Computers, informatics, nursing : CIN最新文献_第2页

Inflection Point: Artificial Intelligence, Digital Health, and the Evolution of Pre-Licensure Nursing Informatics Competencies. 拐点：人工智能，数字健康，和执照前护理信息学能力的演变。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-05-01 DOI: 10.1097/CIN.0000000000001506

Mollie R Cummins, Seneca Perri Moore, Katherine A Sward

{"title":"Inflection Point: Artificial Intelligence, Digital Health, and the Evolution of Pre-Licensure Nursing Informatics Competencies.","authors":"Mollie R Cummins, Seneca Perri Moore, Katherine A Sward","doi":"10.1097/CIN.0000000000001506","DOIUrl":"10.1097/CIN.0000000000001506","url":null,"abstract":"Recent advancements in artificial intelligence, telehealth, and sensor technologies have fundamentally transformed health care, creating an urgent need to update and revise nursing informatics competencies for pre-licensure education. The purpose of this narrative, non-systematic review is to (1) describe and characterize the evolution of pre-licensure nursing informatics competencies; (2) discuss the central phenomena driving current digital transformation in health care; and (3) discuss future directions to evolve pre-licensure nursing informatics competency frameworks in an era of digital health. We conducted multiple literature searches in support of the narrative review. Current pre-licensure nursing informatics competency frameworks require evolution, given the new knowledge and skills needed for nurses to engage with rapidly advancing digital health technologies. The review reveals the need for a fifth wave of competency development that prepares nurses as informed users, contributors, evaluators, and stewards of digital health tools. We must advance nursing informatics education to meet the workforce needs of the digital health era by building on a robust foundation of past competency development efforts.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13143369/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147477118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Educating the Digital Nurse: A Scoping Review of Nursing Informatics in Pre-licensure Programs. 教育数字护士：护理信息学在预许可计划的范围审查。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-05-01 DOI: 10.1097/CIN.0000000000001505

Marshall K Muehlbauer, Nancy Husson, Kathleen Morouse, Elizabeth V Weinfurter, Tracia Forman

{"title":"Educating the Digital Nurse: A Scoping Review of Nursing Informatics in Pre-licensure Programs.","authors":"Marshall K Muehlbauer, Nancy Husson, Kathleen Morouse, Elizabeth V Weinfurter, Tracia Forman","doi":"10.1097/CIN.0000000000001505","DOIUrl":"10.1097/CIN.0000000000001505","url":null,"abstract":"Background: This scoping review examined how nursing informatics has been integrated into pre-licensure nursing education programs and how informatics competency has been assessed from 2017 to 2024.Methods: Searches were conducted in MEDLINE and CINAHL in May 2024 for English language, peer-reviewed studies involving pre-licensure nursing students. Eligibility criteria included original research focused on informatics instruction or assessment. Two reviewers independently screened records; disagreements were resolved by a third reviewer. Methodological quality was assessed using the Joanna Briggs Institute tools. Data were extracted into a structured matrix and synthesized thematically.Results: Twenty-three studies met inclusion criteria, featuring diverse designs and instructional strategies such as simulation-based learning (n=10), academic EHR integration (n=4), and peer-led instruction (n=3). Most studies used researcher-developed assessment tools (n=14), whereas standardized instruments were infrequently applied. Few studies explicitly aligned informatics instruction with clinical judgment frameworks.Conclusions: Findings indicate increasing, although inconsistent, integration of nursing informatics. Assessment practices lack standardization, and theoretical grounding is limited.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147629616","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}

引用次数: 0

Emerging Technologies and Informatics in Nursing Education. 护理教育中的新兴技术和信息学。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-05-01 DOI: 10.1097/CIN.0000000000001543

Ronald J Piscotty

引用次数: 0

Inflection Point: AI, Digital Health, and the Evolution of Pre-licensure Nursing Informatics Competencies. 拐点：人工智能，数字健康和执照前护理信息学能力的演变。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-05-01 DOI: 10.1097/CIN.0000000000001520

引用次数: 0

Artificial Intelligence in Nursing: American Association of Colleges of Nursing Addresses Opportunities, Risks, and the Ethical Compass. 护理中的人工智能：美国护理学院协会解决机会，风险和道德指南针。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-05-01 DOI: 10.1097/CIN.0000000000001553

Connie White Delaney, Jane Carrington, Karen Dunn Lopez

引用次数: 0

Predicting Somatization Risk Among Infectious Disease Disaster Frontline Nurses Using Machine Learning. 利用机器学习预测传染病灾害一线护士的躯体化风险。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-21 DOI: 10.1097/CIN.0000000000001542

Sung-Hee Shin, Eun Kyoung Yun

{"title":"Predicting Somatization Risk Among Infectious Disease Disaster Frontline Nurses Using Machine Learning.","authors":"Sung-Hee Shin, Eun Kyoung Yun","doi":"10.1097/CIN.0000000000001542","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001542","url":null,"abstract":"This study aimed to identify key risk factors associated with high-somatization risk among frontline nurses responding to infectious diseases, utilizing a robust machine learning approach. Data were collected from 222 nurses in South Korea, including sociodemographic factors, work-related conditions, job stress, and somatic symptoms. Of the participants, 13.1% had high levels of somatization. Machine learning models, including Logistic regression, XGBoost, and the Random Forest algorithm, were developed to predict high-somatization risk. The models were evaluated based on their mean performance across ten CV folds. While XGBoost demonstrated the highest mean AUC (0.734), the Logistic Regression model was prioritized for interpretation due to its superior performance in identifying the high-risk group. Cross-model feature importance analysis revealed that Infection Anxiety and Delayed Staffing Assignment were the 2 most consistent and influential predictors across both models, followed by factors like satisfaction with salary/bonus and daily PPE hours. These findings suggest that integrating machine learning into occupational health assessments can facilitate the early identification of frontline nurses at high risk of somatization, enabling targeted workplace interventions. This study highlights the potential for proactive support strategies to enhance nurse well-being and maintain health care system resilience during future infectious disease responses.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147794954","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}

引用次数: 0

e-Health in Occupational Accident Management: Insights From Nursing Practice Using the Digitalized Omaha System. 职业事故管理中的电子健康：使用数字化奥马哈系统的护理实践的见解。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-17 DOI: 10.1097/CIN.0000000000001534

Nur Sena Kayacan, Emine Aktas

{"title":"e-Health in Occupational Accident Management: Insights From Nursing Practice Using the Digitalized Omaha System.","authors":"Nur Sena Kayacan, Emine Aktas","doi":"10.1097/CIN.0000000000001534","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001534","url":null,"abstract":"Occupational accidents remain a critical public health concern globally and are especially prevalent in Türkiye. Integrating standardized nursing classification systems into electronic health records presents an opportunity to improve data quality, care coordination, and evidence-based decision-making. This study aimed to evaluate the clinical and informatics utility of the Omaha System, integrated into a digital electronic health records platform, for assessing and monitoring the health problems of workers hospitalized due to occupational accidents. A descriptive-longitudinal study was conducted with 45 workers admitted to an orthopedics and traumatology service in Türkiye following occupational accidents. Data were collected using a Personal Information Form and the Nightingale Notes platform, a digital electronic health records system structured around the Omaha System. The Problem Classification Scheme, Intervention Scheme, and Problem Rating Scale for Outcomes were used to identify problems, guide nursing interventions, and evaluate outcomes. The mean age of workers was 39.82±11.40 years. Hand and finger injuries were most common, affecting 75.6% of workers. Across the Problem Classification Scheme, 1274 problem entries were documented, including Neighborhood/Workplace Safety, Skin, Personal Care, Neuro-Musculoskeletal Function, Pain, and Role Change. A total of 2167 interventions were implemented, predominantly in the Teaching, Guidance, and Counseling category. Postintervention of the Problem Rating Scale for Outcomes evaluations showed statistically significant improvements in knowledge, behavior, and status (P<.05). The Omaha System-based electronic health records demonstrated clinical effectiveness in occupational health nursing by enabling systematic assessment, targeted interventions, and structured outcome monitoring. These findings support its broader applicability in occupational health surveillance, acute care services, and the development of data-driven, precision nursing practice.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147795029","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}

引用次数: 0

Integration of Nursing Data in Clinical Coding: Impact on Hospital Management and Optimization. 临床编码中护理数据的整合：对医院管理和优化的影响。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-16 DOI: 10.1097/CIN.0000000000001533

Tamara Moya-Ruiz, Marta Lima-Serrano, María Dolores Guerra-Martín, María Dolores Mateos-García

引用次数: 0

A Framework for Creating Effective Prompts Using Prompt Engineering. 使用提示工程创建有效提示的框架。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-13 DOI: 10.1097/CIN.0000000000001532

Jeeyae Choi, Darlene Hicks, Shamatree Shakya, Seoyoon Woo, Yea-Jyh Chen, Yeounsoo Kim

引用次数: 0

Testing Machine Learning-Based Pain Assessment for Postoperative Geriatric Patients: Erratum. 基于机器学习的老年患者术后疼痛评估测试：勘误。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-10 DOI: 10.1097/CIN.0000000000001546

引用次数: 0