Cin-Computers Informatics Nursing最新文献

The rapid integration of mobile applications in healthcare has prompted an evolutionary change in nursing domain. This study aimed to systematically analyze the basic publication characteristics, research priorities, emerging trends, and thematic evolutions concerning mobile applications in nursing, providing an overview of the field's developmental trajectory and future directions. This was a descriptive bibliometric study. Data were collected on July 5, 2023, from the Web of Science database and analyzed by using the Bibliometrix package in R software. The search strategy yielded 417 documents authored by 1969 researchers, cited 12 595 references, and featured 1213 author keywords, spanning from 2012 to 2023. Research on mobile applications in nursing exhibited several key trends: (1) substantial collaboration among authors; (2) significant growth in the number of publications; (3) self-management was the most prominent hot topic; and (4) an evolution of research themes from general topics to a more specific focus on people-centered and problem-centered research. The corpus of literature pertaining to research on mobile applications within the nursing domain is anticipated to expand continually. Future research and practice in the nursing field are expected to benefit significantly from multidisciplinary collaboration and advancements in emerging technologies, including artificial intelligence.

Surgery is a significant part of healthcare, but its demand is increasing, leading to challenges in managing patient care. Inefficient perioperative practices and traditional linear models contribute to adverse outcomes and patient anxiety. E-health interventions show promise in improving surgical care, but more research is needed. The purpose of this study was to involve patients and healthcare workers during the design phase of an e-health intervention that aims to support the perioperative care of elective surgery preparation and recovery. This study used an Information Systems Research Framework to guide collaborative codesign through semistructured interviews and cocreation workshops. Semistructured interviews collected insights on the perioperative journey and e-health needs from healthcare workers and consumers, resulting in the creation of a patient surgery journey map, experience map, and a stakeholder needs table. Collaborative work between consumers and healthcare workers in the cocreation workshops identified priority perioperative journey issues and proposed solutions, as well as prioritizing application software needs, guiding the development of the wireframe. The development of an e-health application aimed at supporting surgery preparation and recovery is a significant step toward improving patient engagement, satisfaction, and postsurgical health outcomes.

Although electronic health record optimization programs are common in healthcare organizations, a dearth of published evaluations of these programs exists. Little is known about the ability of optimization programs to handle flooding requests for change and achieve their objectives of cost savings, value, quality of care, and efficiency. This program evaluation reviewed one organization's electronic health record clinical optimization program. The evaluation examines the implementation of the insulin dosing calculator project at five hospitals within a large nonprofit healthcare organization using interviews, project documents, reported insulin dosing errors, and workflow observation to determine if the program provides sufficient structure and processes to successfully implement large optimization projects and achieve the project's desired outcomes. This evaluation finds that the optimization program processes support the implementation of large projects. The program can improve the planning of human resources to increase productivity and reduce waste. A clearer definition of meaningful project outcomes at the onset would allow the program to measure and communicate its accomplishments across the organization.

Diabetic peripheral neuropathy is a major cause of disability and death in the later stages of diabetes. A retrospective chart review was performed using a hospital-based electronic medical record database to identify 1020 patients who met the criteria. The objective of this study was to explore and analyze the early risk factors for peripheral neuropathy in patients with type 2 diabetes, even in the absence of specific clinical symptoms or signs. Finally, the random forest algorithm was used to rank the influencing factors and construct a predictive model, and then the model performance was evaluated. Logistic regression analysis revealed that vitamin D plays a crucial protective role in preventing diabetic peripheral neuropathy. The top three risk factors with significant contributions to the model in the random forest algorithm eigenvalue ranking were glycosylated hemoglobin, disease duration, and vitamin D. The areas under the receiver operating characteristic curve of the model ware 0.90. The accuracy, precision, specificity, and sensitivity were 0.85, 0.83, 0.92, and 0.71, respectively. The predictive model, which is based on the random forest algorithm, is intended to support clinical decision-making by healthcare professionals and help them target timely interventions to key factors in early diabetic peripheral neuropathy.

The number of health technology-based intervention studies has grown significantly. However, issues in the recruitment and retention for such studies, especially of Asian Americans, have rarely been discussed. The purpose of this paper was to discuss issues in the recruitment and retention of a specific group of Asian Americans-Korean American midlife women with depressive symptoms-into a technology-based intervention study using computers and mobile devices with a measurement device and to provide directions for future participant recruitment and retention in technology-based intervention studies. The written memos of research team members and the written records of research team meetings were analyzed using a content analysis. The issues in the recruitment and retention process included (1) low recruitment and retention rates; (2) the perceived long intervention period; (3) strict inclusion/exclusion criteria; (4) concerns related to the use of a measurement device; and (5) the perceived adequacy of monetary incentives. Based on the issues identified in the study, several suggestions are made for future recruitment and retention of racial/ethnic minorities in technology-based intervention studies (eg, appropriate intervention period, innovative and creative motivation strategies, acceptable measurement scales and devices, and adequate monetary reimbursement).

To date, symptom documentation has mostly relied on clinical notes in electronic health records or patient-reported outcomes using disease-specific symptom inventories. To provide a common and precise language for symptom recording, assessment, and research, a comprehensive list of symptom codes is needed. The International Classification of Diseases, Ninth Revision or its clinical modification ( International Classification of Diseases, Ninth Revision, Clinical Modification ) has a range of codes designated for symptoms, but it does not contain codes for all possible symptoms, and not all codes in that range are symptom related. This study aimed to identify and categorize the first list of International Classification of Diseases, Ninth Revision, Clinical Modification symptom codes for a general population and demonstrate their use to characterize symptoms of patients with type 2 diabetes mellitus in the Cerner database. A list of potential symptom codes was automatically extracted from the Unified Medical Language System Metathesaurus. Two clinical experts in symptom science and diabetes manually reviewed this list to identify and categorize codes as symptoms. A total of 1888 International Classification of Diseases, Ninth Revision, Clinical Modification symptom codes were identified and categorized into 65 categories. The symptom characterization using the newly obtained symptom codes and categories was found to be more reasonable than that using the previous symptom codes and categories on the same Cerner diabetes cohort.

This study shows the development of a software for calculating the number of nursing team members required for providing care during the coronavirus disease 2019 pandemic. Study about the development of a technology based on the literature about data and indicators. The indicators were systematized in the following dimensions: institutional, professional, and occupational structure, all with a focus on coronavirus disease 2019. The software was created to be used on the Web, client-server, in browsers such as Internet Chrome, Explorer, and/or Mozilla Firefox, accessing via an Internet address and also allowing access by Windows, Android, and Linux operating systems, with MySQL database used for data storage. The data and indicators related to the institutional structure for coronavirus disease 2019 were systematized with 10 dimensions and indicators, and the professional and occupational structure, with 14 dimensions and indicators. The construction of computer requirements followed the precepts of software engineering, with theoretical support from the area. In the evaluation of the software, data simulation revealed points that had to be adjusted to ensure security, data confidentiality, and easy handling. The software provides to calculate the size and quality of the team, nursing sizing required due to the needs generated by the coronavirus disease 2019 pandemic.

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.