How to identify key players that contribute to resilient performance: A social network analysis perspective

Bertoni, Vanessa Becker; Saurin, Tarcísio Abreu; Fogliatto, Flávio Sanson

doi:10.1016/j.ssci.2021.105648

Cited by 17 publications

(17 citation statements)

References 43 publications

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“…Four included studies met the level-1 [ 13 , 25 – 27 ], 74 the level-2 [ 15 – 17 , 19 – 21 , 23 , 28 – 94 ], and 24 the level-3 [ 18 , 22 , 24 , 95 – 115 ] criteria.…”

Section: Resultsmentioning

confidence: 99%

Network approaches and interventions in healthcare settings: A systematic scoping review

2023

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Introduction The growing interest in networks of interactions is sustained by the conviction that they can be leveraged to improve the quality and efficiency of healthcare delivery systems. Evidence in support of this conviction, however, is mostly based on descriptive studies. Systematic evaluation of the outcomes of network interventions in healthcare settings is still wanting. Despite the proliferation of studies based on Social Network Analysis (SNA) tools and techniques, we still know little about how intervention programs aimed at altering existing patterns of social interaction among healthcare providers affect the quality of service delivery. We update and extend prior reviews by providing a comprehensive assessment of available evidence. Methods and findings We searched eight databases to identify papers using SNA in healthcare settings published between 1st January 2010 and 1st May 2022. We followed Chambers et al.’s (2012) approach, using a Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. We distinguished between studies relying on SNA as part of an intervention program, and studies using SNA for descriptive purposes only. We further distinguished studies recommending a possible SNA-based intervention. We restricted our focus on SNA performed on networks among healthcare professionals (e.g., doctors, nurses, etc.) in any healthcare setting (e.g., hospitals, primary care, etc.). Our final review included 102 papers. The majority of the papers used SNA for descriptive purposes only. Only four studies adopted SNA as an intervention tool, and measured outcome variables. Conclusions We found little evidence for SNA-based intervention programs in healthcare settings. We discuss the reasons and challenges, and identify the main component elements of a network intervention plan. Future research should seek to evaluate the long-term role of SNA in changing practices, policies and behaviors, and provide evidence of how these changes affect patients and the quality of service delivery.

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“…Four included studies met the level-1 [ 13 , 25 – 27 ], 74 the level-2 [ 15 – 17 , 19 – 21 , 23 , 28 – 94 ], and 24 the level-3 [ 18 , 22 , 24 , 95 – 115 ] criteria.…”

Section: Resultsmentioning

confidence: 99%

Network approaches and interventions in healthcare settings: A systematic scoping review

2023

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“…2.3 Application of social network analysis to project management SNA, which features integrated mathematical and computational applications, is a quantitative tool used to model organizational structure, analyze interactions among different individuals or groups and interpret the features and implications of relational fabrics (Yu et al, 2017). It focuses on a set of linkages connecting a definite set of individuals, where the roles and social behaviors of each individual are readily influenced by its connected neighbors in the network (Bertoni et al, 2022).…”

Section: Project Portfolio Synergymentioning

confidence: 99%

“…, 2017). It focuses on a set of linkages connecting a definite set of individuals, where the roles and social behaviors of each individual are readily influenced by its connected neighbors in the network (Bertoni et al. , 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of factors influencing project portfolio benefits with synergy considerations

Bai

Xue

Liu

et al. 2022

ECAM

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PurposeRealizing project portfolio benefits (PPBs) is considered a key challenge faced by enterprises. This challenge can largely be attributed to an unclear understanding of the factors influencing PPBs. However, synergistic relationships create complexity for the management of influencing factors. In response to this dilemma, the objective of this study is to quantitatively investigate the factors influencing PPBs while considering the synergistic effect among factors to provide guidelines for benefits management.Design/methodology/approachThrough an integration of the synergy degree of the composite system model and social network analysis (SNA), a refined model is proposed to explore the factors influencing PPBs. First, a list that includes financial and nonfinancial influencing factors is clarified. Then, the corresponding network links, which represent the synergistic relationships among the factors, are innovatively assessed based on the synergy degree of the composite system. Finally, the influencing factor network is analyzed using both individual and overall indicators of SNA.FindingsThe resulting evidence demonstrates that four critical influencing factors exist, namely, “project managers,” “purchasers,” “development capacity” and “tangible resources.” These factors are relatively important and should be prioritized. Furthermore, the factors are divided into three subgroups: participant, resource and governmental factors. A general observation from the results is that factors that share the same subgroup are more likely to have a synergistic effect advantage, which leads to an increase in PPBs.Originality/valueThe value of this paper lies in its proposition of a quantitative model that can be used to measure and analyze the factors influencing PPBs with synergy considerations. This research contributes to the body of knowledge on benefits management by linking synergy with PPBs. It presents new insights for managers on how PPBs may be effectively managed and promoted from the perspective of influencing factors.

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“…In order to assess the contribution of healthcare professionals to the resilient performance of the system, Bertoni et al (2022) created the resilience score, which encompasses three social network metrics and two non-network attributes. These three metrics are rooted in social network analysis (i.e., in-degree, betweenness, and closeness) and are explained in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Correlations Between Burnout and Centrality in Social Networks: A Study of an Emergency Department

Terra¹,

Reckziegel²,

Saurin³

2023

Anais Do XII Congresso Internacional De Conhecimento E Inovação (ciKi)

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Healthcare environments are known to be intense in knowledge and constant stress. Exchanging information through social interactions in the work environment was addressed in this study of an emergency department in order to answer the following research question: “Regarding knowledge management, what are the relationships between resilient performance and burnout?”. To do so, we used the resilience social network questionnaire and the Maslach Burnout Inventory. Results showed that resilience is positively correlated to burnout. Nurses are the most resilient actors. In addition, professional experience and participating in huddles relate to a greater contribution to the organisation's resilience performance. Therefore, the constant use of resilient capacity takes a toll on health care professionals. Knowledge sharing also promotes informal leadership, providing more skilled professionals and highly qualified human capital.

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How to identify key players that contribute to resilient performance: A social network analysis perspective

Cited by 17 publications

References 43 publications

Network approaches and interventions in healthcare settings: A systematic scoping review

Network approaches and interventions in healthcare settings: A systematic scoping review

Analysis of factors influencing project portfolio benefits with synergy considerations

Analysis of Correlations Between Burnout and Centrality in Social Networks: A Study of an Emergency Department

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