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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. No abstract available Vulnerable populations face challenges gaining access to quality healthcare, which places them at a high risk for poor health outcomes. Using patient portals and secure messaging can improve patient activation, access to care, patient follow-up adherence, and health outcomes. Developing and testing quality improvement strategies to help reduce disparities is vital to ensure patient portals benefit all, especially vulnerable populations. This quality improvement initiative aimed to increase enrollment in a patient portal, use secure messages, and adhere to follow-up appointments. Before the project, no patients were enrolled in the portal at this practice site. Over 8 weeks, 61% of invited patients were enrolled in the patient portal. Eighty-five percent were Medicaid recipients, and the others were underinsured. Eight patients utilized the portal for secure messaging. The follow-up appointment attendance rate was better in the enrolled patients than in those who did not enroll. The majority of survey respondents reported satisfaction in using the patient portal. Patient portal utilization and adoption in vulnerable groups can improve when a one-on-one, hands-on demonstration and technical assistance are provided. Mobile healthcare has emerged as a prominent technological solution for self-management of health. However, the development and utilization of tailored mobile healthcare applications for older adults with diabetes mellitus remain limited. This study examined the relationship between social support and mobile healthcare use and further explored how this relationship varies with eHealth literacy and application design among older adults with diabetes mellitus. A descriptive cross-sectional trial was conducted with a structured self-report questionnaire, surveying 252 South Korean older adults with diabetes mellitus via offline and online modes. The mediating effect and moderated mediating effect were analyzed with the PROCESS macro of SPSS. eHealth literacy mediated the relationship between social support and mobile healthcare use. High levels of eHealth literacy and social support may increase mobile healthcare use among older adults with diabetes. Application design aesthetics facilitated mobile healthcare use. Future researchers, healthcare providers, and developers can contribute to the development of tailored mobile healthcare applications for older adults with diabetes mellitus by considering application design aspects such as font size, color, and menu configuration. This study aims to develop a virtual reality–based education program for managing behavioral and psychological symptoms of dementia for family carers of persons living with dementia and investigate the feasibility for users. The program was developed through literature review, interviews with family carers, surveys, and expert content validity assessment. User feasibility was evaluated quantitatively through a questionnaire on usefulness, ease of use, and satisfaction, and qualitatively through participant interviews. The program was produced in two parts, Type 1 and Type 2, consisting of three and six episodes, respectively. Participants showed a high level of satisfaction with overall program scores of 4.28 ± 0.66 and 4.34 ± 0.41 for the two evaluations. Participants also expressed that both programs were helpful, Type 1 for achieving changes in attitude associated with more understanding of persons living with dementia and Type 2 for acquiring coping methods through communication training. Use of the virtual reality device was not inconvenient and was identified as helpful due to the high immersion experience. Results of this study confirmed that family carers had no resistance to education using new technologies such as virtual reality devices and that virtual reality–based education could be effective for training family carers. The aim of this study was to describe medication administration and alert patterns among a cohort of new graduate nurses over the first year of practice. Medical errors related to clinical decision-making, including medication administration errors, may occur more frequently among new graduate nurses. To better understand nursing workflow and documentation workload in today's clinical environment, it is important to understand patterns of medication administration and alert generation during barcode-assisted medication administration. Study objectives were addressed through a descriptive, longitudinal, observational cohort design using secondary data analysis. Set in a large, urban medical center in the United States, the study sample included 132 new graduate nurses who worked on adult, inpatient units and administered medication using barcode-assisted medication administration. Data were collected through electronic health record and administration sources. New graduate nurses in the sample experienced a total of 587 879 alert and medication administration encounters, administering 772 unique medications to 17 388 unique patients. Nurses experienced an average medication workload of 28.09 medications per shift, 3.98% of which were associated with alerts, over their first year of practice. In addition to high volume of medication administration, new graduate nurses administer many different types of medications and are exposed to numerous alerts while using barcode-assisted medication administration. No abstract available Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and prioritizing injuries and illnesses on the frontlines of the emergency room. This study aims to create an Emergency Medical Rapid Triage and Prediction Assistance model using electronic medical records and machine learning techniques. Patient information was retrieved from the emergency department of a large regional teaching hospital in Taiwan, and five supervised learning techniques were used to construct classification models for predicting critical outcomes. Of these models, the model using logistic regression had superior prediction performance, with an F1 score of 0.861 and an area under the receiver operating characteristic curve of 0.855. The Emergency Medical Rapid Triage and Prediction Assistance model demonstrated superior performance in predicting intensive care and hospitalization outcomes compared with the Taiwan Triage and Acuity Scale and three clinical early warning tools. The proposed model has the potential to assist emergency nurses in executing challenging triage assessments and emergency teams in treating critically ill patients promptly, leading to improved clinical care and efficient utilization of medical resources. 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 This retrospective bibliometric analysis was conducted to explore research trends and identify studies in fields of nursing, virtual reality, and cancer. Data were obtained from the Web of Science database using an advanced search strategy. The study data were analyzed using the R Studio software and visualized using VOSviewer. A total of 594 studies were retrieved and analyzed from January 1995 to December 2021. It was determined that 59.4% of the studies were research articles and that these studies had been conducted by 2771 authors. The reviewed studies were produced by researchers from 25 countries and were published in 29 different journals. Of these, 169 were conducted by researchers in the United States. “Virtual reality” and “nursing” were found to be prominent topics. Studies on virtual reality in patients with cancer in the field of nursing have increased over the past 8 years. Researchers have actively conducted studies in this field. Prominent studies have covered various patients with cancer in all age groups and palliative care processes. It was seen that the majority of the studies were randomized controlled trials, reviews, and systematic reviews. In addition, studies have used virtual reality as a distraction method in the management of symptoms in patients with breast, lung, and pediatric cancers undergoing chemotherapy treatment. This study provides a detailed and up-to-date analysis of the findings obtained from the Web of Science database by emphasizing bibliometric models of virtual reality technologies in nursing patients with cancer. We believe that the current data on the use of virtual reality applications in patients with cancer will guide the clinical practice and scientific studies of healthcare professionals. The International Classification for Nursing Practice is a comprehensive terminology representing the domain of nursing practice. A categorization of the diagnoses/outcomes and interventions may further increase the usefulness of the terminology in clinical practice. The aim of this study was to categorize the precoordinated concepts of the International Classification for Nursing Practice into subsets for nursing diagnoses/outcomes and interventions using the structure of an established documentation model. The aim was also to investigate the distribution of the precoordinated concepts of the International Classification for Nursing Practice across the different areas of nursing practice. The method was a descriptive content analysis using a deductive approach. The VIPS model was used as a theoretical framework for categorization. The results showed that all the precoordinated concepts of the International Classification for Nursing Practice could be categorized according to the keywords in the VIPS model. It also revealed the parts of nursing practice covered by the concepts of the International Classification for Nursing Practice as well as the parts that needed to be added to the International Classification for Nursing Practice. This has not been identified in earlier subsets as they covered only one specific area of nursing. 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. No abstract available This study aimed to develop a Mobile Application to Prevent Recurrent Stroke to prevent recurrent stroke by enhancing self-management and to evaluate its effects on stroke survivors' health outcomes. The Mobile Application to Prevent Recurrent Stroke was developed based on social cognitive theory and the model in order of analysis, design, development, implementation, and evaluation process. The Mobile Application to Prevent Recurrent Stroke consisted of health management contents such as information about stroke, its associated risk factors, and required skills to conduct self-management with tailored support and counseling. A quasi-experimental preintervention and postintervention design was used involving a total of 54 stroke survivors. The experimental group (n = 27) was provided the Mobile Application to Prevent Recurrent Stroke for 8 weeks, whereas the control group (n = 27) received an education booklet. The result revealed that medication adherence (P = .002), healthy eating habit (P 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. To examine whether psychosocial needs in diabetes care are associated with carbohydrate counting and if carbohydrate counting is associated with satisfaction with diabetes applications' usability, a randomized crossover trial of 92 adults with type 1 or 2 diabetes requiring insulin therapy tested two top-rated diabetes applications, mySugr and OnTrack Diabetes. Survey responses on demographics, psychosocial needs (perceived competence, autonomy, and connectivity), carbohydrate-counting frequency, and application satisfaction were modeled using mixed-effect linear regressions to test associations. Participants ranged between 19 and 74 years old (mean, 54 years) and predominantly had type 2 diabetes (70%). Among the three tested domains of psychosocial needs, only competence—not autonomy or connectivity—was found to be associated with carbohydrate-counting frequency. No association between carbohydrate-counting behavior and application satisfaction was found. In conclusion, perceived competence in diabetes care is an important factor in carbohydrate counting; clinicians may improve adherence to carbohydrate counting with strategies designed to improve perceived competence. Carbohydrate-counting behavior is complex; its impact on patient satisfaction of diabetes application usability is multifactorial and warrants consideration of patient demographics such as sex as well as application features for automated carbohydrate counting. No abstract available 
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