Online digital health and informatics education for undergraduate nursing students in China: impacts and recommendations.

BACKGROUND: Digital health plays a vital role in healthcare services. Governments in many countries, including China, are increasingly advocating for the appropriate use of digital technologies to address significant health system challenges. It is crucial to incorporate digital health education into the curriculum for future nurses to adapt to the changes in the digital medical system. This study aimed to evaluate the impact of an online Digital Health and Informatics Course in China on the knowledge and comprehension of key digital health and informatics topics, self-assessment of nursing informatics competencies, and satisfaction among undergraduate nursing students. The findings of this study provide recommendations for the design and implementation of future digital health education. METHODS: This study employed a one-group, quasi-experimental mixed-methods design with pre- and post-assessments. The participants received digital health and informatics education through six three-hour online sessions in six interactive days, with online self-learning materials in between. An online quiz and focus group discussions pre- and post the course were designed to evaluate the knowledge and comprehension of key digital health and informatics topics. Also, a validated Chinese version of the Self-assessment of Nursing Informatics Competencies Scale was conducted pre- and post-course to assess self-assessment of nursing informatics competencies. Additionally, all students were invited to participate in an online survey with a performance-focused course evaluation form as well as focus group discussions to gather their feedback on the learning experience and their evaluations of the course. RESULTS: A total of 24 undergraduate nursing students were enrolled in the course. All students completed all sessions of this course, resulting in an attendance rate of 100%. Additionally, all students completed both pre- and post-assessments. In terms of the knowledge and comprehension of key digital health and informatics topics, scores of the quiz on knowledge assessment improved from the pre-test [mean pretest score: 78.33 (SD 6.005)] to the post-test [mean post-test score: 83.17 (SD 4.86)] upon completion of the course (P < 0.001). Also, students acknowledged that the course enhanced their knowledge and comprehension of informatics and digital health, the benefits of (nursing) informatics in clinical practice, and the role of health care professionals in informatics and digital health. In terms of self-assessment of nursing informatics competencies, scores on nursing informatics attitudes demonstrated significant improvement (P < 0.001). Furthermore, students reported high satisfaction with various aspects of this course, including the opportunity to explore broad horizons in informatics for future careers, engaging in group discussions, and analyzing case studies on the use of informatics and digital health in clinical practice. CONCLUSIONS: This Online Digital Health and Informatics education effectively improved undergraduate nursing students' knowledge and comprehension of the key digital health and informatics topics, nursing informatics attitudes in the self-assessment of nursing informatics competency with high levels of satisfaction. In order to ensure that future education in digital health and informatics for nursing students is in line with the technological advancements in clinical settings, it is necessary to foster collaboration between medical school training and clinical practice. This collaboration should involve the use of clinical examples to illustrate advanced digital health applications and the inclusion of practical exercises on the use of digital health technology in clinical settings.

Global Trends and Hotspots in Nursing Research on Decision Support Systems: A Bibliometric Analysis in CiteSpace.

Decision support systems have been widely used in healthcare in recent years; however, there is lack of evidence on global trends and hotspots. This descriptive bibliometric study aimed to analyze bibliometric patterns of decision support systems in nursing. Data were extracted from the Web of Science Core Collection. Published research articles on decision support systems in nursing were identified. Co-occurrence and co-citation analysis was performed using CiteSpace version 6.1.R2. In total, 165 articles were analyzed. A total of 358 authors and 257 institutions from 20 countries contributed to this research field. The most productive authors were Andrew Johnson, Suzanne Bakken, Alessandro Febretti, Eileen S. O'Neill, and Kathryn H. Bowles. The most productive country and institution were the United States and Duke University, respectively. The top 10 keywords were "care," "clinical decision support," "clinical decision support system," "decision support system," "electronic health record," "system," "nursing informatics," "guideline," "decision support," and "outcomes." Common themes on keywords were planning intervention, national health information infrastructure, and methodological challenge. This study will help to find potential partners, countries, and institutions for future researchers, practitioners, and scholars. Additionally, it will contribute to health policy development, evidence-based practice, and further studies for researchers, practitioners, and scholars.

Foundation Models, Generative AI, and Large Language Models: Essentials for Nursing.

We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care.

Data-Centric Machine Learning in Nursing: A Concept Clarification.

The ubiquity of electronic health records and health information exchanges has generated abundant administrative and clinical healthcare data. The vastness of this rich dataset presents an opportunity for emerging technologies (eg, artificial intelligence and machine learning) to assist clinicians and healthcare administrators with decision-making, predictive analytics, and more. Multiple studies have cited various applications for artificial intelligence and machine learning in nursing. However, what is unknown in the nursing discipline is that while greater than 90% of machine-learning implementations use a model-centric strategy, a fundamental change is occurring. Because of the limitations of this approach, the industry is beginning to pivot toward data-centric artificial intelligence. Nurses should be aware of the differences, including how each approach affects their engagement in designing human-intelligent-like technologies and their data usage, especially regarding electronic health records. Using the Norris Concept Clarification method, this article elucidates the data-centric machine learning concept for nursing. This is accomplished by (1) exploring the concept's origins in the data and computer science disciplines; (2) differentiating data- versus model-centric machine learning approaches, including introducing the machine-learning operation life cycle and process; and (3) explaining the advantages of the data-centric phenomenon, especially concerning nurses' engagement in technological design and proper data usage.

Microlearning: A Concept Analysis.

With an overall rise in technology adoption, the information-seeking behaviors of today have become instant and single-focused, and demand convenience for learning and the acquisition of knowledge. Digital technologies expand the reach of learning and allow for the development of innovative and creative methods of teaching. The use of microlearning has been gaining popularity in academic and professional development settings and corporate training. Currently, there is no standardized definition of microlearning. Using Walker and Avant's method of concept analysis, a comprehensive overview of microlearning is provided through identifying the concept and describing its uses, attributes, exemplary cases, antecedents, consequences, and empirical referents. Seven attributes associated with microlearning are single focus, bite-sized, asynchronistic, accessibility, flexibility, interactivity, and multimodal delivery. A proposed definition is a self-directed, on-demand, teaching strategy where small single-focused interactive content is presented to learners asynchronously, using technologies that accommodate multimodal delivery, and access where and when convenient for the learner. This analysis will assist informatics and nursing educators in understanding how microlearning, as a strategy, fits into the electronic learning landscape, is supported by digital technologies, and adds portability to leverage in an on-demand asynchronous way providing targeted learning for use in all areas of clinical practice.

Academic Electronic Health Record in Mental Health Clinical: A Quality Review.

Developing competency in the use of EHRs is essential for entry-level professional nurses. Although nursing education has been encouraged to integrate this technology into nursing curriculum, many students still graduate feeling unprepared in this area. As a result, nursing graduates lack the skills necessary to effectively use EHRs, which may have negative consequences for safe patient care. Use of academic EMRs provides students the opportunity to integrate informatics education, develop critical thinking, and incorporate problem-solving skills in the clinical area. An academic EMR was introduced to students in the second semester of a baccalaureate degree nursing program. Students completed documentation on one patient from the mental health clinical rotation. A retrospective chart review was conducted, using a rubric to determine charting efficacy. Data analysis indicated that students struggled with documentation of the mental health assessment, care plan development, and nursing notes. Student documentation was strongest in vital signs and basic information. Students need practice documenting on the critical aspects of nursing care. Utilization of an academic EMR for clinical charting provides an opportunity for students to practice documentation and develop necessary skills for clinical practice.

[Next-Generation Intelligent Care Opportunities].

Nursing information systems are becoming increasingly prevalent in our medical institutions. However, changes in the social environment and imbalances between the demands of caregivers and care recipients mean that current nursing information systems are inadequate in terms of quality and operational needs. This article was written to provide insights into opportunities to leverage technology to further promote care quality by applying a "data, information, knowledge, and wisdom" system development structure to develop intelligent technology products that equitably meet the needs of patients, caregivers, and nursing processes. Applied in clinical settings, these products should help satisfy patient needs and facilitate nursing work.

Digital nursing practice theory: A scoping review and thematic analysis.

AIMS: This scoping review aims to identify existing theories associated with digital nursing practice to add a lens on the future use of digital technologies by nurses. DESIGN: A review of theories related to digital technology in nursing practice was conducted following the framework described by Arksey and O'Malley. All published literature until 12th May 2022 was included. DATA SOURCES: Seven databases were utilized including Medline, Scopus, CINAHL, ACM Digital Library, IEEE Xplore, BNI and Web of Science. A Google Scholar search was also performed. REVIEW METHODS: The search terms included (nurs* AND [digital OR technol* OR e-health or ehealth or digital health or telemedicine or telehealth] AND theory). RESULTS: The database searches yielded 282 citations. After screening, nine articles were included in the review. These described eight distinct nursing theories. CONCLUSION: The focuses of the theories included the role of technology in society and nursing. How technology should be developed to support nursing practice, health consumers' use of nursing informatics, the use of technology as an expression of caring and the preservation of humanness and the relationship between human persons and non-human actants and the creation of nursing technologies as caring in addition to existing technologies. Three themes were identified including the role of technology as an agent within the patient environment; nurse interactions with technology to achieve 'knowing' of patients and the necessity of technological competence among nurses. Then, using Actor Network Theory (ANT), a zoom-out lens to map the concepts was proposed (The Lens for Digital Nursing [LDN]). This study is the first to add a new theoretical lens on digital nursing. IMPACT: This study provides the first synthesis of key concepts of nursing theories to add a theoretical lens to digital nursing practice. This can be used in a functional capacity to zoom-in different entities. No patient or public contribution was made in this study due to it being an early scoping study on a currently understudied area of nursing theory.

Nursing informatics competence profiles and perceptions of health information system usefulness among registered nurses: A latent profile analysis.

AIMS: To identify different nursing informatics competence (NIC) profiles in nurses, examine the factors associated with profile memberships and examine the associations of the derived profiles with the nurses' perception of the usefulness of a health information system (HIS). DESIGN: A cross-sectional study. METHODS: A sample of 3610 registered nurses responded to a nationwide survey in March 2020. A latent profile analysis was performed to identify NIC profiles based on three competence areas: nursing documentation, working in digital environment, and ethics and data protection. A multinomial logistic regression was carried out to examine the associations of demographic and background variables with the profile membership. Linear regression analyses were carried out to examine the association between the profile membership and perceived HIS usefulness. RESULTS: Three NIC profiles were identified and labelled as low, moderate and high competence groups. A younger age, recent graduation year, sufficient orientation and high-rated proficiency as an HIS user were associated with nurses belonging to a high or moderate competence group relative to a low competence group. Competence group membership was associated with perceived HIS usefulness. The high competence group consistently expressed the highest usefulness of the HIS and the low competence group the lowest. CONCLUSION: Tailored training and support should be provided for nurses with different levels of informatics competence, thereby facilitating their ability to respond to increasingly digitalized work. This could contribute to higher usefulness of the HIS in terms of supporting the nurses' work tasks and promoting the quality of care. IMPACT: This was the first study exploring latent profiles of informatics competence in nurses. Insights from this study are useful for nursing management to identify different competence profiles of their employees, provide support and training to meet their needs, and promote the successful use of an HIS.

Nursing Informatics and Epigenetics: Methodological Considerations for Big Data Analysis.

Nursing informatics requires an understanding of patient-centered data and clinical workflow, and epigenetic research requires an understanding of data analysis. The purpose of this article is to document the methodology that nursing informatics specialists can use to conduct epigenetic research and subsequently strengthen patient-centered care. A pilot study of a secondary methylation data analysis using The Cancer Genome Atlas data from individuals with colon cancer is utilized to illustrate the methodology. The steps for conducting the study using public and free resources are discussed. These steps include finding a data source; downloading and analyzing differentially methylated regions; annotating differentially methylated region, gene ontology and function analysis; and reporting results. A model of epigenetic testing workflow is provided, as is a list of publicly available data and analysis sources that can be used to conduct epigenetic research.

Nursing Faculty Informatics Competencies.

It is essential that nurses can use technology and accurately record and interpret clinical data to deliver efficient and effective patient care. The purpose of this study was to determine the level of nursing faculty informatics competencies and to learn about barriers faculty find in teaching informatics. Using a cross-sectional design, faculty were surveyed about their knowledge and comfort in teaching informatics using the Self-Assessment of Informatics Competency Scale for Health Professionals instrument. The aggregate mean (SD) score of the Self-Assessment of Informatics Competency Scale for Health Professionals basic knowledge and skills competency subscale and role subscale were was 3.36 (0.437) and 3.35 (0.711), respectively, which showed overall proficiency with these competencies. The aggregate mean (SD) for the applied computer skills competency was 2.25 (0.842), which showed less proficiency in higher-level informatics skills. Reported barriers to integrating informatics into courses were technology issues (17.2%), lack of knowledge (15.5%), and a lack of resources (12.1%). Some faculty reported that the concept of informatics was confusing (3.5%) and students were not engaged in the concepts (3.5%). Faculty with informatics competence can help students advance the use of technology and informatics at the bedside to improve patient care.

Identifying the Knowledge Structure and Trends of Nursing Informatics: A Text Network Analysis.

With the advent of the information age and technological development, the importance of digital health technologies has increased. Subsequently, nursing informatics has been developed to enhance the effectiveness of healthcare information management and communication. This study aimed to identify the nursing informatics knowledge structure and research trends through quantitative analysis using text network analysis. Here, we analyzed 14 225 studies published by 2020. The knowledge structure of nursing informatics and changes therein were clarified by identifying and analyzing the core keywords, topics, and changes in the topics of related studies over time. We identified "patient," "health," "system," and "information" as core keywords connecting other keywords. Over time, the networks between "information," "communication," and "technology" strengthened, and "patient safety" and "quality" have recently emerged as research keywords. This change indicates an increase in the importance of nursing education on technology. Similar changes appeared in the topic analysis, showing an increased proportion of research related to system and technology and nursing education. These results can broaden a systematic understanding of nursing informatics research. Furthermore, given these findings, the importance of nursing informatics on patient safety and nursing education-based on the development of systems and technology-can be expected to continue growing.

The Psychometric Properties of Version 2 of the Canadian Nurse Informatics Competency Assessment Scale.

In 2020, we conducted a mixed methods study comprised of a cross-sectional survey in which we applied a modified version of the 21-item Canadian Nurse Informatics Competency Assessment Scale and one-on-one interviews to explore self-perceived nursing informatics competency and readiness for future digital health practice. A total of 221 senior-level students in BScN programs in western Canada participated. This article reports on results related to the factor structure and internal consistency reliability of the 26-item (version 2) of the Canadian Nurse Informatics Competency Assessment Scale. Exploratory principal component analysis with the varimax rotation revealed a four-component structure, explaining 55.10% of the variance. All items on the Canadian Nurse Informatics Competency Assessment Scale 2 had good loadings, except item 7, which did not load to any domain but was retained based on an evaluation of the α value and item relevance to nursing practice. A few items shifted to different domains. The overall reliability of the Canadian Nurse Informatics Competency Assessment Scale 2 was ( α = .916) and its subscales: information and knowledge management ( α = .814), professional and regulatory accountability ( α = .741), and use of information and communication technology ( α = .895). This study provided preliminary evidence for the factor structure and reliability of the Canadian Nurse Informatics Competency Assessment Scale 2 among nursing students. Further testing is recommended.

Providing evidence-based knowledge on nursing interventions at the point of care: findings from a mapping project.

BACKGROUND: In healthcare there is a call to provide cost-efficient and safe care. This can be achieved through evidence-based practice (EBP), defined as the use of evidence from research, context, patient preferences, and clinical expertise. However, the contemporary and process-integrated supply of evidence-based knowledge at the point of care is a major challenge. An integrative knowledge management system supporting practicing clinical nurses in their daily work providing evidence-based knowledge at the point of care is required. The aim of this study was (1) to map standardized and structured nursing interventions classification and evidence on a knowledge platform to support evidence-based knowledge at the point of care, and (2) to explore the challenge of achieving interoperability between the source terminology of the nursing interventions classification (LEP Nursing 3) and the target format of the evidence provided on the knowledge platform (FIT-Nursing Care). METHODS: In an iterative three-round mapping process, three raters, nurses with clinical and nursing informatics or EBP experience, matched nursing interventions from the LEP Nursing 3 classification and evidence provided from Cochrane Reviews summarized on FIT-Nursing Care as so-called study synopses. We used a logical mapping method. We analysed the feasibility using thematic analysis. RESULTS: In the third and final mapping round, a total of 47.01% (252 of 536) of nursing interventions from LEP Nursing 3 were mapped to 92.31% (300 of 325) of synopses from FIT-Nursing Care. The interrater reliability of 77.52% suggests good agreement. The experience from the whole mapping process provides important findings: (1) different content orientations-because both systems pursue different purposes (content validity), (2) content granularity-differences regarding the structure and the level of detail in both systems, and (3) operationalization of knowledge. CONCLUSION: Mapping of research evidence to nursing classification seems feasible; however, three specific challenges were identified: different content orientation; content granularity; and operationalization of knowledge. The next step for this integrative knowledge management system will now be testing at the point of care.

How to Support the Nursing Informatics Leadership Pipeline: Recommendations for Nurse Leaders and Professional Organizations.

There is a need for nursing informatics leaders. However, there are not enough people educated and trained in informatics and leadership to fill that need. Therefore, the purpose of this study was to understand how professional organizations and nurse leaders support nursing informatics leadership development. This cross-sectional, descriptive study collected data via a scan of Web sites for eight nursing, informatics, and/or leadership professional organizations; interviews and surveys with nursing informatics leaders within the eight organizations; and a review of Web site, interview, and survey findings by nursing informatics leaders involved in leadership development. We found that nursing informatics leaders and professional organizations can support the nursing informatics leadership pipeline several ways. Examples included mentoring, education/training, and providing opportunities for networking and engagement in leadership roles. To help meet the need for nursing informatics leaders, professional organizations and current leaders can engage in various activities that provide training, education, and experiences for emerging leaders.

Expanding the Informatics Competencies of Nurse Practitioners Through Online Learning.

Nurse practitioners' informatics competencies are not well-understood. Limited evidence alludes to the potential need to improve the informatics competencies of nurse practitioners. The primary purpose of this study was to analyze the informatics competencies of nurse practitioners, including nurses training to become nurse practitioners, before and after completing an online learning module in nursing informatics. Six topics were covered in the investigator-developed learning module. A pretest-posttest, one-group, quasi-experimental design was used in the study. The link to the study was emailed to members of a local nurse practitioners' association in California and graduate nursing students at a public university in Missouri. The study was also shared on a professional networking Web site, LinkedIn. Data were collected from 15 nurse practitioners and two nurse practitioner students, using a demographic questionnaire and an 18-item self-assessment of informatics competency scale. A related-samples Sign test was conducted to compare the pretest and posttest scores. Statistically significant median increases ( P = .001 to <.001) were found in five areas. Findings suggest that the online learning module expanded the participants' competencies in specific areas of informatics. The results also provide an initial understanding of nurse practitioners' informatics competencies and inform future iterations of the study.

Development of Nursing Informatics Competence Scale for Korean Clinical Nurses.

Much of the research on nursing informatics competence has been conducted in a Western context. Thus, this study aimed to develop the Korean Nursing Informatics Competence Assessment Scale for clinical nurses and to evaluate its validity and reliability. A total of 52 items were derived based on the hybrid model. After a content validity test by six experts and item evaluation by 20 nurses, the scale was revised to include 35 items. For this study, 214 nurses completed the nursing informatics competence assessment scale to verify the scale's reliability and validity. Confirmatory factor analysis revealed five factors composed of 20 items; the fit index of the derived model was good. A positive correlation between scores on the nursing informatics competence scale and the patient safety competence scale ( r = .66, P < .001) was found for the criterion-related validity test. Cronbach's α was .91, indicating that the instrument is reliable and stable. Overall, this study provides preliminary evidence for the validity and reliability of the Korean nursing informatics competence assessment scale to evaluate clinical nurses. This study contributes to the understanding and improvement of nursing informatics competence by providing a reliable scale for assessing clinical nursing practice.

The Relationship Between Nursing Informatics Competency and Clinical Decision-Making Among Nurses in West Bank, Palestine.

This study aimed to examine the relationship between nursing informatics competencies and clinical decision-making by taking into account nurses' individual characteristics and job-related characteristics. A cross-sectional design was used. The cluster random sampling method was adopted to select 14 governmental hospitals in West Bank, Palestine, in which all nurses in these hospitals were invited to participate in this study. Results found that the total mean (SD) score for the nursing informatics competency scale was 2.6 (0.88), which indicates that the nurses had lower nursing informatics competency, and the informatics skills subscale had the lowest mean score (mean [SD], 2.4 [1.00]). Concerning clinical decision-making, the total mean (SD) score was 2.59 (0.38), which indicates that the nurses had lower clinical decision-making. Regarding clinical decision-making subscales, searching for information and unbiased assimilation of new information had the highest mean score (mean [SD], 2.64 [0.39]); on the contrary, the canvassing of objectives and values subscale had the lowest mean score (mean [SD], 2.53 [0.38]). Nursing informatics competency had a positive relationship with clinical decision-making. Thus, it is necessary to enhance nurses' informatics competency, especially informatics skills and clinical decision-making, by developing training programs about this technology directed to nurses.

Developing nursing students' informatics competencies - A Canadian faculty perspective.

OBJECTIVES: The aim of this study was to explore nursing faculty experiences in integrating digital tools to support undergraduate students' learning and development of nursing informatics competencies. METHODS: This focused ethnography study used a combination of semi-structured interviews, document reviews, and field visits. Convenience and snowball sampling were applied to recruit participants. Data were analyzed concurrently with data collection, using thematic analysis. RESULTS: Twenty-one faculty members from nine undergraduate nursing programs in Western Canada participated. Themes discussed include: 1) meaning of the term nursing informatics, 2) faculty perceived nursing informatics competence, 3) developing students' nursing informatics competencies, 4) facilitators, and 5) challenges. CONCLUSIONS: Nursing faculty are relatively engaged in developing students' informatics competencies. However, challenges must be addressed and faculty need more support to improve their own informatics capacity. Implications for Practice and Research: This study has implications for faculty, nursing program administrators, and nursing organizations.

Designing a national model for assessment of nursing informatics competency.

BACKGROUND: Due to the need for informatics competencies in the field of nursing, the present study was conducted to design a psychometric instrument to determine the qualification of informatics competencies of employed nurses in educational care centers. METHODS: The questionnaire was made by reviewing existing scientific resources and assessment tools. Two hundred nurses were selected using simple random sampling. Structural equation modeling was used using the measurement model technique and the average variance was calculated. Linear structural relations (LISREL) software was used to test the assumptions and correlations of the model. RESULTS: Findings showed relatively good estimation in the fit of first-order measurement model. The informatics knowledge subscale with a determining rate of 0.90 had the greatest explanatory effect among the subscales and informatics skill with a determining rate of 0.67 and basic computer skill with a determining rate of 0.60 were observed. The second-order measurement model of fitness indicators showed that the three factors can well explain the multidimensional construct of informatics competency. CONCLUSIONS: The designed tool can be used to develop educational strategies in relation to nursing students in the field of informatics and prepare them in the rich environment of information technology, which can be helpful in training nursing instructors.