{"title":"Harnessing Predictive Analytics for Nursing: A PyHealth-Driven Approach to Hospital Readmission Prediction Using EHR Data.","authors":"Jose Huerta","doi":"10.1097/CIN.0000000000001472","DOIUrl":"10.1097/CIN.0000000000001472","url":null,"abstract":"<p><p>Health care systems face considerable challenges of hospital readmission, which bear adverse implications for patient outcomes and compromise productivity and efficient use of system resources. In this study, PyHealth, an open-source health care machine-learning tool, and the RETAIN model, a reverse-time attention neural network, were used to predict hospital readmissions within 30 days after discharge. The analysis was performed on the publicly available MIMIC-III demo data set that was additionally deidentified for patient privacy. The predictability of hospital readmissions within 30 days after discharge was evaluated using nursing-centric clinical components such as diagnosis, procedures, and prescriptions. The results revealed a strong potential of open-source tools such as PyHealth in enhancing nursing support for workflows such as discharge planning, education, and postdelivery interventions. Accordingly, integrations like PyHealth can assist in improving patient care before discharge so as to minimize the number of hospital readmissions.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145914613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Developing AI-generated Storybooks for Patient Education: A Practical Framework for Nursing Educators and Clinicians.","authors":"Yasemin Boy, Funda Çam","doi":"10.1097/CIN.0000000000001476","DOIUrl":"10.1097/CIN.0000000000001476","url":null,"abstract":"<p><p>Recent advances in Large Language Models and Text-to-Image technologies present new opportunities for developing innovative and personalized patient education tools. This study aimed to establish a practical framework for creating multimodal digital storybooks that combine narrative text, visuals, and audio narration to support patients with chronic diseases. A qualitative content development design was applied, using an iterative process guided by expert feedback to ensure clinical accuracy and cultural relevance. ChatGPT-5 (OpenAI) was utilized for prompt engineering, while Gemini 2.5 Pro (Google LLC) generated storybooks integrating text, visuals, and narration for 3 chronic conditions: heart failure, diabetes mellitus, and chronic obstructive pulmonary disease. Each storybook underwent multiple cycles of refinement to address clinical detail, readability, and visual accuracy. Findings indicated that while AI systems can generate patient education materials, general prompts were insufficient, and technical limitations, such as medically inaccurate visuals, required expert correction. Despite these challenges, the framework demonstrated that high-quality, accessible, and engaging storybooks can be produced when AI is used in collaboration with subject matter experts. This approach highlights AI's role as a supportive tool for health care professionals, enhancing their ability to deliver effective, patient-centered education that promotes understanding, engagement, and improved self-management in chronic disease care.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146055819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christina Grape Viding, Marie-Therese Crafoord, Ann Langius-Eklöf, Kay Sundberg
{"title":"Nurses' Perspectives of a Digital Supportive Intervention When Caring for Patients During Radiotherapy for Prostate Cancer: A Qualitative Study.","authors":"Christina Grape Viding, Marie-Therese Crafoord, Ann Langius-Eklöf, Kay Sundberg","doi":"10.1097/CIN.0000000000001495","DOIUrl":"10.1097/CIN.0000000000001495","url":null,"abstract":"<p><p>Nurses' duties have come to include new technological solutions when supporting patients in cancer care. Patient-reported outcomes through digital self-monitoring in routine clinical care are highly recommended when supporting patients in cancer care. Learning about nurses' perceptions when providing digital support would enhance understanding of this new way of working and is necessary for future development and implementation. We performed a focus group interview with nurses who had been working with an interactive app (Interaktor) for digital support in daily practice when caring for patients undergoing radiotherapy for prostate cancer. The interview revealed that the nurses had retrieved useful information through the app about patients' symptoms and concerns that had promoted contact with the patients. Furthermore, they acknowledged that the app supported patients in communicating emotions such as worry. Monitoring and managing patients' symptoms were not seen as difficult or overly burdensome, although the organization at the clinic had difficulty putting it into practice. Overall, the nurses had a positive attitude and gained more knowledge about the patients than in standard care. This study contributes to the growing research on digital technology in health care delivery and its potential for supporting patients in cancer care.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146152220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Madison Horton, Michelle Lardner, Meghan Reading Turchioe
{"title":"Centering Nursing in AI-enabled Care: Alliance for Nursing Informatics Offers Perspectives on the Adoption and Use of Artificial Intelligence as Part of Clinical Care.","authors":"Madison Horton, Michelle Lardner, Meghan Reading Turchioe","doi":"10.1097/CIN.0000000000001557","DOIUrl":"10.1097/CIN.0000000000001557","url":null,"abstract":"","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147937198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Pilot Report on Extracting Symptom Onset Date and Time From Clinical Notes in Patients Presenting With Chest Pain.","authors":"Anjaly George, Aashrith Maisa, Caitlin Dreisbach, Sukardi Suba","doi":"10.1097/CIN.0000000000001406","DOIUrl":"10.1097/CIN.0000000000001406","url":null,"abstract":"<p><p>The timing of clinical events is important information in understanding disease progression and its critical context and relationship to treatment and patient outcomes. However, time information documentation in the electronic health record (EHR) is inconsistent, hindering its utility in research and clinical care. In research where event timing is crucial, such as symptom onset in acute coronary syndrome, automated tools can expedite data collection, reducing the reliance on labor-intensive manual reviews. We aimed to apply natural language processing (NLP) methods for extracting date and time (DateTime) information from free-text EHR clinical notes. Two off-the-shelf NLP pipelines, parsedatetime and regular expression ( regex ), were pilot tested on 71 annotated clinical notes: History and Physical (n=49), Emergency Department Screening (n=3), and Triage Notes (n=19). Parsedatetime identified correct DateTime information in 36 notes (50.7%) with an F1-score of 0.31 (low performance), while regex failed to produce any accurate outputs. Despite parsedatetime outperforming regex , its performance remains inadequate. Both approaches required significant refinement and customization to improve efficacy. To optimize automated DateTime extraction, future research should focus on advanced rule-based NLP methods capable of handling complex narratives. Consistent time documentation by clinicians, adhering to standardized formats, remains essential for improving the downstream usability of EHR data.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Immersive Virtual Simulation for Undergraduate Nursing Education on Migrant Mental Health: A Mixed-Methods Study.","authors":"Geneveave Barbo, Donald Leidl, Hua Li, Marjorie Montreuil, Solina Richter, Pammla Petrucka","doi":"10.1097/CIN.0000000000001431","DOIUrl":"10.1097/CIN.0000000000001431","url":null,"abstract":"<p><p>Nursing graduates reported feeling unprepared to address migrants' mental health needs. Immersive virtual reality offers an innovative approach to enhance therapeutic communication, cultural competence, and humility. This study examined the acceptability of a virtual reality simulation focused on migrants with mental health challenges and its impact on students' attitudes and cultural competence. A multi-phase sequential mixed methods design was used: phase 1 involved intervention development through an integrative review and a participatory approach; phase 2 employed a one-group pre-quasi-experimental and post-quasi-experimental design; phase 3 employed an interpretive description. Students found the simulation highly acceptable, reporting significant improvements in cultural competence and modest reductions in stigma. Qualitative findings revealed 4 themes: interacting with virtual reality technology; bridging educational gaps; shifting perspectives and practice; and navigating care through lived experiences. Virtual reality shows promise for strengthening mental health nursing education and practice by addressing gaps in clinical placements and traditional teaching. Future research should expand content, improve usability and realism, assess long-term impacts, and support faculty training.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145866824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effectiveness of a Virtual Communication Laboratory in Enhancing Therapeutic Communication Skills in Nursing Students.","authors":"Nazmiye Yildirim, Ayşe Gürbüz","doi":"10.1097/CIN.0000000000001413","DOIUrl":"10.1097/CIN.0000000000001413","url":null,"abstract":"<p><p>This study aimed to evaluate the effectiveness of a web-based Virtual Communication Laboratory, which was developed to include informative content, interactive exercises, and animated practice videos, on nursing students' therapeutic and nontherapeutic communication skills. This quasi-experimental study was conducted with 39 fourth-year nursing students from a public university in Türkiye who were enrolled in a 14-week clinical mental health nursing internship. Students used the Virtual Communication Laboratory in the eighth week. The Therapeutic Communication Skills Scale for Nursing Students was administered in the 7th (pretest) and 14th (posttest) weeks. The scale assessed students' self-reported frequency of using specific communication techniques during clinical practice. Mean scores improved from 18.66 to 14.02 for Nontherapeutic Communication Skills, from 28.17 to 34.02 for Therapeutic Communication Skills I, and from 17.92 to 19.46 for Therapeutic Communication Skills II (all P <.001). Students rated the platform highly for ease of use and usefulness, and reported that it facilitated reflection and aligned with clinical scenarios. The Virtual Communication Laboratory offers a user-friendly and engaging learning experience that supports the development of therapeutic communication skills. Given the growing importance of blended learning environments, these findings suggest its potential as a valuable complementary tool in nursing education.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patricia A Ball Dunlap, Eun-Shim Nahm, Elizabeth E Umberfield
{"title":"Response to Letter to the Editor.","authors":"Patricia A Ball Dunlap, Eun-Shim Nahm, Elizabeth E Umberfield","doi":"10.1097/CIN.0000000000001432","DOIUrl":"10.1097/CIN.0000000000001432","url":null,"abstract":"","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147583547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrating Spatial Awareness into Nursing EHR Design: A Scoping Review of Usability and Cognitive Load.","authors":"","doi":"10.1097/CIN.0000000000001598","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001598","url":null,"abstract":"","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":"44 7","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148379431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clinical Nurses' Point-of-Care Technology Use and Digital Health Competency: Scoping Review.","authors":"Jiwon Park, Eun-Shim Nahm","doi":"10.1097/CIN.0000000000001465","DOIUrl":"10.1097/CIN.0000000000001465","url":null,"abstract":"<p><p>The integration of digital health technologies (DHTs) in health care has been shown to improve patient care and management of chronic conditions while reducing care costs. Nurses, as the largest health care workforce, frequently use DHTs at the bedside, necessitating ongoing adaptation to point-of-care (POC) technologies. However, research on nurses' competencies in using these tools and the impact of competency levels remains limited. This scoping review explores factors influencing nurses' competency in DHT use, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Using Arksey and O'Malley's methodological approach, academic databases were searched for peer-reviewed studies from 2014 to 2024 focusing on registered nurses, DHTs, POC technologies, and digital health competency. Studies on undergraduate nursing students and those published before 2014 were excluded. Of 1513 articles identified, 20 were reviewed. The findings revealed that demographic, psychological, practical skill, and organizational factors shape digital health competency. Younger and educated nurses adapted quickly to digital tools, while experienced nurses leveraged clinical knowledge to their use. Organizational support and targeted training were critical for sustained digital tool use. Strengthening nurses' DHT competencies at the POC is essential for modern health care. Future research should focus on interventions that enhance these competencies to ensure better patient outcomes.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}