nadia [11 ,12 ]
Thandi, Manpreet [13 ]
Wong, Sabrina T. [13 ]
Liddy, Clare [4 ,9 ]
机构
[1] Univ Ottawa, Interdisciplinary Sch Hlth Sci, Ottawa, ON, Canada
[2] Bruyere Res Inst, Ottawa, ON, Canada
[3] Ottawa Hosp Res Inst, Ottawa, ON, Canada
[4] Univ Ottawa, Dept Family Med, Ottawa, ON, Canada
[5] Univ Ottawa, Fac Med, Ottawa, ON, Canada
[6] McGill Univ, Dept Family Med, Montreal, PQ, Canada
[7] Univ Ottawa, Fac Hlth Sci, Ottawa, ON, Canada
[8] Care Partner, Ottawa, ON, Canada
[9] Bruyere Res Inst, CT Lamont Primary Hlth Care Res Ctr, Ottawa, ON, Canada
[10] Ottawa Hosp, Anesthesiol & Pain Med, Ottawa, ON, Canada
[11] Univ Montreal, Dept Hlth Management Evaluat & Policy, Montreal, PQ, Canada
[12] Ctr Hosp Univ Montreal, Rech Ctr, Montreal, PQ, Canada
[13] Univ British Columbia, Ctr Hlth Serv & Policy Res, Vancouver, BC, Canada
来源
BMJ OPEN | 2023年 / 13卷 / 12期
基金
加拿大健康研究院;
关键词
Health Services for the Aged; Aging; GERIATRIC MEDICINE; Health informatics; Clinical Decision-Making; Systematic Review; OLDER-PEOPLE; INSTRUMENTS; ACCURACY;
D O I
10.1136/bmjopen-2023-076918
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IntroductionRapid population ageing and associated health issues such as frailty are a growing public health concern. While early identification and management of frailty may limit adverse health outcomes, the complex presentations of frailty pose challenges for clinicians. Artificial intelligence (AI) has emerged as a potential solution to support the early identification and management of frailty. In order to provide a comprehensive overview of current evidence regarding the development and use of AI technologies including machine learning and deep learning for the identification and management of frailty, this protocol outlines a scoping review aiming to identify and present available information in this area. Specifically, this protocol describes a review that will focus on the clinical tools and frameworks used to assess frailty, the outcomes that have been evaluated and the involvement of knowledge users in the development, implementation and evaluation of AI methods and tools for frailty care in clinical settings.Methods and analysisThis scoping review protocol details a systematic search of eight major academic databases, including Medline, Embase, PsycInfo, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Ageline, Web of Science, Scopus and Institute of Electrical and Electronics Engineers (IEEE) Xplore using the framework developed by Arksey and O'Malley and enhanced by Levac et al and the Joanna Briggs Institute. The search strategy has been designed in consultation with a librarian. Two independent reviewers will screen titles and abstracts, followed by full texts, for eligibility and then chart the data using a piloted data charting form. Results will be collated and presented through a narrative summary, tables and figures.Ethics and disseminationSince this study is based on publicly available information, ethics approval is not required. Findings will be communicated with healthcare providers, caregivers, patients and research and health programme funders through peer-reviewed publications, presentations and an infographic.Registration detailsOSF Registries (https://doi.org/10.17605/OSF.IO/T54G8).
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页数:7
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