Your browser doesn't support javascript.
loading
A few panel members dominated guideline development meeting discussions: Social network analysis.
Li, Shelly-Anne; Yousefi-Nooraie, Reza; Guyatt, Gordon; Talwar, Gaurav; Wang, Qi; Zhu, Ying; Hozo, Iztok; Djulbegovic, Benjamin.
Afiliação
  • Li SA; Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada. Electronic address: shellyanne.li@mail.utoronto.ca.
  • Yousefi-Nooraie R; Department of Public Health Sciences, University of Rochester, New York, USA.
  • Guyatt G; Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Ontario, Canada.
  • Talwar G; Michael G DeGroote School of Medicine, McMaster University, Ontario, Canada.
  • Wang Q; Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Ontario, Canada.
  • Zhu Y; Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Ontario, Canada.
  • Hozo I; Department of Mathematics, Indiana University, IN, USA.
  • Djulbegovic B; Department of Computational & Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA.
J Clin Epidemiol ; 141: 1-10, 2022 01.
Article em En | MEDLINE | ID: mdl-34555427
OBJECTIVES: To identify patterns of interactions that may influence guideline panels' decision-making. STUDY DESIGN AND SETTING: Social network analysis (SNA) to describe the conversation network in a guideline development meeting in United States. RESULTS: We analyzed one two-day guideline panel meeting that included 20 members who developed a guideline using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. The conversation pattern of the guideline panel indicated a well-connected network (density=0.59, clustering coefficient=0.82). GRADE topics on quality of evidence and benefits versus harms accounted for 46%; non-GRADE factors accounted for 30% of discussion. The chair, co-chair and methodologist initiated 53% and received 60% of all communications in the meeting; 42% of their communications occurred among themselves. SNA metrics (eigenvector, betweenness and closeness) indicated that these individuals also exerted highest influence on discussion, controlled information flow and were at the center of all communications. Members were more likely to continue previous discussion with the same individuals after both morning breaks (r=0.54, P<0.005; r=0.17, P=0.04), and after the last break on day 2 (r=0.44, P=0.015). CONCLUSION: Non-GRADE factors such as breaks, and the members' roles, affect guideline development more than previously recognized. Collectively, the chair, co-chair and methodologist dominated the discussion.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Temas: Fomentar_producao_conhecimento_especifico Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Medicina Baseada em Evidências / Análise de Rede Social Tipo de estudo: Guideline / Prognostic_studies / Qualitative_research Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: J Clin Epidemiol Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Temas: Fomentar_producao_conhecimento_especifico Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Medicina Baseada em Evidências / Análise de Rede Social Tipo de estudo: Guideline / Prognostic_studies / Qualitative_research Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: J Clin Epidemiol Ano de publicação: 2022 Tipo de documento: Article