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Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative
被引:112
|作者:
Ronquillo, Charlene Esteban
[1
,2
,3
]
Peltonen, Laura-Maria
[3
,4
]
Pruinelli, Lisiane
[5
]
Chu, Charlene H.
[6
]
Bakken, Suzanne
[7
,8
]
Beduschi, Ana
[9
]
Cato, Kenrick
[7
]
Hardiker, Nicholas
[10
]
Junger, Alain
[11
]
Michalowski, Martin
[5
]
Nyrup, Rune
[12
]
Rahimi, Samira
[13
]
Reed, Donald Nigel
[14
]
Salakoski, Tapio
[15
]
Salantera, Sanna
[4
,16
]
Walton, Nancy
[1
,17
,18
]
Weber, Patrick
[19
,20
]
Wiegand, Thomas
[21
,22
,23
]
Topaz, Maxim
[3
,7
]
机构:
[1] Ryerson Univ, Fac Community Serv, Daphne Cockwell Sch Nursing, Toronto, ON, Canada
[2] Univ British Columbia Okanagan, Fac Hlth & Social Dev, Sch Nursing, Kelowna, BC, Canada
[3] Int Med Informat Assoc, Student & Emerging Professionals Special Interest, Geneva, Switzerland
[4] Univ Turku, Dept Nursing Sci, Turku, Finland
[5] Univ Minnesota, Sch Nursing, Minneapolis, MN USA
[6] Univ Toronto, Lawrence S Bloomberg Fac Nursing, Toronto, ON, Canada
[7] Columbia Univ, Sch Nursing, Data Sci Inst, Dept Biomed Informat, New York, NY USA
[8] Columbia Univ, Precis Symptom Self Management PriSSM Ctr, Reducing Hlth Dispar Informat Training Program RH, New York, NY USA
[9] Univ Exeter, Law Sch, Exeter, Devon, England
[10] Univ Huddersfield, Sch Human & Hlth Sci, Huddersfield, W Yorkshire, England
[11] Ctr Hosp Univ Vaudois CHUV Lausanne, Nursing Informat Syst Unit, Nursing Direct, Lausanne, Switzerland
[12] Univ Cambridge, Leverhulme Ctr Future Intelligence, Cambridge, England
[13] McGill Univ, Lady Davis Inst Med Res, Dept Family Med, Mila Quebec Artificial Intelligence,Jewish Gen Ho, Montreal, PQ, Canada
[14] Univ Exeter, Coll Med & Hlth, Exeter, Devon, England
[15] Univ Turku, Dept Math & Stat, Turku, Finland
[16] Turku Univ Hosp, Turku, Finland
[17] Womens Coll Hosp, Res Eth Board, Toronto, ON, Canada
[18] Hlth Canada & Publ Hlth Agcy Canadas Res Eth Boar, Toronto, ON, Canada
[19] NICE Comp SA, Lausanne, Switzerland
[20] European Federat Med Informat EFMI, Copenhagen, Denmark
[21] ITU WHO Focus Grp Artificial Intelligence Hlth FG, Geneva, Switzerland
[22] Fraunhofer Heinrich Hertz Inst, Berlin, Germany
[23] Berlin Inst Technol, Berlin, Germany
基金:
英国惠康基金;
关键词:
health services research;
information technology;
leadership;
management;
nurse roles;
policy;
politics;
technology;
workforce issues;
SOCIAL-JUSTICE;
BIG DATA;
NURSES;
RECOMMENDATIONS;
HEALTH;
INFORMATICS;
CARE;
D O I:
10.1111/jan.14855
中图分类号:
R47 [护理学];
学科分类号:
1011 ;
摘要:
Aim To develop a consensus paper on the central points of an international invitational think-tank on nursing and artificial intelligence (AI). Methods We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3-day invitational think tank in autumn 2019. Activities included a pre-event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities. Implications for nursing Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice. Conclusion There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems. Impact We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.
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页码:3707 / 3717
页数:11
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