scholarly journals Nursing Education in the Age of Artificial Intelligence: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Christine Buchanan ◽  
M. Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Nursing Education ◽  
Nursing Students ◽  
Scoping Review ◽  
Digital Health ◽  
Clinical Care ◽  
Grey Literature ◽  
Health Technologies ◽  
Cochrane Database ◽  
Educational Requirements

BACKGROUND It is predicted that artificial intelligence will transform nursing across various domains of nursing practice: administration, clinical care, education, policy, and research. However, little synthesis has been completed exploring how artificial intelligence technologies will influence nursing education specifically. OBJECTIVE A scoping review was conducted to explore how artificial intelligence-driven digital health technologies are expected to influence nursing education over the next ten years and beyond. METHODS This scoping review followed the previously published protocol from April 2020. Using an established scoping review methodology, 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 databases 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 pre-specified inclusion and exclusion criteria. Included literature focused on nursing and digital health technologies that incorporate artificial intelligence. Data was charted using a piloted 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 and nursing students at the undergraduate/entry levels, graduate, and doctoral levels. A variety of artificial intelligence technologies were discussed, including virtual nursing applications and robots. Key categories derived from the literature included: (1) educational requirements for nurses at the entry level, graduate and doctoral levels, (2) educational requirements for nurses in clinical practice, and (3) changes to the delivery of nursing education. CONCLUSIONS Nurses need to be better equipped to evaluate and integrate artificial intelligence in practice settings, and imminent changes are needed within nursing education programs to prepare nurses to use these technologies. Additionally, nurse educators need to understand how to use artificial intelligence in their teaching practices at the undergraduate and post-graduate levels. INTERNATIONAL REGISTERED REPORT RR2-10.2196/17490

scholarly journals Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

JMIR Nursing ◽  
10.2196/23933 ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. e23933
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Nursing Education ◽  
Clinical Practice ◽  
Nursing Students ◽  
Scoping Review ◽  
Nurse Educators ◽  
Clinical Care ◽  
Grey Literature ◽  
Academic Institutions ◽  
Health Technologies

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

scholarly journals Nursing in the Age of Artificial Intelligence: Protocol for a Scoping Review

10.2196/17490 ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. e17490 ◽  
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Education Policy ◽  
Scoping Review ◽  
Digital Health ◽  
Clinical Care ◽  
Electronic Database ◽  
Health Technologies ◽  
Care Education ◽  
Emerging Trends ◽  
Briefing Paper

Background It is predicted that digital health technologies that incorporate artificial intelligence will transform health care delivery in the next decade. Little research has explored how emerging trends in artificial intelligence–driven digital health technologies may influence the relationship between nurses and patients. Objective The purpose of this scoping review is to summarize the findings from 4 research questions regarding emerging trends in artificial intelligence–driven digital health technologies and their influence on nursing practice across the 5 domains outlined by the Canadian Nurses Association framework: administration, clinical care, education, policy, and research. Specifically, this scoping review will examine how emerging trends will transform the roles and functions of nurses over the next 10 years and beyond. Methods Using an established scoping review methodology, 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 databases were searched. In addition to the electronic database searches, a targeted website search will be performed to access relevant grey literature. Abstracts and full-text studies will be independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included literature will focus on nursing and digital health technologies that incorporate artificial intelligence. Data will be charted using a structured form and narratively summarized. Results Electronic database searches have retrieved 10,318 results. The scoping review and subsequent briefing paper will be completed by the fall of 2020. Conclusions A symposium will be held to share insights gained from this scoping review with key thought leaders and a cross section of stakeholders from administration, clinical care, education, policy, and research as well as patient advocates. The symposium will provide a forum to explore opportunities for action to advance the future of nursing in a technological world and, more specifically, nurses’ delivery of compassionate care in the age of artificial intelligence. Results from the symposium will be summarized in the form of a briefing paper and widely disseminated to relevant stakeholders. International Registered Report Identifier (IRRID) DERR1-10.2196/17490

scholarly journals Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Scoping Review ◽  
Predictive Analytics ◽  
Digital Health ◽  
Shared Responsibility ◽  
Compassionate Care ◽  
Health Technologies ◽  
Emerging Trends ◽  
Research Questions

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. INTERNATIONAL REGISTERED REPORT RR2-10.2196/17490

scholarly journals Procurement of innovation terminology usage in health care: A scoping review protocol

2020 ◽  
Author(s):  
Margaret R. Andrews ◽  
Romualdo Ramos ◽  
Martina Ahlberg ◽  
Jan A. Hazelzet ◽  
Erik M. van Raaij ◽  
...  
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
New Technologies ◽  
Scientific Literature ◽  
Digital Health ◽  
Supply And Demand ◽  
Grey Literature ◽  
Health Care Settings ◽  
Health Technologies ◽  
Policy Tool

AbstractBackgroundAlthough procurement of innovation is an established policy tool used to stimulate collaboration between supply- and demand-side entities during the development of new technologies, there is little scientific literature describing the process as applied in health care settings. Furthermore, what literature exists contains inconsistencies of terms, definitions, and/or concepts related to procurement of innovation. This protocol details our process for a systematic scoping review to describe the current scope of literature and to provide terminology clarification.MethodsA search strategy will be used to search PubMed, EMBASE [OVID], CINAHL [EBSCO], PsycINFO [ProQUEST], ABI/INFORM, ISI Web of Knowledge, EBSCO, JSTOR, the Cochrane Database of Systematic Reviews, and Google Scholar; grey literature, non-scientific reports, policy documents and expert recommendations will also be considered as additional sources for texts. Two researchers will screen titles and abstracts for inclusion/exclusion criteria, followed by full texts. We will extract the following data, if applicable: title, authors, date, author affiliations, country, journal/publication characteristics, setting, aims/purpose, methodology, sample characteristics, assessment/evaluation tools, outcome parameters, key findings, relevance, and terminology usage/definitions. Results will be presented narratively and visually.DiscussionThis paper describes the steps of our proposed systematic scoping review to identify and analyse scientific and non-scientific literature related to procurement of innovation and/or innovation of procurement in health care settings, with a particular focus on digital health technologies. Results are intended to demonstrate the current scope of literature, to provide clarity in language and therefore to serve as a first step for further research in this growing field.

scholarly journals Defining compassion in the digital health age: protocol for a scoping review

BMJ Open ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. e026338 ◽  
Author(s):  
David Wiljer ◽  
Rebecca Charow ◽  
Helen Costin ◽  
Lydia Sequeira ◽  
Melanie Anderson ◽  
...  
Keyword(s):  
Leadership Development ◽  
Scoping Review ◽  
Professional Education ◽  
Digital Health ◽  
Clinical Care ◽  
Compassionate Care ◽  
Screening Process ◽  
Quality Healthcare ◽  
Health Technologies ◽  
Full Text Review

IntroductionThe notion of compassion and compassionate care is playing an increasingly important role in health professional education and in the delivery of high-quality healthcare. Digital contexts, however, are not considered in the conceptualisation of compassionate care, nor is there guidance on how compassionate care is to be exercised while using digital health technologies. The widespread diffusion of digital health technologies provides new contexts for compassionate care, with both opportunities for new forms and instantiations of compassion as well as new challenges. How compassion is both understood and enacted within this evolving, digital realm has not been synthesised.Methods and analysisThis scoping review protocol follows Arksey and O’Malley’s methodology to examine dimensions of compassionate professional practice when digital technologies are integrated into clinical care. Relevant peer-reviewed literature will be identified using a search strategy developed by medical librarians, which applies to six databases of medical, computer and information systems disciplines. Eligibility of articles will be determined using the two-stage screening process consisting of (1) title and abstract scan, and (2) full-text review. Screening, abstracting and charting will be conducted by two independent reviewers, with a third reviewer available for resolution when consensus is not achieved. In order to look at the range of current research in this area, extracted data will be thematically analysed and validated by content experts. Descriptive statistics will be calculated where necessary.Ethics and disseminationResearch ethics approval and consent to participate is not required for this scoping review. The results of the review will inform resource development and strategy for Associated Medical Services (AMS) Healthcare, a Canadian charitable organisation at the forefront of advancing research and leadership development in health and humanities, as part of the AMS Phoenix Project: A Call to Caring, particularly for digital professionalism frameworks so that they are inclusive of a compassion competency.

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

JMIR Nursing ◽  
10.2196/23939 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e23939
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Scoping Review ◽  
Predictive Analytics ◽  
Digital Health ◽  
Shared Responsibility ◽  
Compassionate Care ◽  
Health Technologies ◽  
Emerging Trends ◽  
Research Questions

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. International Registered Report Identifier (IRRID) RR2-10.2196/17490

scholarly journals Artificial intelligence for good health: a scoping review of the ethics literature

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kathleen Murphy ◽  
Erica Di Ruggiero ◽  
Ross Upshur ◽  
Donald J. Willison ◽  
Neha Malhotra ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Global Health ◽  
Population Health ◽  
Health Systems ◽  
Scoping Review ◽  
Industrial Revolution ◽  
Ethical Issues ◽  
Grey Literature ◽  
Ethical Implications

Abstract Background Artificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective? Methods Eight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed. Results Upon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs). Conclusions The ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.

scholarly journals Scoping review protocol: bladder cancer in Nigeria: what are the gaps in clinical care and research?

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e041894
Author(s):  
Joyce Kibaru ◽  
Pinky Kotecha ◽  
Abdulkarim Muhammad Iya ◽  
Beth Russell ◽  
Muzzammil Abdullahi ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Scoping Review ◽  
Low Income ◽  
Clinical Care ◽  
Grey Literature ◽  
Case Series ◽  
Cochrane Library ◽  
Future Research ◽  
Scoping Reviews ◽  
Local Risk

IntroductionBladder cancer (BC) is the 10th common cancer worldwide and ranks seventh in Nigeria. This scoping review aims to identify the gaps in clinical care and research of BC in Nigeria as part of the development of a larger national research programme aiming to improve outcomes and care of BC.Methods and analysisThis review will be conducted according to Arksey and O’Malley scoping review methodology framework. The following electronic databases will be searched: Medline (using the PubMed interface), Ovid Gateway (Embase and Ovid), Cochrane library and Open Grey literature. Two independent reviewers will screen titles and abstracts and subsequently screen full-text studies for inclusion, any lack of consensus will be discussed with a third reviewer. Any study providing insight into the epidemiology or treatment pathway of BC (RCTs, observations, case series, policy paper) will be included. A data chart will be used to extract relevant data from the included studies. Results will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. A consultation process will be carried out with a multidisciplinary team of Nigerian healthcare professionals, patients and scientists.Ethics and disseminationThe results will be disseminated through peer-reviewed publications. By highlighting the key gaps in the literature, this review can provide direction for future research and clinical guidelines in Nigeria (and other low-income and middle-income countries), where BC is more prevalent due to local risk factors and healthcare settings.

scholarly journals Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ania Syrowatka ◽  
Masha Kuznetsova ◽  
Ava Alsubai ◽  
Adam L. Beckman ◽  
Paul A. Bain ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Real Time ◽  
Scoping Review ◽  
Grey Literature ◽  
Use Cases ◽  
Outbreak Detection ◽  
Response To Treatment ◽  
Pandemic Preparedness ◽  
Modeling Approaches

AbstractArtificial intelligence (AI) represents a valuable tool that could be widely used to inform clinical and public health decision-making to effectively manage the impacts of a pandemic. The objective of this scoping review was to identify the key use cases for involving AI for pandemic preparedness and response from the peer-reviewed, preprint, and grey literature. The data synthesis had two parts: an in-depth review of studies that leveraged machine learning (ML) techniques and a limited review of studies that applied traditional modeling approaches. ML applications from the in-depth review were categorized into use cases related to public health and clinical practice, and narratively synthesized. One hundred eighty-three articles met the inclusion criteria for the in-depth review. Six key use cases were identified: forecasting infectious disease dynamics and effects of interventions; surveillance and outbreak detection; real-time monitoring of adherence to public health recommendations; real-time detection of influenza-like illness; triage and timely diagnosis of infections; and prognosis of illness and response to treatment. Data sources and types of ML that were useful varied by use case. The search identified 1167 articles that reported on traditional modeling approaches, which highlighted additional areas where ML could be leveraged for improving the accuracy of estimations or projections. Important ML-based solutions have been developed in response to pandemics, and particularly for COVID-19 but few were optimized for practical application early in the pandemic. These findings can support policymakers, clinicians, and other stakeholders in prioritizing research and development to support operationalization of AI for future pandemics.

scholarly journals The Real Era of the Art of Medicine Begins with Artificial Intelligence (Preprint)

2019 ◽  
Author(s):  
Bertalan Meskó
Keyword(s):  
Artificial Intelligence ◽  
Digital Health ◽  
Medical Science ◽  
Three Dimensional ◽  
Three Dimensional Printing ◽  
The Real ◽  
Art Of Medicine ◽  
Health Technologies ◽  
Based Medicine ◽  
Dimensional Printing

UNSTRUCTURED Physicians have been performing the art of medicine for hundreds of years, and since the ancient era, patients have turned to physicians for help, advice, and cures. When the fathers of medicine started writing down their experience, knowledge, and observations, treating medical conditions became a structured process, with textbooks and professors sharing their methods over generations. After evidence-based medicine was established as the new form of medical science, the art and science of medicine had to be connected. As a result, by the end of the 20th century, health care had become highly dependent on technology. From electronic medical records, telemedicine, three-dimensional printing, algorithms, and sensors, technology has started to influence medical decisions and the lives of patients. While digital health technologies might be considered a threat to the art of medicine, I argue that advanced technologies, such as artificial intelligence, will initiate the real era of the art of medicine. Through the use of reinforcement learning, artificial intelligence could become the stethoscope of the 21st century. If we embrace these tools, the real art of medicine will begin now with the era of artificial intelligence.

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