Introduction: There are many different types of nursing care delivery models used to organize and provide care in hospitals. These models are comprised of different organizational structures and staffing skill mixes.
Objective: The aim of this study was to explore how nursing care delivery models promote intraprofessional collaborative care in acute care hospitals from the perspectives of nurse leaders.
Methods: A qualitative descriptive approach was used for this study. Telephone interviews were conducted between January 2021 and August 2021 using an interview guide comprised of semi-structured and structured questions. Using a purposeful sampling technique, ten leaders from nine hospital systems, representing both urban and rural hospitals in the province of Ontario, Canada, participated in the study. Content analysis was conducted resulting in two overarching themes.
Results: The first theme, addresses the flexibility of the models and the impact of contextual factors such as changes in nurses' scope of practice, government funding changes, staffing mix, and organizational policies and rules. The second theme, describes the resources that hospitals implement to promote intraprofessional collaboration that indirectly impacts on patient safety.
Conclusion: Nursing care delivery models need to be flexible and adaptable. All nursing care delivery models in this study used various tools to promote intraprofessional collaborative care.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583196 | PMC |
http://dx.doi.org/10.1177/23779608221133648 | DOI Listing |
JMIR Form Res
January 2025
Institute of Nursing Science, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Background: Health care systems and the nursing profession worldwide are being transformed by technology and digitalization. Nurses acquire digital competence through their own experience in daily practice, but also from education and training; nursing education providers thus play an important role. While nursing education providers have some level of digital competence, there is a need for ongoing training and support for them to develop more advanced skills and effectively integrate technology into their teaching.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
University hospital Medical Information Network (UMIN) Center, The University of Tokyo Hospital, Tokyo, Japan.
Background: The Patient Education Materials Assessment Tool (PEMAT) is a reliable and validated instrument for assessing the understandability and actionability of patient education materials. It has been applied across diverse cultural and linguistic contexts, enabling cross-field and cross-national material quality comparisons. Accumulated evidence from studies using the PEMAT over the past decade underscores its potential impact on patient and public action.
View Article and Find Full Text PDFRev Bras Enferm
January 2025
Universidade da Integração Internacional da Lusofonia Afro-Brasileira. Redenção, Ceará, Brazil.
Rev Bras Enferm
January 2025
Universidade Federal de Santa Catarina, Colégio de Aplicação. Santa Catarina, Santa Catarina, Brazil.
Objective: To analyze the new roles of community health workers as outlined in the 2017 National Primary Care Policy (PNAB) from the perspectives of both nurses and community health workers.
Methods: This qualitative study involved nurses and community health workers from Family Health teams, conducted through semi-structured interviews via videoconference between August 2021 and April 2022. The data were analyzed using thematic content analysis.
Rev Bras Enferm
January 2025
Universidade Federal de Minas Gerais. Belo Horizonte, Minas Gerais, Brazil.
Objective: To analyze the reach and engagement on the history of nursing on social media of the Memory Center of the School of Nursing, Federal University of Minas Gerais (CEMENF/UFMG), in light of Pierre Lévy.
Methods: Documentary study carried out on CEMENF's Instagram and on the YouTube of the School of Nursing of UFMG, from September to December 2021. The findings were analyzed according to Pierre Lévy's concepts.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!