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Social network analysis of nationwide interhospital emergency department transfers in Taiwan.
Tsai, Chu-Lin; Cheng, Ming-Tai; Hsu, Shu-Hsien; Lu, Tsung-Chien; Huang, Chien-Hua; Liu, Yueh-Ping; Shih, Chung-Liang; Fang, Cheng-Chung.
Afiliação
  • Tsai CL; Department of Emergency Medicine, National Taiwan University Hospital, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.
  • Cheng MT; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Hsu SH; Department of Emergency Medicine, National Taiwan University Hospital, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.
  • Lu TC; Department of Emergency Medicine, National Taiwan University Hospital, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.
  • Huang CH; Department of Emergency Medicine, National Taiwan University Hospital, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.
  • Liu YP; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Shih CL; Department of Emergency Medicine, National Taiwan University Hospital, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.
  • Fang CC; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
Sci Rep ; 13(1): 2311, 2023 02 09.
Article em En | MEDLINE | ID: mdl-36759680
Transferring patients between emergency departments (EDs) is a complex but important issue in emergency care regionalization. Social network analysis (SNA) is well-suited to characterize the ED transfer pattern. We aimed to unravel the underlying transfer network structure and to identify key network metrics for monitoring network functions. This was a retrospective cohort study using the National Electronic Referral System (NERS) database in Taiwan. All interhospital ED transfers from 2014 to 2016 were included and transfer characteristics were retrieved. Descriptive statistics and social network analysis were used to analyze the data. There were a total of 218,760 ED transfers during the 3-year study period. In the network analysis, there were a total of 199 EDs with 9516 transfer ties between EDs. The network demonstrated a multiple hub-and-spoke, regionalized pattern, with low global density (0.24), moderate centralization (0.57), and moderately high clustering of EDs (0.63). At the ED level, most transfers were one-way, with low reciprocity (0.21). Sending hospitals had a median of 5 transfer-out partners [interquartile range (IQR) 3-7), while receiving hospitals a median of 2 (IQR 1-6) transfer-in partners. A total of 16 receiving hospitals, all of which were designated base or co-base hospitals, had 15 or more transfer-in partners. Social network analysis of transfer patterns between hospitals confirmed that the network structure largely aligned with the planned regionalized transfer network in Taiwan. Understanding the network metrics helps track the structure and process aspects of regionalized care.
Assuntos

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal Base de dados: MEDLINE Assunto principal: Transferência de Pacientes / Análise de Rede Social Tipo de estudo: Observational_studies / Prognostic_studies Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal Base de dados: MEDLINE Assunto principal: Transferência de Pacientes / Análise de Rede Social Tipo de estudo: Observational_studies / Prognostic_studies Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article