TY  - BOOK
AU  - Cheng, Tianyi
AU  - Fong, Allan
AU  - Franklin, Ella
AU  - Ratwani, Raj M
TI  - Identifying influential individuals on intensive care units: using cluster analysis to explore culture
SN  - 0966-0429
PY  - 2017///
KW  - *Health Personnel/px [Psychology]
KW  - *Intensive Care Units/ma [Manpower]
KW  - *Organizational Culture
KW  - *Peer Influence
KW  - *Social Support
KW  - Academic Medical Centers/og [Organization & Administration]
KW  - Cluster Analysis
KW  - Health Personnel/sn [Statistics & Numerical Data]
KW  - Health Personnel/st [Standards]
KW  - Humans
KW  - Intensive Care Units/og [Organization & Administration]
KW  - Intensive Care Units/sn [Statistics & Numerical Data]
KW  - Safety Management/sn [Statistics & Numerical Data]
KW  - Safety Management/st [Standards]
KW  - Surveys and Questionnaires
KW  - MedStar Institute for Innovation
KW  - Journal Article
N2  - AIM: The objective of this paper is to identify attribute patterns of influential individuals in intensive care units using unsupervised cluster analysis; BACKGROUND: Despite the acknowledgement that culture of an organisation is critical to improving patient safety, specific methods to shift culture have not been explicitly identified; CONCLUSIONS: Culture is created locally by individual influencers. Cluster analysis is an effective way to identify common characteristics among members of an intensive care unit team that are noted as highly influential by their peers. To change culture, identifying and then integrating the influencers in intervention development and dissemination may create more sustainable and effective culture change. Additional studies are ongoing to test the effectiveness of utilising these influencers to disseminate patient safety interventions; Copyright c 2017 John Wiley & Sons Ltd; IMPLICATIONS FOR NURSING MANAGEMENT: This study offers an approach that can be helpful in both identifying and understanding influential team members and may be an important aspect of developing methods to change organisational culture; METHODS: A social network analysis survey was conducted and an unsupervised cluster analysis was used; RESULTS: A total of 100 surveys were gathered. Unsupervised cluster analysis was used to group individuals with similar dimensions highlighting three general genres of influencers: well-rounded, knowledge and relational
UR  - https://dx.doi.org/10.1111/jonm.12476
ER  -