scholarly journals Leveraging the trust of nurses to advance a digital agenda in Europe: a critical review of health policy literature

2021 ◽  
Vol 1 ◽  
pp. 26
Author(s):  
Paul De Raeve ◽  
Patricia M. Davidson ◽  
Franklin A. Shaffer ◽  
Eric Pol ◽  
Amit Kumar Pandey ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Policy ◽  
Nurse Practitioners ◽  
White Paper ◽  
Health Data ◽  
Nursing Workforce ◽  
Preventative Care ◽  
Validity And Reliability ◽  
Nursing Time

This article is a critical and integrative review of health policy literature examining artificial intelligence (AI) and its implications for healthcare systems and the frontline nursing workforce. A key focus is on co-creation as essential for the deployment and adoption of AI. Our review hinges on the European Commission’s White Paper on Artificial Intelligence from 2020, which provides a useful roadmap. The value of health data spaces and electronic health records (EHRs) is considered; and the role of advanced nurse practitioners in harnessing the potential of AI tools in their practice is articulated. Finally, this paper examines “trust” as a precondition for the successful deployment and adoption of AI in Europe. AI applications in healthcare can enhance safety and quality, and mitigate against common risks and challenges, once the necessary level of trust is achieved among all stakeholders. Such an approach can enable effective preventative care across healthcare settings, particularly community and primary care. However, the acceptance of AI tools in healthcare is dependent on the robustness, validity and reliability of data collected and donated from EHRs. Nurse stakeholders have a key role to play in this regard, since trust can only be fostered through engaging frontline end-users in the co-design of EHRs and new AI tools. Nurses hold an intimate understanding of the direct benefits of such technology, such as releasing valuable nursing time for essential patient care, and empowering patients and their family members as recipients of nursing care. This article brings together insights from a unique group of stakeholders to explore the interaction between AI, the co-creation of data spaces and EHRs, and the role of the frontline nursing workforce. We identify the pre-conditions needed for successful deployment of AI and offer insights regarding the importance of co-creating the future European Health Data Space.

scholarly journals Leveraging the trust of nurses to advance a digital agenda in Europe: a critical review of health policy literature

2021 ◽  
Vol 1 ◽  
pp. 26
Author(s):  
Paul De Raeve ◽  
Patricia M. Davidson ◽  
Franklin A. Shaffer ◽  
Eric Pol ◽  
Amit Kumar Pandey ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Policy ◽  
Nurse Practitioners ◽  
White Paper ◽  
Health Data ◽  
Nursing Workforce ◽  
Preventative Care ◽  
Validity And Reliability ◽  
Nursing Time

This article is a critical and integrative review of health policy literature examining artificial intelligence (AI) and its implications for healthcare systems and the frontline nursing workforce. A key focus is on co-creation as essential for the deployment and adoption of AI. Our review hinges on the European Commission’s White Paper on Artificial Intelligence from 2020, which provides a useful roadmap. The value of health data spaces and electronic health records (EHRs) is considered; and the role of advanced nurse practitioners in harnessing the potential of AI tools in their practice is articulated. Finally, this paper examines “trust” as a precondition for the successful deployment and adoption of AI in Europe. AI applications in healthcare can enhance safety and quality, and mitigate against common risks and challenges, once the necessary level of trust is achieved among all stakeholders. Such an approach can enable effective preventative care across healthcare settings, particularly community and primary care. However, the acceptance of AI tools in healthcare is dependent on the robustness, validity and reliability of data collected and donated from EHRs (Smart4Health & InteropEHRate). Nurse stakeholders have a key role to play in this regard, since trust can only be fostered through engaging frontline end-users in the co-design of EHRs and new AI tools. Nurses hold an intimate understanding of the direct benefits of such technology, such as releasing valuable nursing time for essential patient care, and empowering patients and their family members as recipients of nursing care. This article brings together insights from a unique group of stakeholders to explore the interaction between AI, the co-creation of data spaces and EHRs, and the role of the frontline nursing workforce. We identify the pre-conditions needed for successful deployment of AI and offer insights regarding the importance of co-creating the future European Health Data Space.

scholarly journals Data for sale: trust, confidence and sharing health data with commercial companies

2021 ◽  
pp. medethics-2021-107464
Author(s):  
Mackenzie Graham
Keyword(s):  
Artificial Intelligence ◽  
Data Sharing ◽  
Health Data ◽  
Computing Power ◽  
Health Institutions

Powered by ‘big health data’ and enormous gains in computing power, artificial intelligence and related technologies are already changing the healthcare landscape. Harnessing the potential of these technologies will necessitate partnerships between health institutions and commercial companies, particularly as it relates to sharing health data. The need for commercial companies to be trustworthy users of data has been argued to be critical to the success of this endeavour. I argue that this approach is mistaken. Our interactions with commercial companies need not, and should not, be based on trust. Rather, they should be based on confidence. I begin by elucidating the differences between trust, reliability, and confidence, and argue that trust is not the appropriate attitude to adopt when it comes to sharing data with commercial companies. I argue that what we really should want is confidence in a system of data sharing. I then provide an outline of what a confidence-worthy system of data sharing with commercial companies might look like, and conclude with some remarks about the role of trust within this system.

Gay Men Talking About Health

2011 ◽  
Vol 6 (3) ◽  
pp. 182-193 ◽  
Author(s):  
Jeffery Adams ◽  
Virginia Braun ◽  
Tim McCreanor
Keyword(s):  
Health Policy ◽  
Health Services ◽  
Focus Groups ◽  
Gay Men ◽  
Functional Ability ◽  
Health Data

Defining and describing health has traditionally been the role of medical experts. Although a rich literature has recently established the importance of lay accounts of health, one important gap relates to gay men’s accounts of health. Data from 11 focus groups involving 45 gay men were thematically analyzed to investigate gay men’s views of health. Two contrasting positions on a possible relationship between sexuality and health—there is no link or there is a definite link—were identified. In addition, five key ways gay men talked about health were identified: health is the absence of disease, is functional ability, is fitness and exercise, is psychological, and is multifaceted. Although there are similarities in the ways gay and other men talk about health, important differences exist, which suggest that issues of sexuality need to be considered by health policy and service planners so that responsive health services can be provided.

scholarly journals Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology

2018 ◽  
Vol 69 (2) ◽  
pp. 120-135 ◽  
Author(s):  
An Tang ◽  
Roger Tam ◽  
Alexandre Cadrin-Chênevert ◽  
Will Guest ◽  
Jaron Chong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Patient Care ◽  
Working Group ◽  
White Paper ◽  
Patient Centered ◽  
Computing Power ◽  
Implementation Phase ◽  
Early Adoption ◽  
Canadian Association

Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada.

scholarly journals Pembuatan Aplikasi Sistem Informasi Kesehatan (SIFKES) untuk Meningkatkan Integrasi Data Puskesmas di Kota Jambi Berbasis Web Service

2018 ◽  
Vol 6 (2) ◽  
pp. 150-156
Author(s):  
Lailyn Puad ◽  
Windy Adriana
Keyword(s):  
Artificial Intelligence ◽  
Quality Of Service ◽  
Web Service ◽  
Health Data ◽  
Health Centers ◽  
Classic Problem ◽  
Health Institutions ◽  
The Web

Health is one parameter that is often used as a measure of the welfare of a region. Jambi City has 20 health centers spread across 8 sub-districts and has a duty to serve the entire community of Jambi City. The classic problem that always arises in the integration of data raises a mature unsuitability to the accuracy of the patient's diagnosis. Web services are the perfect answer to use as a data centralization medium, with their superiority in terms of capacity, speed and security of the web service very apt to be implemented in the integration of crucial data such as health data. Supported by artificial intelligence applied to be used as an assistant to the role of a physician in the diagnosis process, this application is suitable for use on every line of health institutions as a step to improve the quality of service to the community.

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

Artificial intelligence and the management transformation

2020 ◽  
Vol 16 (4) ◽  
pp. 600-612
Author(s):  
L.F. Nikulin ◽  
V.V. Velikorossov ◽  
S.A. Filin ◽  
A.B. Lanchakov
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Soft Power ◽  
Process Integration ◽  
Management Practice ◽  
Scientific School ◽  
Strategic Culture ◽  
Analysis And Synthesis ◽  
And Training

Subject. The article discusses how management transforms as artificial intelligence gets more important in governance, production and social life. Objectives. We identify and substantiate trends in management transformation as artificial intelligence evolves and gets more important in governance, production and social life. The article also provides our suggestions for management and training of managers dealing with artificial intelligence. Methods. The study employs methods of logic research, analysis and synthesis through the systems and creative approach, methodology of technological waves. Results. We analyzed the scope of management as is and found that threats and global challenges escalate due to the advent of artificial intelligence. We provide the rationale for recognizing the strategic culture as the self-organizing system of business process integration. We suggest and substantiate the concept of soft power with reference to strategic culture, which should be raised, inter alia, through the scientific school of conflict studies. We give our recommendations on how management and training of managers should be improved in dealing with artificial intelligence as it evolves. The novelty hereof is that we trace trends in management transformation as the role of artificial intelligence evolves and growth in governance, production and social life. Conclusions and Relevance. Generic solutions are not very effective for the Russian management practice during the transition to the sixth and seventh waves of innovation. Any programming product represents artificial intelligence, which simulates a personality very well, though unable to substitute a manager in motivating, governing and interacting with people.

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