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As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System provides public health surveillance of US violent deaths; however, understanding the National Violent Death Reporting System's research utility is limited. The purpose of our rapid review of the 2019-2023 literature was to understand to what extent artificial intelligence methods are being used with the National Violent Death Reporting System. We identified 16 National Violent Death Reporting System artificial intelligence studies, with more than half published after 2020. The text-rich content of National Violent Death Reporting System enabled researchers to center their artificial intelligence approaches mostly on natural language processing (50%) or natural language processing and machine learning (37%). Significant heterogeneity in approaches, techniques, and processes was noted across the studies, with critical methods information often lacking. The aims and focus of National Violent Death Reporting System studies were homogeneous and mostly examined suicide among nurses and older adults. Our findings suggested that artificial intelligence is a promising approach to the National Violent Death Reporting System data with significant untapped potential in its use. Artificial intelligence may prove to be a powerful tool enabling nursing scholars and practitioners to reduce the number of preventable, violent deaths. This study aimed to identify the main themes from exit interviews of adult patients with type 2 diabetes after completion of a diabetes education program. Eighteen participants with type 2 diabetes completed an exit interview regarding their program experience and satisfaction. Semistructured interview questions were used, and the interviews were auto-recorded. The interview transcripts were preprocessed and analyzed using four natural language processing–based text-mining techniques. The top 30 words from the term frequency and term frequency–inverse document frequency each were derived. In the N-gram analysis, the connection strength of “diabetes” and “education” was the highest, and the simultaneous connectivity of word chains ranged from a maximum of seven words to a minimum of two words. Based on the CONvergence of iteration CORrelation (CONCOR) analysis, three clusters were generated, and each cluster was named as follows: participation in a diabetes education program to control blood glucose, exercise, and use of digital devices. This study using text mining proposes a new and useful approach to visualize data to develop patient-centered diabetes education. No abstract available Improving nurses' situation awareness skills would likely improve patient status recognition and prevent adverse events. Technologies such as electronic health record dashboards can be a promising approach to support nurses' situation awareness. However, the effect of these dashboards on this skill is unknown. This systematic literature review explores the evidence around interventions to improve nurses' situation awareness at the point of care. Current research on this subject is limited. Studies that examined the use of electronic health record dashboards as an intervention had weak evidence to support their effectiveness. Other interventions, including communication interventions and structured nursing assessments, may also improve situation awareness, but more research is needed to confirm this. It is important to carefully consider the design and content of situation awareness interventions, as well as the specific outcomes being measured, when designing situation awareness interventions. Overall, there is a need for higher-quality research in this area to determine the most effective interventions for improving nurse situation awareness. Future studies should focus on developing dashboards that follow a theoretical situation awareness model information and represent all situation awareness levels. No abstract available The poor usability of electronic health records contributes to increased nurses' workload, workarounds, and potential threats to patient safety. Understanding nurses' perceptions of electronic health record usability and incorporating human factors engineering principles are essential for improving electronic health records and aligning them with nursing workflows. This review aimed to synthesize studies focused on nurses' perceived electronic health record usability and categorize the findings in alignment with three human factor goals: satisfaction, performance, and safety. This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five hundred forty-nine studies were identified from January 2009 to June 2023. Twenty-one studies were included in this review. The majority of the studies utilized reliable and validated questionnaires (n = 15) to capture the viewpoints of hospital-based nurses (n = 20). When categorizing usability-related findings according to the goals of good human factor design, namely, improving satisfaction, performance, and safety, studies used performance-related measures most. Only four studies measured safety-related aspects of electronic health record usability. Electronic health record redesign is necessary to improve nurses' perceptions of electronic health record usability, but future efforts should systematically address all three goals of good human factor design. Hospitals are experiencing a nursing shortage crisis that is expected to worsen over the next decade. Acute care settings, which manage the care of very complex patients, need innovations that lessen nurses' workload burden while ensuring safe patient care and outcomes. Thus, a pilot study was conducted to evaluate the feasibility of implementing a large-scale acute care telenurse program, where a hospital-employed telenurse would complete admission and discharge processes for hospitalized patients virtually. In 3 months, almost 9000 (67%) of patient admissions and discharges were conducted by an acute care telenurse, saving the bedside nurse an average of 45 minutes for each admission and discharge. Preliminary benefits to the program included more uninterrupted time with patients, more complete hospital admission and discharge documentation, and positive patient and nurse feedback about the program. Knowledge models inform organizational behavior through the logical association of documentation processes, definitions, data elements, and value sets. The development of a well-designed knowledge model allows for the reuse of electronic health record data to promote efficiency in practice, data interoperability, and the extensibility of data to new capabilities or functionality such as clinical decision support, quality improvement, and research. The purpose of this article is to describe the development and validation of a knowledge model for healthcare-associated venous thromboembolism prevention. The team used FloMap, an Internet-based survey resource, to compare metadata from six healthcare organizations to an initial draft model. The team used consensus decision-making over time to compare survey results. The resulting model included seven panels, 41 questions, and 231 values. A second validation step included completion of an Internet-based survey with 26 staff nurse respondents representing 15 healthcare organizations, two electronic health record vendors, and one academic institution. The final knowledge model contained nine Logical Observation Identifiers Names and Codes panels, 32 concepts, and 195 values representing an additional six panels (groupings), 15 concepts (questions), and the specification of 195 values (answers). The final model is useful for consistent documentation to demonstrate the contribution of nursing practice to the prevention of venous thromboembolism. Computer-based technologies have been widely used in nursing education, although the best educational modality to improve documentation and nursing diagnostic accuracy using electronic health records is still under investigation. It is important to address this gap and seek an effective way to address increased accuracy around nursing diagnoses identification. Nursing diagnoses are judgments that represent a synthesis of data collected by the nurse and used to guide interventions and to achieve desirable patients' outcomes. This current investigation is aimed at comparing the nursing diagnostic accuracy, satisfaction, and usability of a computerized system versus a traditional paper-based approach. A total of 66 nursing students solved three validated clinical scenarios using the NANDA-International terminologies traditional paper-based approach and then the computer-based Clinical Decision Support System. Study findings indicated a significantly higher nursing diagnostic accuracy (P Care coordination is a crucial component of healthcare systems. However, little is known about data needs and uses in ambulatory care coordination practice. Therefore, the purpose of this study was to identify information gathered and used to support care coordination in ambulatory settings. Survey respondents (33) provided their demographics and practice patterns, including use of electronic health records, as well as data gathered and used. Most of the respondents were nurses, and they described varying practice settings and patterns. Although most described at least partial use of electronic health records, two respondents described paper documentation systems. More than 25% of respondents gathered and used most of the 72 data elements, with collection and use often occurring in multiple locations and contexts. This early study demonstrates significant heterogeneity in ambulatory care coordination data usage. Additional research is necessary to identify common data elements to support knowledge development in the context of a learning health system. 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. This study aims to describe the prototype development and testing of a serious game designed for Brazilian children with diabetes. Following an approach of user-centered design, the researchers assessed game's preferences and diabetes learning needs to develop a Paper Prototype. The gameplay strategies included diabetes pathophysiology, self-care tasks, glycemic management, and food group learning. Diabetes and technology experts (n = 12) tested the prototype during audio-recorded sessions. Next, they answered a survey to evaluate the content, organization, presentation, and educational game aspects. The prototype showed a high content validity ratio (0.80), with three items not achieving the critical values (0.66). Experts recommended improving the game content and food illustrations. This evaluation contributed to the medium-fidelity prototype version, which after testing with diabetes experts (n = 12) achieved high content validity values (0.88). One item did not meet the critical values. Experts suggested increasing the options of outdoor activities and meals. Researchers also observed and video-recorded children with diabetes (n = 5) playing the game with satisfactory interaction. They considered the game enjoyable. The interdisciplinary team plays an important role guiding the designers in the use of theories and real needs of children. Prototypes are a low-cost usability and a successful method for evaluating games. This study aimed to describe the process of construction, validation, and usability of the chatbot ESTOMABOT to assist in the self-care of patients with intestinal ostomies. Methodological research was conducted in three phases: construction, validation, and usability. The first stage corresponded to the elaboration of a script through a literature review, and the second stage corresponded to face and content validation through a panel of enterostomal therapy nurses. In the third phase, the usability of ESTOMABOT was assessed with the participation of surgical clinic nurses, patients with intestinal elimination ostomies, and information technology professionals, using the System Usability Scale. The ESTOMABOT content reached excellent criteria of adequacy, with percentages of agreement equal to or greater than 90%, which were considered adequate, relevant, and representative. The evaluation of the content validity of the script using the scale content validity index/average proportion method reached a result above 0.90, and the Fleiss κ was excellent (P This study aimed to identify topics and within-topic core keywords in premature infant–related nursing studies published in Korean and international academic journals using topic modeling and to compare and analyze the trends in Korean and international studies. Journal databases were searched to extract nursing studies involving premature infants from 1998 to 2020. Journal databases included MEDLINE, Web of Science, CINAHL, and EMBASE for international studies and DBpia, the National Digital Science Library, the Korea Citation Index, and the Research Information Sharing Service for Korean studies. Abstracts from the selected 182 Korean and 2502 international studies were analyzed using NetMiner4.4.3e. In results, four similar topics (Korean vs international) were “pain intervention” versus “pain management”; “breast feeding practice” versus “breast feeding”; “kangaroo mother care”; and “parental stress” versus “stress & depression.” Two topics that appeared only in the international studies were “infection management” and “oral feeding & respiratory care.” Overall, the international studies dealt with diverse topics directly associated with premature. Korean studies mainly dealt with topics related to mothers of premature infants, whereas studies related to premature infants were insufficient. Nursing research in Korea needs to be expanded to research topics addressing premature infants. This pilot study tested the feasibility of Lantern program, an adherence program to HIV medications using WhatsApp, a secure social media messaging application from Meta, for a smartphone-based platform to enhance medication-taking adherence of antiretroviral therapy among people living with HIV in Indonesia. Thirty participants were recruited for this 8-week study. We recruited persons if they had taken antiretroviral therapy for at least 3 months prior to the study, had a smartphone, Internet access, and could use Lantern with WhatsApp. Here, we report the results from the focus group discussions, with the participants evaluating the qualitative aspects of the experiences. The WhatsApp platform was found to be safe, practical, and relatively inexpensive and provided confidentiality for the participants. Three themes emerged from the focus groups: the study motivated participants to take their antiretroviral therapy medications on time, they still set medication reminder alarms, and being in the study made them feel supported. The Lantern program indicated good feasibility and acceptability for adherence to antiretroviral therapies among people living with HIV. Future research should examine on how community organizations and healthcare providers can take advantage of the WhatsApp program to improve adherence to antiretroviral therapies. No abstract available 
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