Information Management in Hospital Unit Daily Operations: A Descriptive Study With Nurses and Physicians

Operations management of a hospital unit is a shared activity involving nursing and medical professionals, characterized by suddenly changing situations, constant interruptions, and ad hoc decision-making. Previous studies have explored the informational needs affecting decision-making, but only limited information has been collected regarding factors affecting information management related to the daily operations of hospital units. The aim of this study was to describe the experiences of nursing and medical professionals of information management in the daily operations of hospital units. This qualitative study consists of interviews following the critical incidence technique. Twenty-six nurses and eight physicians working in operational leadership roles in hospital units were interviewed, and the data were subjected to thematic analysis. The data analysis showed that strengths of current systems were organizational operational procedures, general instruments supporting information management, and a digital operations dashboard, whereas opportunities for improvement included the information architecture, quality of information, and technology use. The study findings highlight that despite several decades of efforts to provide solutions to support information management in hospital daily operations, further measures need to be taken in developing and implementing information systems with user-centered strategies and systematic approaches to better support healthcare professionals.

A rapid review on current and potential uses of large language models in nursing

BACKGROUND

The application of large language models across commercial and consumer contexts has grown exponentially in recent years. However, a gap exists in the literature on how large language models can support nursing practice, education, and research. This study aimed to synthesize the existing literature on current and potential uses of large language models across the nursing profession.

METHODS

A rapid review of the literature, guided by Cochrane rapid review methodology and PRISMA reporting standards, was conducted. An expert health librarian assisted in developing broad inclusion criteria to account for the emerging nature of literature related to large language models. Three electronic databases (i.e., PubMed, CINAHL, and Embase) were searched to identify relevant literature in August 2023. Articles that discussed the development, use, and application of large language models within nursing were included for analysis.

RESULTS

The literature search identified a total of 2028 articles that met the inclusion criteria. After systematically reviewing abstracts, titles, and full texts, 30 articles were included in the final analysis. Nearly all (93 %; n = 28) of the included articles used ChatGPT as an example, and subsequently discussed the use and value of large language models in nursing education (47 %; n = 14), clinical practice (40 %; n = 12), and research (10 %; n = 3). While the most common assessment of large language models was conducted by human evaluation (26.7 %; n = 8), this analysis also identified common limitations of large language models in nursing, including lack of systematic evaluation, as well as other ethical and legal considerations.

DISCUSSION

This is the first review to summarize contemporary literature on current and potential uses of large language models in nursing practice, education, and research. Although there are significant opportunities to apply large language models, the use and adoption of these models within nursing have elicited a series of challenges, such as ethical issues related to bias, misuse, and plagiarism.

CONCLUSION

Given the relative novelty of large language models, ongoing efforts to develop and implement meaningful assessments, evaluations, standards, and guidelines for applying large language models in nursing are recommended to ensure appropriate, accurate, and safe use. Future research along with clinical and educational partnerships is needed to enhance understanding and application of large language models in nursing and healthcare.

User Needs and Factors Associated With the Acceptability of Audiovisual Feedback Devices for Chest Compression Monitoring in Cardiopulmonary Resuscitation

The use of audiovisual feedback devices to guide the quality of chest compressions during cardiopulmonary resuscitation has increased in recent years. Audiovisual feedback devices can be classified as integrated (eg, Zoll AED Plus defibrillator) or standalone (eg, CPRmeter). This study aimed to explore users' needs and factors affecting the acceptability of audiovisual feedback devices. Semistructured interviews were conducted with healthcare professionals involved in lifesaving activities. The Unified Theory of Acceptance and Use of Technology was used as a theoretical framework for the study. The Unified Theory of Acceptance and Use of Technology model has four constructs: performance expectancy, effort expectancy, social influence, and facilitating factors. Ten themes were identified under the four constructs. The performance expectancy constructs include three themes: perceived usefulness, outcome expectation, and applicability in diverse situations. The effort expectancy construct encompasses two themes: user-friendliness and complexity. The social influence construct has two themes: social and organizational factors. Lastly, the facilitating factors construct includes three themes: staff competence, perceived cost, and compatibility of devices. Exploring the needs and factors influencing the acceptability of audiovisual feedback devices used during cardiopulmonary resuscitation will inform healthcare providers, managers, manufacturers, and procurers on how to improve the efficiency and use of these devices.

The ChatGPT Effect: Nursing Education and Generative Artificial Intelligence

This article examines the potential of generative artificial intelligence (AI), such as ChatGPT (Chat Generative Pre-trained Transformer), in nursing education and the associated challenges and recommendations for their use. Generative AI offers potential benefits such as aiding students with assignments, providing realistic patient scenarios for practice, and enabling personalized, interactive learning experiences. However, integrating generative AI in nursing education also presents challenges, including academic integrity issues, the potential for plagiarism and copyright infringements, ethical implications, and the risk of producing misinformation. Clear institutional guidelines, comprehensive student education on generative AI, and tools to detect AI-generated content are recommended to navigate these challenges. The article concludes by urging nurse educators to harness generative AI's potential responsibly, highlighting the rewards of enhanced learning and increased efficiency. The careful navigation of these challenges and strategic implementation of AI is key to realizing the promise of AI in nursing education. [J Nurs Educ. 2024;63(X):XXX-XXX.].

Towards Automated Evaluation of Patient Centered Care-Assessing the Potential of Electronic Health Records

Providing patient centered care is a crucial element of high quality care. It can be defined as a responsive way of caring for and empowering patients, embodying compassion, empathy, and responsiveness to the patient's needs. The aim of this study was to assess the potential of using EHRs as information source in the development of tools for assessing PCC. An annotation guide following the Person-centred Practice Framework proposed by McCance and McCormack was developed for the purpose of this study. Twenty patients' documents were manually annotated, resulting in 539 expressions. All dimensions of the framework were covered in the documents, with 61.3% of expressions describing the activity of engaging authentically with the patient. The results of this study indicate that electronic health records are one potential source of information in automated evaluation of patient centered care, however more information is still needed on how to interpret this information.

The effect of standalone audio-visual feedback devices on the quality of chest compressions during laypersons' cardiopulmonary resuscitation training: a systematic review and meta-analysis

AIMS

Individual studies that investigated the effect of standalone audio-visual feedback (AVF) devices during laypersons' cardiopulmonary resuscitation (CPR) training have yielded conflicting results. This review aimed to evaluate the effect of standalone AVF devices on the quality of chest compressions during laypersons' CPR training.

METHOD AND RESULT

Randomized controlled trials of simulation studies recruiting participants without actual patient CPR experience were included. The intervention evaluated was the quality of chest compressions with standalone AVF devices vs. without AVF devices. Databases, such as PubMed, Cochrane Central, Embase, Cumulative Index to Nursing & Allied Health Literature (CINAHL), Web of Science, and PsycINFO, were searched from January 2010 to January 2022. The risk of bias was assessed using the Cochrane risk of bias tool. A meta-analysis alongside a narrative synthesis was used for examining the effect of standalone AVF devices.Sixteen studies were selected for this systematic review. A meta-analysis revealed an increased compression depth of 2.22 mm [95% CI (Confidence Interval), 0.88-3.55, P = 0.001] when participants performed CPR using the feedback devices. Besides, AVF devices enabled laypersons to deliver compression rates closer to the recommended range of 100-120 per min. No improvement was noted in chest recoil and hand positioning when participants used standalone AVF devices.

CONCLUSION

The quality of the included studies was variable, and different standalone AVF devices were used. Standalone AVF devices were instrumental in guiding laypersons to deliver deeper compressions without compromising the quality of compression rates. However, the devices did not improve the quality of chest recoil and placement of the hands.

REGISTRATION

PROSPERO: CRD42020205754.

Exploring the Documentation of Delirium in Patients After Cardiac Surgery: A Retrospective Patient Record Study

Delirium is a common disorder for patients after cardiac surgery. Its manifestation and care can be examined through EHRs. The aim of this retrospective, comparative, and descriptive patient record study was to describe the documentation of delirium symptoms in the EHRs of patients who have undergone cardiac surgery and to explore how the documentation evolved between two periods (2005-2009 and 2015-2020). Randomly selected care episodes were annotated with a template, including delirium symptoms, treatment methods, and adverse events. The patients were then manually classified into two groups: nondelirious (n = 257) and possibly delirious (n = 172). The data were analyzed quantitatively and descriptively. According to the data, the documentation of symptoms such as disorientation, memory problems, motoric behavior, and disorganized thinking improved between periods. Yet, the key symptoms of delirium, inattention, and awareness were seldom documented. The professionals did not systematically document the possibility of delirium. Particularly, the way nurses recorded structural information did not facilitate an overall understanding of a patient's condition with respect to delirium. Information about delirium or proposed care was seldom documented in the discharge summaries. Advanced machine learning techniques can augment instruments that facilitate early detection, care planning, and transferring information to follow-up care.

Technological Challenges and Solutions in Emergency Remote Teaching for Nursing: An International Cross-Sectional Survey

OBJECTIVES

With the sudden global shift to online learning modalities, this study aimed to understand the unique challenges and experiences of emergency remote teaching (ERT) in nursing education.

METHODS

We conducted a comprehensive online international cross-sectional survey to capture the current state and firsthand experiences of ERT in the nursing discipline. Our analytical methods included a combination of traditional statistical analysis, advanced natural language processing techniques, latent Dirichlet allocation using Python, and a thorough qualitative assessment of feedback from open-ended questions.

RESULTS

We received responses from 328 nursing educators from 18 different countries. The data revealed generally positive satisfaction levels, strong technological self-efficacy, and significant support from their institutions. Notably, the characteristics of professors, such as age (p = 0.02) and position (p = 0.03), influenced satisfaction levels. The ERT experience varied significantly by country, as evidenced by satisfaction (p = 0.05), delivery (p = 0.001), teacher-student interaction (p = 0.04), and willingness to use ERT in the future (p = 0.04). However, concerns were raised about the depth of content, the transition to online delivery, teacher-student interaction, and the technology gap.

CONCLUSIONS

Our findings can help advance nursing education. Nevertheless, collaborative efforts from all stakeholders are essential to address current challenges, achieve digital equity, and develop a standardized curriculum for nursing education.

Evaluating the representation of disaster hazards in SNOMED CT: gaps and opportunities

OBJECTIVE

Climate change, an underlying risk driver of natural disasters, threatens the environmental sustainability, planetary health, and sustainable development goals. Incorporating disaster-related health impacts into electronic health records helps to comprehend their impact on populations, clinicians, and healthcare systems. This study aims to: (1) map the United Nations Office for Disaster Risk Reduction and International Science Council (UNDRR-ISC) Hazard Information Profiles to SNOMED CT International, a clinical terminology used by clinicians, to manage patients and provide healthcare services; and (2) to determine the extent of clinical terminologies available to capture disaster-related events.

MATERIALS AND METHODS

Concepts related to disasters were extracted from the UNDRR-ISC's Hazard Information Profiles and mapped to a health terminology using a procedural framework for standardized clinical terminology mapping. The mapping process involved evaluating candidate matches and creating a final list of matches to determine concept coverage.

RESULTS

A total of 226 disaster hazard concepts were identified to adversely impact human health. Chemical and biological disaster hazard concepts had better representation than meteorological, hydrological, extraterrestrial, geohazards, environmental, technical, and societal hazard concepts in SNOMED CT. Heatwave, drought, and geographically unique disaster hazards were not found in SNOMED CT.

CONCLUSION

To enhance clinical reporting of disaster hazards and climate-sensitive health outcomes, the poorly represented and missing concepts in SNOMED CT must be included. Documenting the impacts of climate change on public health using standardized clinical terminology provides the necessary real time data to capture climate-sensitive outcomes. These data are crucial for building climate-resilient healthcare systems, enhanced public health disaster responses and workflows, tracking individual health outcomes, supporting disaster risk reduction modeling, and aiding in disaster preparedness, response, and recovery efforts.

Structural and Psychological Empowerment of Learners Enrolled in Continuing Nursing Leadership Education in Finland: A Quasi-Experimental Longitudinal Study

BACKGROUND

This study was conducted to assess structural and psychological empowerment among learners enrolled in a continuing leadership education program. Although the number of nurse leadership development interventions has increased, there is little evidence on how they influence leaders' empowerment.

METHOD

A longitudinal study was employed, with learners (N = 85) enrolled in a continuing leadership education program as the participants. Data were collected in the beginning, at the end, and 8 months after the completion of the program using internationally validated instruments. Data were analyzed statistically.

RESULTS

A total of 25 learners (29%) responded to the questionnaire at all three data collection points. The education significantly increased psychological and structural empowerment across all dimensions except formal power. These increased levels of empowerment were partially sustained at the 8-month follow-up time point.

CONCLUSION

Continuing education seems to benefit nurse leaders, and the continuing nursing leadership education program was positively associated with learners' perceived empowerment. [J Contin Educ Nurs. 2023;54(10):462-471.].

Videoconferencing Applications for Training Professionals on Nonverbal Communication in Online Clinical Consultations

OBJECTIVES

The use of videoconferencing technologies for clinician-patient online consultations has become increasingly popular. Training on online communication competence through a videoconferencing application that integrates nonverbal communication detection with feedback is one way to prepare future clinicians to conduct effective online consultations. This case report describes and evaluates two such applications designed for healthcare professionals and students in healthcare-related fields.

METHODS

We conducted a literature review using five databases, including the Web of Science, Scopus, PubMed, ACM, IEEE, and CINAHL in the spring of 2022.

RESULTS

We identified seven studies on two applications, ReflectLive and EQClinic. These studies were conducted by two research groups from the USA and Australia and were published between 2016 and 2020. Both detected nonverbal communication from video and audio and provided computer-generated feedback on users' nonverbal communication. The studies evaluated usability, effectiveness in learning communication skills, and changes in the users' awareness of their nonverbal communication. The developed applications were deemed feasible. However, the feedback given by the applications needs improvement to be more beneficial to the user. The applications were primarily evaluated with medical students, with limited or no attention given to questions regarding ethics, information security, privacy, sustainability, and costs.

CONCLUSIONS

Current research on videoconferencing systems for training online consultation skills is very limited. Future research is needed to develop more user-centered solutions, focusing on a multidisciplinary group of students and professionals, and to explore the implications of these technologies from a broader perspective, including ethics, information security, privacy, sustainability, and costs.

Representation of Environmental Concepts Associated with Health Impacts in Computer Standardized Clinical Terminologies

OBJECTIVE

To evaluate the representation of environmental concepts associated with health impacts in standardized clinical terminologies.

METHODS

This study used a descriptive approach with methods informed by a procedural framework for standardized clinical terminology mapping. The United Nations Global Indicator Framework for the Sustainable Development Goals and Targets was used as the source document for concept extraction. The target terminologies were the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and the International Classification for Nursing Practice (ICNP). Manual and automated mapping methods were utilized. The lists of candidate matches were reviewed and iterated until a final mapping match list was achieved.

RESULTS

A total of 119 concepts with 133 mapping matches were added to the final SNOMED CT list. Fifty-three (39.8%) were direct matches, 37 (27.8%) were narrower than matches, 35 (26.3%) were broader than matches, and 8 (6%) had no matches. A total of 26 concepts with 27 matches were added to the final ICNP list. Eight (29.6%) were direct matches, 4 (14.8%) were narrower than, 7 (25.9%) were broader than, and 8 (29.6%) were no matches.

CONCLUSION

Following this evaluation, both strengths and gaps were identified. Gaps in terminology representation included concepts related to cost expenditures, affordability, community engagement, water, air and sanitation. The inclusion of these concepts is necessary to advance the clinical reporting of these environmental and sustainability indicators. As environmental concepts encoded in standardized terminologies expand, additional insights into data and health conditions, research, education, and policy-level decision-making will be identified.

Nursing Informatics' Contribution to One Health

OBJECTIVES

To summarise contemporary knowledge in nursing informatics related to education, practice, governance and research in advancing One Health.

METHODS

This descriptive study combined a theoretical and an empirical approach. Published literature on recent advancements and areas of interest in nursing informatics was explored. In addition, empirical data from International Medical Informatics Association (IMIA) Nursing Informatics (NI) society reports were extracted and categorised into key areas regarding needs, established activities, issues under development and items not current.

RESULTS

A total of 1,772 references were identified through bibliographic database searches. After screening and assessment for eligibility, 146 articles were included in the review. Three topics were identified for each key area: 1) education: "building basic nursing informatics competence", "interdisciplinary and interprofessional competence" and "supporting educators competence"; 2) practice: "digital nursing and patient care", "evidence for timely issues in practice" and "patient-centred safe care"; 3) governance: "information systems in healthcare", "standardised documentation in clinical context" and "concepts and interoperability", and 4) research: "informatics literacy and competence", "leadership and management", and "electronic documentation of care". 17 reports from society members were included. The data showed overlap with the literature, but also highlighted needs for further work, including more strategies, methods and competence in nursing informatics to support One Health.

CONCLUSIONS

Considering the results of this study, from the literature nursing informatics would appear to have a significant contribution to make to One Health across settings. Future work is needed for international guidelines on roles and policies as well as knowledge sharing.

Digital Information Management for Advanced Practice Nursing: Needs Assessment

The aim of this pilot study was to explore needs related to a quality dashboard for advanced practice nursing to support quality management in a Finnish university hospital.

Electronic Health Records as Information Source in Assessment of the Effectiveness of Delivered Care - A Pilot Study

Effectiveness is a key element of high quality health services. The aim of this pilot study was to explore the potential of electronic health records (EHR) as an information source for assessing the effectiveness of nursing care by investigating the appearance of nursing processes in the documentation of care. Deductive and inductive content analysis were used in a manual annotation of ten patients' EHRs. The analysis resulted in the identification of 229 documented nursing processes. The results indicate that EHRs can be used in decision support systems for assessing effectiveness of nursing care, however, future work is needed to verify these findings in a larger data set and extend to other dimensions related to care quality.

An Augmented Reality Mobile App (Easypod AR) as a Complementary Tool in the Nurse-Led Integrated Support of Patients Receiving Recombinant Human Growth Hormone: Usability and Validation Study

BACKGROUND

Children with growth hormone deficiency face the prospect of long-term recombinant human growth hormone (r-hGH) treatment requiring daily injections. Adherence to treatment is important, especially at treatment initiation, to achieve positive health outcomes. Historically, telenursing services embedded in patient support programs (PSPs) have been a valid approach to support r-hGH treatment initiation and patient education and facilitate adherence by identifying and optimizing appropriate injection techniques. The development of mobile phones with augmented reality (AR) capabilities offers nurses new tools to support patient education.

OBJECTIVE

To investigate experiences among nurses of a new mobile phone app developed to support patient training with a phone-based PSP for r-hGH treatment.

METHODS

In 2020, the Easypod AR mobile app was launched to support nurse-driven telehealth education for patients initiating r-hGH therapy with the Easypod electromechanical auto-injector device. Nurses who were part of PSPs in countries where the Easypod AR app had been launched or where training was provided as part of an anticipated future launch of the app were invited to participate in an online survey based on the Mobile App Rating Scale to capture their feedback after using the app.

RESULTS

In total, 23 nurses completed the online questionnaire. They positively rated the quality of the app across multiple dimensions. The highest mean scores were 4.0 for engagement (ie, adaptation to the target group; SD 0.74), 4.1 (SD 0.79) for functionality (navigation) and 4.1 (SD 0.67) for aesthetics (graphics). Responses indicated the potential positive impact of such a tool on enhancing patient education, patient support, and communication between patients and PSP nurses. Some participants also suggested enhancements to the app, including gamification techniques that they felt have the potential to support the formation of positive treatment behaviors and habits.

CONCLUSIONS

This study highlights the potential for new digital health solutions to reinforce PSP nurse services, including patient education. Future studies could explore possible correlations between any behavioral and clinical benefits that patients may derive from the use of such apps and how they may contribute to support improved patient experiences and treatment outcomes.

Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery

AIM

The aim of this study was to describe what psychosocial factors associated with postoperative persistent pain can be found in electronic health records of patients with breast cancer, and which of these factors that may be used in the development of a decision-support system algorithm to better support health professionals in their clinical work.

DESIGN

A qualitative descriptive study.

METHODS

A retrospective electronic health record review was done using manual semantic annotation. A set of 101 records of patients with breast cancer were selected by computerized random sampling. The data were analysed with deductive content analysis.

RESULTS

A total of 337 different expressions describing psychosocial factors associated with postoperative persistent pain were identified from the documentation done in the electronic health records. These regarded psychological strength and resilience, social factors, emotional factors, anxiety, sleep-related factors and depression. No records were found dealing with pain catastrophizing. Although psychosocial factors associated with postoperative persistent pain were documented in the electronic health records, documentation about such factors was not found in all patient's records, nor was the documentation done in a systematic manner.

CONCLUSIONS

The findings show that there is potential to use electronic health records as information source in the development of decision-support system algorithms to better support nurses in the identification of patients at risk of developing postoperative persistent pain. However, the documentation quality needs to be acknowledged in the application of decision support systems, which are built on information extracted from electronic health records. Future work is needed to standardize documentation practices and assess the comprehensiveness of the documentation.

Assessing the carbon footprint of digital health interventions: a scoping review

OBJECTIVE

Integration of environmentally sustainable digital health interventions requires robust evaluation of their carbon emission life-cycle before implementation in healthcare. This scoping review surveys the evidence on available environmental assessment frameworks, methods, and tools to evaluate the carbon footprint of digital health interventions for environmentally sustainable healthcare.

MATERIALS AND METHODS

Medline (Ovid), Embase (Ovid). PsycINFO (Ovid), CINAHL, Web of Science, Scopus (which indexes IEEE Xplore, Springer Lecture Notes in Computer Science and ACM databases), Compendex, and Inspec databases were searched with no time or language constraints. The Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA_SCR), Joanna Briggs Scoping Review Framework, and template for intervention description and replication (TiDiER) checklist were used to structure and report the findings.

RESULTS

From 3299 studies screened, data was extracted from 13 full-text studies. No standardised methods or validated tools were identified to systematically determine the environmental sustainability of a digital health intervention over its full life-cycle from conception to realisation. Most studies (n = 8) adapted publicly available carbon calculators to estimate telehealth travel-related emissions. Others adapted these tools to examine the environmental impact of electronic health records (n = 2), e-prescriptions and e-referrals (n = 1), and robotic surgery (n = 1). One study explored optimising the information system electricity consumption of telemedicine. No validated systems-based approach to evaluation and validation of digital health interventions could be identified.

CONCLUSION

There is a need to develop standardised, validated methods and tools for healthcare environments to assist stakeholders to make informed decisions about reduction of carbon emissions from digital health interventions.

The Essence and Role of Nurses in the Future of Biomedical and Health Informatics

The whole healthcare system is evolving fast due to environmental pressure related to pandemics, climate change, personnel shortages, and financial limitations, to name but a few. Nurses are central actors in the sustainability of healthcare systems. Rapid technological development can support innovative means for holistic and applied critical thinking to improve healthcare delivery based on the uniqueness of nursing. Nurses need to develop adaptive and scientific skills regarding technologies and develop and apply these for better use of "smart" systems in care delivery. The paradigm shift in nursing roles will impact all levels of care, from primary to specialized care, all age groups, from newborn to elderly care, as well as all domains, such as preventive, reparative, rehabilitation, and palliative care. The impact of technologies on human behavior addresses human- factors interaction, computer interaction, and other effects of technologies on wellbeing, including but not limited to robots and artificial intelligence -based assisting nursing deliveries. Nursing competencies need to be developed at all levels of education to prepare a mindset and culture of the healthcare workforce in a digital health system. Gamification and simulation as educational tools help prepare educators to educate healthcare clinicians and researchers who become key mediators between technologies and practice.

Structural and psychological empowerment of students obtaining continuing leadership education in Finland-a national survey

BACKGROUND

In nursing, empowerment may be deemed one's potential to gain power, achieve goals and promote one's skills to advance positive changes in the working environment, or decentralization of authority. Empowerment is associated with nurses' and nurse leaders' satisfaction, performance and organizational commitment, as well as burnout, emotional exhaustion and intentions to leave the profession. Research on nurse empowerment in relation to continuing education is sparse.

OBJECTIVES

This study describes the structural and psychological empowerment levels of students beginning a collaboratively implemented continuing leadership education program.

DESIGN

Cross-sectional electronic survey.

SETTINGS

National, continuing nursing leadership education program (37 ECT) organized by five universities that provide masters level education to nurse leaders in Finland.

PARTICIPANTS

Students (N = 85) working at nine healthcare organizations across the service system as current or prospective nurse leaders and enrolled in the continuing leadership education program.

METHODS

The Conditions of Work Effectiveness Questionnaire and the Work Empowerment Questionnaire were each used to measure structural and psychological empowerment, respectively. The data were collected between October 2019 and February 2020.

RESULTS

A total of 69 students participated (response rate 81 %). Moderate levels of both structural and psychological empowerment were observed. In structural empowerment, the strongest dimension was access to opportunity (4.1, SD 0.7), whereas access to support was the weakest (2.7, SD 0.7). The strongest psychological empowerment dimension was verbal empowerment (8.5, SD 1.9) and the weakest was outcome empowerment (7.0, SD 1.6).

CONCLUSIONS

Nurses and nurse leaders seem to lack the status and power required to impact their organizations, possibly causing them to apply for nursing leadership education. Nurse leaders should be given opportunities for continuing leadership education to improve empowerment and, as a result, staff outcomes.

Towards Automated Screening of Literature on Artificial Intelligence in Nursing

We evaluate the performance of multiple text classification methods used to automate the screening of article abstracts in terms of their relevance to a topic of interest. The aim is to develop a system that can be first trained on a set of manually screened article abstracts before using it to identify additional articles on the same topic. Here the focus is on articles related to the topic "artificial intelligence in nursing". Eight text classification methods are tested, as well as two simple ensemble systems. The results indicate that it is feasible to use text classification technology to support the manual screening process of article abstracts when conducting a literature review. The best results are achieved by an ensemble system, which achieves a F1-score of 0.41, with a sensitivity of 0.54 and a specificity of 0.96. Future work directions are discussed.

Text Classification Model Explainability for Keyword Extraction - Towards Keyword-Based Summarization of Nursing Care Episodes

Tools to automate the summarization of nursing entries in electronic health records (EHR) have the potential to support healthcare professionals to obtain a rapid overview of a patient's situation when time is limited. This study explores a keyword-based text summarization method for the nursing text that is based on machine learning model explainability for text classification models. This study aims to extract keywords and phrases that provide an intuitive overview of the content in multiple nursing entries in EHRs written during individual patients' care episodes. The proposed keyword extraction method is used to generate keyword summaries from 40 patients' care episodes and its performance is compared to a baseline method based on word embeddings combined with the PageRank method. The two methods were assessed with manual evaluation by three domain experts. The results indicate that it is possible to generate representative keyword summaries from nursing entries in EHRs and our method outperformed the baseline method.

The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review

OBJECTIVES

The objective of this paper is to draw attention to the currently underused potential of clinical documentation by nursing and allied health professions to improve the representation of social determinants of health (SDoH) and intersectionality data in electronic health records (EHRs), towards the development of equitable artificial intelligence (AI) technologies.

METHODS

A rapid review of the literature on the inclusion of nursing and allied health data and the nature of health equity information representation in the development and/or use of artificial intelligence approaches alongside expert perspectives from the International Medical Informatics Association (IMIA) Student and Emerging Professionals Working Group.

RESULTS

Consideration of social determinants of health and intersectionality data are limited in both the medical AI and nursing and allied health AI literature. As a concept being newly discussed in the context of AI, the lack of discussion of intersectionality in the literature was unsurprising. However, the limited consideration of social determinants of health was surprising, given its relatively longstanding recognition and the importance of representation of the features of diverse populations as a key requirement for equitable AI.

CONCLUSIONS

Leveraging the rich contextual data collected by nursing and allied health professions has the potential to improve the capture and representation of social determinants of health and intersectionality. This will require addressing issues related to valuing AI goals (e.g., diagnostics versus supporting care delivery) and improved EHR infrastructure to facilitate documentation of data beyond medicine. Leveraging nursing and allied health data to support equitable AI development represents a current open question for further exploration and research.

Assessment of Health Service Quality Through Electronic Health Record - A Scoping Review

The World Health Organization defines, that high quality health services should be effective, safe, people-centered, timely, equitable, integrated, and effective. This requires systematic quality assessment. The aim of this scoping review was to explore how electronic health records (EHRs) have been used to assess quality of health services using the WHO criteria. A total of 4247 records were obtained whereof 8 studies were included in the review. Research showed that EHRs were used to evaluate safety, performance and care processes. EHRs were regarded as an applicable real-world data source, highlighting the importance of consistency and standardised terminologies. Use of EHR data is limited to its representation of the real world and current evaluation systems have limited quality criteria, diverse definitions and they use only structured data. Future research should explore possibilities of natural language processing methods and include narrative EHR information for a more a comprehensive view of service quality assessment.

Clustering Nursing Sentences - Comparing Three Sentence Embedding Methods

In health sciences, high-quality text embeddings may augment qualitative data analysis of large amounts of text by enabling, e.g., searching and clustering of health information. This study aimed to evaluate three different sentence-level embedding methods in clustering sentences in nursing narratives from individual patients' hospital care episodes. Two of these embeddings are generated from language models based on the BERT framework, and the third on the Sent2Vec method. These embedding methods were used to cluster sentences from 20 patient care episodes and the results were manually evaluated. Findings suggest that the best clusters were produced by the embeddings from a BERT model fine-tuned for the proxy task of predicting subject headings for nursing text.

Terveydenhuollon digitaalisten tietojärjestelmien vaikutus hoitohenkilöstöön ja potilastuloksiin: Kartoittava kirjallisuuskatsaus hoitotyön näkökulmasta

Tämän kartoittavan kirjallisuuskatsauksen tarkoituksena oli koota tutkimusnäyttöä terveyspalveluiden digitaalisten tietojärjestelmien vaikuttavuudesta hoitohenkilöstöön ja potilastuloksiin. Sisäänottokriteerit olivat: tutkimus käsittelee terveydenhuollon digitaalista tietojärjestelmää, joka on käytössä kliinisessä työssä sekä sen vaikutusta hoidon laatuun, hoitohenkilöstön tai potilaiden tyytyväisyyteen, toiminnan tehokkuuteen, hoidon tuloksiin, työn prosessiin tai hoidon kustannuksiin. Pois jätettiin viivakodin lukijat, johtamisen tietojärjestelmät ja mobiililaitteita käsittelevät tutkimukset, sekä tekoälyyn, herätteisiin, asioiden internetiin ja robotiikkaan pohjautuvat tutkimukset. Tiedonhaussa käytettiin neljää tietokantaa: CINAHL, Cochrane Library, PubMed ja Web of Science. Tuloksena löytyi 2400 artikkelia, joista 16 otettiin mukaan tutkimukseen. Artikkelit oli julkaistu vuosina 1995–2020. Tulokset analysoitiin deduktiivisella sisällönanalyysillä. Neljä tukimusta oli tehty kokeellisella asetelmalla ja 12 oli tehty kvasikokeellisella asetelmalla. Tutkimusten laatupisteet olivat keskinkertaisia. Tietojärjestelmistä käytetyt termit muodostivat yläkategoriat: Potilasasiakirja, lääkehoidon prosessi, tiedon automaattinen tallennus sekä potilasportaali. Suurin osa tutkimuksista keskittyi potilasasiakirjoihin. Järjestelmien päätehtäviä olivat lääkehoidon prosessin tukeminen ja digitaalinen hoitotyön kirjaus. Digitaalisia tietojärjestelmiä verrattiin paperisiin järjestelmiin ja dataa kerättiin kyselylomakkeilla tai aika- ja liikeanalyysin avulla. Hoitohenkilöstön tuloksiin liittyen tutkituimpia aiheita olivat ajankäyttö ja tyytyväisyys, joiden suhteen tulokset jäivät ristiriitaisiksi. Potilastulokset eivät tulleet aineistossa esiin laajasti. Neljässä potilastuloksia koskevassa tutkimuksessa havaittiin kuitenkin niin positiivisia kuin negatiivisia vaikutuksia. Tulosten perusteella voidaan todeta, että näyttö digitaalisen tietojärjestelmien vaikutuksesta henkilöstöön ja potilastuloksiin on vielä vähäistä ja digitaalisten tietojärjestelmien terminologia ja määritelmät ovat hajanaisia. Korkeatasoista näyttöä vaikuttavuudesta käytännön ympäristössä tarvitaan enemmän erityisesti siitä, miten tietojärjestelmät vaikuttavat potilastuloksiin.

Self-Management Capacity in Adults with Type 2 Diabetes Using Educational Interventions: A Pilot Study

Type 2 Diabetes (T2D) has been increasing in prevalence over the last decade in Mexico. The glycemic control actions can help to prevent complications. The aimed is to pilot an educational intervention in self- management of adults with T2D through using text messages. Findings show the respondents reported a low level of self-care skills of T2D and there was an increase in the self-care skills after it.

Nursing Informatics Research Trends: Findings from an International Survey

This follow-up survey on trends in Nursing Informatics (NI) was conducted by the International Medical Informatics Association (IMIA) Student and Emerging Professionals (SEP) group as a cross-sectional study in 2019. There were 455 responses from 24 countries. Based on the findings NI research is evolving rapidly. Current ten most common trends include: clinical quality measures, clinical decision support, big data, artificial intelligence, care coordination, education and competencies, patient safety, mobile health, description of nursing practices and evaluation of patient outcomes. The findings help support the efforts to efficiently use resources in the promotion of health care activities, to support the development of informatics education and to grow NI as a profession.

Will Artificial Intelligence Replace Nurses? A Debate

Technological development has enabled Artificial Intelligence (AI) to better support health care delivery and nursing. The need for nurses to be involved and steer the development and implementation of AI in health care is recognized. A 60-minute scientific debate is organized to explore if AI will replace nursing.

Description of the Process to Validate the Mexican Nurse Informatics Competency Self-Assessment Scale

Nurses need to have sufficient competencies in nursing informatics to be able to provide safe and efficient care. The Self-Assessment of Nursing Informatics Competencies Scale (SANICS) has been developed and validated as a self-report measure of informatics competencies in Western settings. In this work, we describe the ongoing study that aims to validate and translate SANICS into the Mexican setting.

Impact of a digital care logistics system on care duration, consumer satisfaction and shift leaders' workload in emergency departments

The primary goal of introducing digital information systems in healthcare organisations is to improve care processes and outcomes, however, studies that investigate the impact of digital information systems on the day-to-day operations management from the perspective of workflow and consumer satisfaction in emergency departments are scarce. Therefore, this study aimed to explore the impact of a digital clinical logistics system on the duration of patient care, consumer satisfaction and shift leaders' experience of workload in emergency departments. A longitudinal prospective design was used. Three units participated in the study; an intervention unit, a control unit A (no implemented system) and a control unit B (system already in use). We collected data on care duration, consumer satisfaction and shift leaders' experience of workload for four weeks at five time points both before system implementation (summer 2015, spring 2016) and after system implementation (summer 2016, autumn 2016, winter 2016). The average care duration time increased in the postimplementation period in the intervention and control B units (p < 0.001). Duration of care was higher in the intervention unit than control unit B in summer 2016 (p < 0.001) and winter 2016 (p = 0.009). Similarly, duration of care in control unit A was higher than control unit B in spring 2016 (p < 0.001). Consumer satisfaction decreased in the intervention unit, in winter 2016 (p < 0.001) and the experience of workload increased in the intervention unit, in summer 2016 and autumn 2016 (p < 0.05). However, the patients-to-nurses ratio was doubled in the intervention unit in the last time point postimplementation when compared to the first timepoint, while it remained similar in the control units throughout the study period. This work demonstrated that a digital care logistics system may support in increasing the number of patients treated with the same nursing resources. However, this seems to connect to other outcome variables such as increased care duration, increased experience of workload and decreased consumer satisfaction in some postimplementation time points.

Exploring nurses' online perspectives and social networks during a global pandemic COVID-19

Objectives

Examine the online interactions, social networks, and perspectives of nursing actors on COVID‐19 from conversations on Twitter to understand how the profession responded to this global pandemic.

Design

Mixed methods.

Sample

Ten‐thousand five‐hundred and seventy‐four tweets by 2790 individuals and organizations.

Measurements

NodeXL software was used for social network analysis to produce a network visualization. The betweenness centrality algorithm identified key users who were influential in COVID‐19 related conversations on Twitter. Inductive content analysis enabled exploration of tweet content. A communicative figurations framework guided the study.

Results

Nursing actors formed different social groupings, and communicated with one another across groups. Tweets covered four themes; (1) outbreak and clinical management of the infectious disease, (2) education and information sharing, (3) social, economic, and political context, and (4) working together and supporting each other.

Conclusion

In addition to spreading knowledge, nurses tried to reach out through social media to political and healthcare leaders to advocate for improvements needed to address COVID‐19. However, they primarily conversed within their own professional community. Action is needed to better understand how social media is and can be used by nurses for health communication, and to improve their preparedness to be influential on social media beyond the nursing community.

How to Improve Information Technology to Support Healthcare to Address the COVID-19 Pandemic: an International Survey with Health Informatics Experts

OBJECTIVES

To identify the ways in which healthcare information and communication technologies can be improved to address the challenges raised by the COVID-19 pandemic.

METHODS

The study population included health informatics experts who had been involved with the planning, development and deployment of healthcare information and communication technologies in healthcare settings in response to the challenges presented by the COVID-19 pandemic. Data were collected via an online survey. A non-probability convenience sampling strategy was employed. Data were analyzed with content analysis.

RESULTS

A total of 65 participants from 16 countries responded to the conducted survey. The four major themes regarding recommended improvements identified from the content analysis included: improved technology availability, improved interoperability, intuitive user interfaces and adoption of standards of care. Respondents also identified several key healthcare information and communication technologies that can help to provide better healthcare to patients during the COVID-19 pandemic, including telehealth, advanced software, electronic health records, remote work technologies (e.g., remote desktop computer access), and clinical decision support tools.

CONCLUSIONS

Our results help to identify several important healthcare information and communication technologies, recommended by health informatics experts, which can help to provide better care to patients during the COVID-19 pandemic. The results also highlight the need for improved interoperability, intuitive user interfaces and advocating the adoption of standards of care.

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative

Aim

To develop a consensus paper on the central points of an international invitational think‐tank on nursing and artificial intelligence (AI).

Methods

We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3‐day invitational think tank in autumn 2019. Activities included a pre‐event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities.

Implications for nursing

Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice.

Conclusion

There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems.

Impact

We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.

Supporting the use of standardized nursing terminologies with automatic subject heading prediction: a comparison of sentence-level text classification methods

Objective

This study focuses on the task of automatically assigning standardized (topical) subject headings to free-text sentences in clinical nursing notes. The underlying motivation is to support nurses when they document patient care by developing a computer system that can assist in incorporating suitable subject headings that reflect the documented topics. Central in this study is performance evaluation of several text classification methods to assess the feasibility of developing such a system.

Materials and Methods

Seven text classification methods are evaluated using a corpus of approximately 0.5 million nursing notes (5.5 million sentences) with 676 unique headings extracted from a Finnish university hospital. Several of these methods are based on artificial neural networks. Evaluation is first done in an automatic manner for all methods, then a manual error analysis is done on a sample.

Results

We find that a method based on a bidirectional long short-term memory network performs best with an average recall of 0.5435 when allowed to suggest 1 subject heading per sentence and 0.8954 when allowed to suggest 10 subject headings per sentence. However, other methods achieve comparable results. The manual analysis indicates that the predictions are better than what the automatic evaluation suggests.

Conclusions

The results indicate that several of the tested methods perform well in suggesting the most appropriate subject headings on sentence level. Thus, we find it feasible to develop a text classification system that can support the use of standardized terminologies and save nurses time and effort on care documentation.

Assisting nurses in care documentation: from automated sentence classification to coherent document structures with subject headings

Background

Up to 35% of nurses’ working time is spent on care documentation. We describe the evaluation of a system aimed at assisting nurses in documenting patient care and potentially reducing the documentation workload. Our goal is to enable nurses to write or dictate nursing notes in a narrative manner without having to manually structure their text under subject headings. In the current care classification standard used in the targeted hospital, there are more than 500 subject headings to choose from, making it challenging and time consuming for nurses to use.

Methods

The task of the presented system is to automatically group sentences into paragraphs and assign subject headings. For classification the system relies on a neural network-based text classification model. The nursing notes are initially classified on sentence level. Subsequently coherent paragraphs are constructed from related sentences.

Results

Based on a manual evaluation conducted by a group of three domain experts, we find that in about 69% of the paragraphs formed by the system the topics of the sentences are coherent and the assigned paragraph headings correctly describe the topics. We also show that the use of a paragraph merging step reduces the number of paragraphs produced by 23% without affecting the performance of the system.

Conclusions

The study shows that the presented system produces a coherent and logical structure for freely written nursing narratives and has the potential to reduce the time and effort nurses are currently spending on documenting care in hospitals.

Exploring Unsupervised Query Paraphrasing to Identify Relevant Search Phrases for a Literature Review

Literature databases have multifaceted search options, but emerging research areas do not have an established terminology and therefore it is difficult to find relevant literature when conducting a review. This study aimed to explore if an unsupervised paraphrasing approach is useful in identifying relevant search phrases for a literature review on an emerging research topic - situational leadership in critical care. Using an initial set of 12 search phrases, the system was used to propose additional phrases, which were manually classified and further used in an expanded PubMed database search. Finally, we assessed the papers found with the expanded search and compared this to the initial search results. As a result, the expanded search more than tripled the search results, from 182 to 673 papers. The expanded search also more than tripled the number of relevant papers, from 12 in the original search to 39 in the expanded search.

An observational study of technical and non-technical skills in advanced life support in the clinical setting

OBJECTIVE

Technical skills (TS) and non-technical skills (NTS) are the primary elements ensuring patient safety during advanced life support (ALS) and effective crisis resource management (CRM). Both skills are needed to perform high-quality ALS, though they are traditionally practiced separately. The evidence of the association between NTS and TS in high-quality ALS performance is insufficient. Hence, we aimed to evaluate the association between the skills in real-life in-hospital ALS situations.

METHODS

We video recorded real-life in-hospital ALS situations, analyzed TS and NTS demonstrated in them with an instrument measuring TS and NTS, and tested the linear association between NTS and TS using a linear mixed model.

RESULTS

Among 50 real-life in-hospital ALS situations that we recorded, 20 had adequate data for analysis. NTS and TS total scores were associated with one another (slope 0.48, P < 0.001). All NTS subcategories were associated with the TS total score (slopes ranging from 0.29 to 0.39, P < 0.001). The NTS total score and TS subcategories (chest compression quality, ventilation quality, rhythm control and defibrillation quality) were associated with one another (slopes ranging from 0.37 to 0.56, P < 0.01).

CONCLUSIONS

The resuscitation teams who demonstrated good NTS also performed the technical aspects of ALS better. The results suggest that NTS and TS have an association with one another in real-life in-hospital ALS situations. NTS performance had the most evident association with chest compression quality and rhythm control and defibrillation quality; these are considered the most crucial elements affecting outcomes of ALS. The findings of the study present novel information of what and why to emphasize in ALS training.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT03017144.

A Digital Service Logistics Information System for Emergency Department Care Coordination - Professionals' Experiences

The aim was to describe nurses' and physicians' perceptions of a digital service logistics information system from an operative management perspective in emergency departments (EDs). A total of 24 professionals were interviewed. Based on the results the information systems support operative management of EDs but the professionals desire more detailed information about patients and staff to support situational awareness in the operative management of these units.

The current state of Nursing Informatics – An international cross-sectional survey

An international survey to explore current and future trends in Nursing Informatics (NI) was done in 2015. This article explores responses to questions about: what should be done to further develop NI as an independent discipline; existing policies and standards influencing NI; perceived support towards NI as a discipline; and advice from NI specialists to students and emerging professionals. Nurse and allied health professionals in academia and practice were reached with snowball sampling. Open-ended questions were analysed with thematic content analysis and the mean and standard deviation is reported for the perceived support towards NI (scale ranging from 1 (not at all supportive) to 10 (very supportive)). A total of 507 respondents from 46 countries responded to the survey. Respondents reported mediocre support towards NI from the environment (M 5.79, SD 2.60). Results showed that NI education needs development to better meet practice demands, that current NI resources seem insufficient, that NI expertise is not used to its full potential in health institutions and the community, and that NI needs to show its value through research and increase visibility to be recognised among stakeholders worldwide. In conclusion, there is a need to clarify NI as a discipline and a need for strong leadership to impact policy making. An increase in NI teaching at undergraduate level in nursing as well as an increase in postgraduate NI programmes worldwide would better support practice demands. National policies and international white papers in NI are needed to guide resource distribution to better support practice.

Pain process of patients with cardiac surgery-Semantic annotation of electronic patient record data

AIMS AND OBJECTIVES

To describe and compare the pain process of the patients' with cardiac surgery through nurses' and physicians' documentations in the electronic patient records.

BACKGROUND

Postoperative pain assessment and management should be documented regularly, to ensure optimal pain care process for patients. Despite availability of evidence-based guidelines, pain assessment and documentation remain inadequate.

DESIGN

A retrospective patients' record review.

METHODS

The original data consisted of the electronic patient records of 26,922 patients with a diagnosed heart disease. A total of 1,818 care episodes of patients with cardiac surgery were selected from the data. We used random sampling to obtain 280 care episodes for annotation. These 280 care episodes contained 2,156 physician reports and 1,327 days of nursing notes. We developed an annotation manual and schema, and then, we manually conducted semantic annotation on care episodes, using the Brat annotation tool. We analysed the annotation units using thematic analysis. Consolidated criteria for reporting qualitative research guideline was followed in reporting where appropriate in this study design.

RESULTS

We discovered expressions of six different aspects of pain process: (a) cause, (b) situation, (c) features, (d) consequences, (e) actions and (f) outcomes. We determined that five of the aspects existed chronologically. However, the features of pain were simultaneously existing. They indicated the location, quality, intensity, and temporality of the pain and they were present in every phase of the patient's pain process. Cardiac and postoperative pain documentations differed from each other in used expressions and in the quantity and quality of descriptions.

CONCLUSION

We could construct a comprehensive pain process of the patients with cardiac surgery from several electronic patient records. The challenge remains how to support systematic documentation in each patient.

RELEVANCE TO CLINICAL PRACTICE

The study provides knowledge and guidance of pain process aspects that can be used to achieve an effective pain assessment and more comprehensive documentation.