Artificial intelligence

McGrow, Kathleen

doi:10.1097/01.nurse.0000577716.57052.8d

Cited by 86 publications

(71 citation statements)

References 3 publications

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“…In the hospital sector, AIHTs such as predictive algorithms and CDSSs have been shown to improve decision making and nursing activities (eg, documentation), allowing more time for patient care [69][70][71][72][73][74][75][76]. For example, one study noted that a predictive algorithm used for the identification of nursing diagnoses reduced the time spent on decision making from 35.5 min to 19.8 min [61].…”

Section: Clinical Practicementioning

confidence: 99%

“…The results of the review found numerous implications for nursing administration. Some articles discussed the use of AIHTs to assist nurses with automated analysis of patient data [69][70][71][72][73][74][75][76]. Other administration applications of AIHTs included scheduling nursing tasks [66], reducing documentation burden [80], and assisting nurses with triaging patients through AIHT computer systems [14], which could potentially aid in streamlining workflow processes and improving the efficiency and accuracy of patient care provided.…”

Section: Nursing Administrationmentioning

confidence: 99%

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Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Buchanan¹,

Howitt²,

Wilson³

et al. 2020

JMIR Nursing

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Background: Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses-the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers. Objective: This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research. This review summarizes the findings from 3 research questions, examining how these emerging trends might influence the roles and functions of nurses and compassionate nursing care over the next 10 years and beyond. Methods: Using an established scoping review methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Center, Scopus, Web of Science, and ProQuest databases were searched. In addition to the electronic database searches, a targeted website search was performed to access relevant gray literature. Abstracts and full-text studies were independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included articles focused on nursing and digital health technologies that incorporate AI. Data were charted using structured forms and narratively summarized. Results: A total of 131 articles were retrieved from the scoping review for the 3 research questions that were the focus of this manuscript (118 from database sources and 13 from targeted websites). Emerging AI technologies discussed in the review included predictive analytics, smart homes, virtual health care assistants, and robots. The results indicated that AI has already begun to influence nursing roles, workflows, and the nurse-patient relationship. In general, robots are not viewed as replacements for nurses. There is a consensus that health technologies powered by AI may have the potential to enhance nursing practice. Consequently, nurses must proactively define how person-centered compassionate care will be preserved in the age of AI. Conclusions: Nurses have a shared responsibility to influence decisions related to the integration of AI into the health system and to ensure that this change is introduced in a way that is ethical and aligns with core nursing values such as compassionate care. Furthermore, nurses must advocate for patient and nursing involvement in all aspects of the design, implementation, and evaluation of these technologies.

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Section: Clinical Practicementioning

confidence: 99%

Section: Nursing Administrationmentioning

confidence: 99%

Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Buchanan¹,

Howitt²,

Wilson³

et al. 2020

JMIR Nursing

View full text Add to dashboard Cite

show abstract

“…Artificial intelligence (AI) and big data analytics play an increasingly important role in nursing documentation and planning, risk assessment and prediction, and clinical decision-making (Brennan & Bakken, 2015;Kuziemsky et al, 2019;McGrow, 2019). In ambulant and stationary long-term care, ambient assisted living systems combine monitoring and surveillance tools with smart home technology (Sapci & Sapci, 2019;Sixsmith, 2013).…”

Section: Introductionmentioning

confidence: 99%

Guardians of humanity? The challenges of nursing practice in the digital age

Rubeis

2020

Nursing Philosophy

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“…Therefore, it is important for nurses to understand how AIHTs can be integrated into the conceptual foundation of nursing practice as they cocreate new models, frameworks, and theories that may be required to support the emerging technologies. This is particularly important given the increasing usage of AIHTs to enhance clinical decision making [14] and their potential to influence the traditional nurse-patient relationship.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, virtual avatar apps that integrate chatbot technology to simulate interactive human conversations between health professionals and patients are growing in popularity [18,19]. Furthermore, social robots with natural language processing abilities [20] that enable them to understand, analyze, and manipulate data and generate language [14] are being increasingly used to provide additional companionship for residents in long-term care homes under the supervision of nurses. These technological advances are expected to cause considerable changes to the nursing landscape over the next decade [9], and nursing education as well as nurse educators will be at the forefront of these changes [21].…”

Section: Introductionmentioning

confidence: 99%

Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

Buchanan¹,

Howitt²,

Wilson³

et al. 2021

JMIR Nursing

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Background It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature. Objective A scoping review was conducted to summarize the current and predicted influences of AIHTs on nursing education over the next 10 years and beyond. Methods This scoping review followed a previously published protocol from April 2020. Using an established scoping review methodology, the databases of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest were searched. In addition to the use of these electronic databases, a targeted website search was performed to access relevant grey literature. Abstracts and full-text studies were independently screened by two reviewers using prespecified inclusion and exclusion criteria. Included literature focused on nursing education and digital health technologies that incorporate AI. Data were charted using a structured form and narratively summarized into categories. Results A total of 27 articles were identified (20 expository papers, six studies with quantitative or prototyping methods, and one qualitative study). The population included nurses, nurse educators, and nursing students at the entry-to-practice, undergraduate, graduate, and doctoral levels. A variety of AIHTs were discussed, including virtual avatar apps, smart homes, predictive analytics, virtual or augmented reality, and robots. The two key categories derived from the literature were (1) influences of AI on nursing education in academic institutions and (2) influences of AI on nursing education in clinical practice. Conclusions Curricular reform is urgently needed within nursing education programs in academic institutions and clinical practice settings to prepare nurses and nursing students to practice safely and efficiently in the age of AI. Additionally, nurse educators need to adopt new and evolving pedagogies that incorporate AI to better support students at all levels of education. Finally, nursing students and practicing nurses must be equipped with the requisite knowledge and skills to effectively assess AIHTs and safely integrate those deemed appropriate to support person-centered compassionate nursing care in practice settings. International Registered Report Identifier (IRRID) RR2-10.2196/17490

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Artificial intelligence

Abstract: Artificial intelligence (AI) is a transformational technology that will affect all healthcare providers. This article offers an overview of basic AI concepts and the role of nurses in embracing this technology in healthcare settings.

Cited by 86 publications

References 3 publications

Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Guardians of humanity? The challenges of nursing practice in the digital age

Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

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