Evaluation of End-User Participation in Artificial Intelligence Nursing Projects.

Artificial Intelligence (AI) projects in healthcare, particularly in nursing, currently gain relevance but encounter challenges in user acceptance. Active participation of end-users in the development and implementation of AI can enhance acceptance. This study proposes a scale to measure the degree of end-user participation in AI development and implementation for nursing on the project level, rated by project managers. It employs the qualitative-analytical COARSE method for scale development and evaluation. The instrument includes 11 items across two sub-scales: activities for active participation of end-users and empowerment activities. It highlights the importance of the measurement's purpose and consequences for interpreting the results of the evaluated degree of end-user participation. The study points to future research opportunities, underscored by the need for psychometric validation, such as reliability and validity.

Continuing Educational Program in Nursing Informatics for Greek Nurses.

Nurses are required to adapt to a complex and rapidly evolving environment that incorporates new IT technologies. Continuing, lifelong learning, especially in the fast-growing fields of Nursing Informatics, eHealth and related Information and Communication Technologies, is vital to the professionalism of nurses. The study presents the curriculum development and implementation of the educational project entitled "Training of Nurses in Nursing Informatics and Information and Communication Technologies (ICT)" which has been designed and offered to Greek nurses as a continuing - lifelong online educational program by the Health Informatics Laboratory of the National and Kapodistrian University of Athens. The training material was created in three modules and 29 sub-modules, considering the new advancements and recommended competencies, necessary for the nurse, in the fields of Nursing Informatics and ICT. So far, eight training cycle courses have been offered to 1388 nurses, free of charge. Each course integrates synchronous and asynchronous distance learning methods and requires a workload of 70 hours over 10 weeks. The initial evaluation of the course by the participants, concerning its effectiveness, usefulness, and innovation are very encouraging.

Reinterpreting the Nursing Record for an Electronic Context: Development Principles.

The full potential for electronic health record systems in facilitating a positive transformation in care, with improvements in quality and safety, has yet to be realised. There remains a need to reconceptualise the structure, content and use of the nursing component of electronic health record systems. The aim of this study was to engage and involve a diverse group of stakeholders, including nurses and electronic health record system developers, in exploring together both issues and possible new approaches to documentation that better fit with practice, and that facilitate the optimal use of recorded data. Three focus groups were held in the UK and USA, using a semi-structured interview guide, and a common reflexive approach to analysis. The findings were synthesised into themes that were further developed into a set of development principles that might be used to inform a novel electronic health record system specification to support nursing practice.

Design and Development of a Fully Intelligent Nursing Information System Based on International Standard Nursing Terminology.

OBJECTIVE: Design and develop a Clinical Care Classification (CCC) nursing information system aligned with nursing terminology CCC, emphasizing standard procedures and a responsibility-based nursing model to enhance efficiency and quality of care. METHODS: Conduct thorough investigation into clinical nursing informatics needs, analyze existing system shortcomings, utilize Microsoft.net for development, integrate standard nursing procedures and clinical operating protocols into system functions. Structure database based on bed characteristics, implant CCC Nursing Terminology and clinical nursing knowledge base. RESULTS: Successfully design and develop CCC Nursing Information System featuring patient list, nurse assignment, nursing evaluation, diagnosis, goals, plan, interventions, special care, shift handover, record query, workload statistics, and intelligent guidance based on patient assessment and nursing elements. CONCLUSION: The CCC Nursing Information System advances standard nursing procedures in clinical practice, promoting standardization and responsibility-based holistic care. It harnesses big data to enhance system intelligence.

Nursing Informatics Competencies of Graduate Nurse Educator Students: Descriptive Study.

The advancement of technology and Artificial Intelligence applied health information systems demand high informatics competencies from nurses. To prepare nursing students to meet this demand, informatics courses are designed to increase informatics competencies. We offered an online informatics course to graduate students in a Nurse Educator program and assessed their informatics competency, including subdomains. Survey data were collected between Fall 2020 and Fall 2022 using an online Self-Assessment of Informatics Competency Scale for Health Professionals. We analyzed 109 responses and found that students were competent in overall informatics competency and the subdomains of "basic computer skills" and "applied computer skills (clinical informatics)." They were proficient in the 'role' subdomain. However, students reported less competency in managing data and incorporating standard terminology into practice. These findings provide detailed insights of the current nursing students' informatics competencies and can guide informatics faculty in improving their courses.

What Is the Level of Nursing Informatics Competency of ChatGPT?

Nurses must excel in using Artificial Intelligence (AI) - applied hospital systems, making their informatics competency crucial. ChatGPT has been trained with extensive amounts of informatics- and technology-related health data and has gained popularity. Nurses could have the opportunity to enhance their informatics competency through the knowledge generated by ChatGPT. However, its informatics competency has not been evaluated. We used the Self-Assessment of Informatics Competency Scale to measure the level of informatics competency of ChatGPT. ChatGPT fell within the range of 'somewhat competent' and 'competent,' lower than that of students in graduate programs. One subdomain, applied computer skills (clinical informatics), demonstrated competency levels close to that of students. Although the results presented certain limitations and concerns, we recognize the potential of ChatGPT to help researchers and healthcare practitioners. Nursing is advancing and continuously integrating AI technology; therefore, we should now embrace both the benefits and risks associated with ChatGPT.

Multidisciplinary-Based Design of a Nursing Informatics Curriculum.

This paper explores the development of a multidisciplinary nursing informatics curriculum. The aim is to integrate multiple disciplines to meet the educational objectives of undergraduate nursing students. The curriculum design included a thorough needs assessment, curriculum development, and evaluation. Of the 29 undergraduate nursing students enrolled in the course, 21 completed the course evaluation with a response rate of 72.4%. The comprehensive assessment of the course (part 1) scored 93.7 out of 100, while the quality of the teacher's teaching (part 2) scored 93.4 out of 100. In addition, in response to the subjective questions, students expressed satisfaction with the course design and teaching methods, and emphasized the usefulness of the course for their future nursing practice.

Nursing Education and Artificial Intelligence.

The American Association of Colleges of Nursing (AACN) is shifting the nursing education paradigm to competency-based education. Competency-based nursing education focuses on the nursing students' demonstration of knowledge. This shift in nursing education will rely on performance measures and data to determine success. Data and artificial intelligence can provide the nursing student with a targeted evaluation from the nursing faculty. Building on prior applications of "precision" and the use of data to drive precision medicine or precision nursing, nursing informatics is well-positioned for this paradigm shift to support data and artificial intelligence in nursing education. Little is understood about the concept of "precision nursing education" and its implications. We completed a concept analysis and defined the concept of "precision nursing education" as the use of data and artificial intelligence to measure student nurses' performance with competency-based nursing education.

Nursing Informatics Research: A Bibliometric Analysis from 1989 to 2023.

Nursing informatics has evolved rapidly since its inception. Despite its growth, there remains a gap in comprehensive bibliometric analyses of the field's development and themes. The study aimed to provide an overview of the evolution and current status of nursing informatics by conducting a bibliometric analysis of the literature from 1989 to 2023. Utilizing the Science Citation Index Expanded edition of the Web of Science Core Collection, 483 original English-language articles were analyzed using Bibliometrix 4.1. The results revealed a steady increase in publications, with the United States as the leading contributor. Thematic analysis indicates a shift from basic informatics integration to advanced technologies like artificial intelligence, reflecting the dynamic nature and expanding scope of nursing informatics. These findings highlight the need for ongoing research, enhanced digital literacy, and interdisciplinary collaboration, emphasizing the field's critical role in advancing healthcare in the digital age.

Integrating Health Informatics into Pre-Registration Nursing Education: Insights from a Participatory Workshop.

The implementation of health informatics in pre-registration health professional degrees faces persistent challenges, including curriculum overload, educator workforce capability gaps, and financial constraints. Despite these barriers, reports of successful implementation of health informatics pre-registration nursing programs exist. A virtual workshop was held during thein 15th International Nursing Informatics Conference in 2021 with the aim to explore successful implementation strategies for incorporating health informatics into the nursing curriculum to meet the accreditation standards. This paper reports recommendations from the workshop emphasising the importance academic-clinical partnerships to develop innovative approaches to enhance theof capacity of academic teams and access to contemporary point of care digital technologies that reflect applications of health informatics in interdisciplinary clinical settings.

Academic-Practice Partnerships, EHR in Nursing Curriculum, and the Value Equation.

Workforce well-being and associated factors such as burnout, depression and documentation burden, have been identified as the highest concerns to be addressed. In academia, the new essentials of nursing practice including domain 8 for informatics and healthcare technology have become a focus for curricular revisions/enhancements. Our study focused on technology skills by using the technology of an academic EHR to measure baselines and progression of EHR use, sense of confidence, documentation competency, and post-graduation employer-based performance assessment. We provide results of an ongoing 1.5-year study and overarching strategy for university-wide deployment and financing.

Evaluating and Incorporating Generative AI in Nursing Informatics and Data Science Graduate Courses.

The disruptive effect and lasting implications of generative artificial intelligence ("Gen AI") tools for higher education are yet unknown. ChatGPT 3.5 was released in November 2022 and soon had over 100 million users. This public software release triggered a global Gen AI race among technology industry giants. Educators in higher education were unprepared for this seismic shift. For the Fall 2023 term, we revised two graduate courses in nursing informatics and data science using generative AI to anticipate broad student awareness of these tools. The aim of this report is to present two different examples of course component evaluation using publicly available Gen AI tools to inform course component revisions. This effort was undertaken to "proof" assignments against inappropriate use of Gen AI, revise assignments to incorporate use of Gen AI tools, and inform course policies about appropriate use of Gen AI for course work.

Artificial Intelligence in Nursing: Perspectives from Norwegian Nurses.

Nurses continue to face challenges in leading health information technology innovations such as Artificial Intelligence (AI). There is an acknowledged need to explore the attitude of nurses towards AI and nurses' acceptance of AI in clinical settings. We sought to address this gap in knowledge about the perceptions of AI by nursing-related professionals in their work and as a content area in the education of nursing students. Norwegian nurses and healthcare personnel interested in the topic met in a seminar in Oslo in 2023 to explore their perspectives on AI. Following a lecture on AI, audience members offered their insights in a recorded discussion. Data analysis consisted of inductive coding of concepts in the transcribed recording. Three major themes emerged: Expectations, Identified needs and related recommendations; and Policy to guard safety; as well as recommendations new to the literature.

Data Literacy and Data Science Literacy for Nurses: State of the Art Literature Review.

In the rapidly evolving landscape of modern healthcare, nurses must proficiently navigate data utilization and grasp the principles of data science. Despite this urgency, nursing stakeholders currently do not fully understand the extent of data literacy or data science literacy they need to acquire. This paper aims to elucidate the distinctions between data literacy and data science literacy, offering insights into strategies for nurturing these competencies within nursing education, research, and practice. Through a state-of-the-art review of 22 articles and six healthcare industry resources, we identified a notable absence of comprehensive frameworks and assessment tools, highlighting key areas for future development.

Health Informatics: A Challenge for Nurses in Public Health in Rural Mexico.

Health informatics has significantly advanced global technology, yet challenges persist in public health and rural nursing in Mexico due to social inequalities, limited technology access, and suboptimal infrastructure, compounded by the absence of nurse informaticians as viable career options. Overcoming these barriers necessitates international collaboration, empowering Mexican nurses to contribute to universal health access and advocate for health equity. Interventions must extend beyond nursing curricula to existing workforces, ensuring they can address the needs of vulnerable populations in Mexico. Long-term international support is crucial to bridge these gaps and unleash the full potential of Mexican nurses in influencing global health.

Nurses' Roles in Artificial Intelligence Implementation: Results from a Mixed-Methods Study.

We aimed to understand nursing informaticists' perspectives on key challenges, questions, and opportunities for the nursing profession as it prepares for an era of healthcare delivery enriched by artificial intelligence (AI). We found that nursing practice is currently, and will continue to be, directly influenced by AI in healthcare. Educating and training nurses so that they may safely and effectively use AI in their clinical practice and engage in implementation planning and evaluation will help overcome predicted challenges. Defining the key tenets of AI literacy for nurses and re-envisioning nursing models of care in the context of AI-enriched healthcare are important next steps for nursing informaticists. If embraced, AI has the potential to support the existing nursing workforce in the context of major shortages and augment the safe and high-quality care that nurses can deliver.

Representing Nursing Practice in EMR/EHRs.

OBJECTIVE: Review of the ISO 18104 technical standard for a Nursing Categorial structure to best represent nursing practice in EMR/EHRs and digital health ecosystems. METHODS: Application of ISO standard review guidelines in consultation with ISO member stakeholders. RESULTS: Comprehensive views of the nursing practice knowledge domain are presented as mindmaps. Groups of patients can now be identified using the 'type of subject of care' category. The collaborative role of nurses is now recognized. This high level structured information model recognises nursing diagnosis, nursing actions and nurse sensitive outcomes relative to other categories and sub-categories known to influence nursing actions and nurse sensitive outcomes. DISCUSSION: This nursing practice framework reflects the nursing process. It supports conceptual and logical analysis of patient journey related nursing practice. CONCLUSION: This updated categorial structure is a good fit with today's information technologies. Its adoption enables the value of nursing services provided to be demonstrated.

Future Needs in Nursing Informatics - Preliminary Findings from the Global Nursing Informatics Survey.

This study investigates the evolving landscape of nursing informatics by conducting a follow-up survey initiated by the International Medical Informatics Association (IMIA) Students and Emerging Professionals (SEP) Nursing Informatics (NI) group in 2015 and 2019. The participants were asked to describe what they thought should be done in their institutions and countries to advance nursing informatics in the next 5-10 years. For this paper, responses in English acquired by December 2023 were analysed using inductive content analysis. Identified needs covered a) recognition and roles, b) educational needs, c) technological needs, and d) research needs. The initial findings indicate that, despite significant progress in nursing informatics, the current needs closely mirror those identified in the 2015 survey.

Dissemination of Strategies for Reducing Excessive Documentation Burden: 25x5 Task Force Activities Relevant to Nursing.

Burnout and workforce shortages are having a negative impact on nurses globally, particularly after the COVID-19 pandemic. Within the United States, excessive documentation burden (DocBurden) has been linked to nurse burnout. The experience of a system or system-imposed process inhibiting patient care is a core focus area of nursing informatics research. The American Medical Informatics Association (AMIA) 25x5 Task Force to Reduce DocBurden was created in 2022 to decrease U.S. health professionals' excessive DocBurden to 25% of current state within five years through impactful solutions across health systems that decrease non-value-added documentation, and leverage public/private partnerships and advocacy. This case study will describe the work of the 25x5 Task Force that is relevant to nursing practice. Specifically, we will describe three projects: A) Toolkit for Reducing Excessive DocBurden, B) Development of Pulse Survey for Health Professionals Perceived DocBurden, and C) HIT Roadmap to Promote Interoperability.

Gender Harmony: A Case for Nursing Informatics.

The design of digital health information systems around a conflated gender/sex binary contributes to health inequities. Lack of specific information that supports affirming communication lead to inappropriate care, disrespectful encounters with healthcare staff, and avoidance of health services by clients who have been harmed by misgendering, deadnaming and being outed. The HL7 International Gender Harmony Model (HL7 GHM) supports the design, implementation and use of DHIS that enable affirming clinical interactions and care. This case study will demonstrate how applying the HL7 GHM can address the harms reported in a recently published account of one patient in Canada.