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Table 3 Summary of studies’ social network analysis methods

From: Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review

Authors Effken et al. Hossain and Guan Lindberg et al. Alexander et al. Creswick and Westbrook Mundt et al.
Data collection method Network survey, previously collected survey with patient outcomes Extraction from National Hospital Ambulatory Medical Care Survey (NHAMCS), patient record surveys selected from emergency departments Survey, focus group discussions, observation, and patient data extraction Observation, previously collected survey Network survey and clinical audit Network survey and electronic health record extractions
Boundary specification method/sampling (if applicable) All nursing staff who worked in one of seven patient care units in three magnet hospitals Emergency departments of 359 hospitals responded to the ambulatory survey section of NHAMCS survey conducted by the CDC. All staff at 21 hemodialysis facilities that form part of the CDC Hemodialysis BSI Prevention Collaborative Comparative case study of two units within two nursing homes, one with the highest IT sophistication and one with the lowest IT sophistication based on a statewide census in 2007. Nodes were both HCWs and the locations and content of their interactions. All HCWs in two wards Eight clinics in Southern Wisconsin were invited to participatein the study, and six agreed. Sites were chosen based on consultation with leadership from the healthcare system.
Network category studied
1. Whole, ego, or hybrid network
2. Directed or undirected
3. Valued or dichotomous
1. Whole network
2. Directed
3. Valued
1. Whole network
2. Directed
3. Dichotomous
1. Whole network
2. Directed
3. Valued
1. Whole network
2. Directed
3. Valued
1. Whole network
2. Directed
3. Valued
1. Whole network
2. Directed
3. Valued
Response rate Not stated N/A as SNA data extracted from surveys on patients 90% N/A as SNA from observation 90% 97%
Network metrics used Clustering coefficient, component count strong, component count weak, density, diffusion, fragmentation, hierarchy, isolates, in-degree centrality, out-degree centrality, eigenvector centrality, simmelian ties, betweenness centrality, number of triads, and number of cliques SNA metrics: degree, density, and centrality Connectivity, inclusion, reach, and centralization None Density
Reciprocity
In-degree centrality
In-degree centrality, tie strength
Analyses conducted Correlations (Spearman Rho) calculated between SNA metrics and patient outcomes Multiple linear regression, p values and r values reported Quantitative: Pearson X 2 and Fisher’s exact test, t test. Reported p valuesQualitative analysis: reflexive observation and contextual analysis Quantitative: calculated highest and lowest ITS NH from survey data in an earlier study Qualitative: axial coding, themes developed using human factors theory Chi-squared with p values Linear modeling (GLMM) and sensitivity analyses
Software ORA, Excel UCINET, SPSS, Excel Not stated ORA, Nvivo, Excel UCINET and NetDraw UCINET, HLM 7.0
Network map (yes/no) Yes Yes Not stated Yes Yes Yes
Further research Replicate study, expand to larger, more diverse group of patient care units. Consider shifting to more patient-centric focus, including full team of care providers Further research needed to verify the relationship suggested by this study between coordination and social network analysis. Survey of emergency departments within Australia for a period of 1 year, to allow accurate measurements to be taken and utilized for the study and for verifying the relationship between social networks and coordination in an emergency department. None stated To demonstrate how organization analytics about communication can be used to benchmark evidence-based practices Further research on link between medication advice-seeking networks and errors, as this study suggests. Also, whether the increased use of electronic medication management systems means that information needs are met through channels other than communication between physicians, nurses and pharmacists, or that information sharing regarding medication issues is reduced and may impact medication safety. Evaluate interventions to engage senior physicians in advice exchange networks. Further health applications of SNA surveys needed to improve validity and reliability of tools. Longitudinal and experimental studies needed to explore the causal pathways between team communication variables and alcohol-related patient care
Network intervention (yes/no) No No Yes (although intervention not based on baseline network analysis. Rather, it was developed with the intention of changing HCW networks) No No No