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vol.37 issue1Variation in timing of decisions to withdraw life-sustaining treatment in adult ICU patients from three centres in different geographies: Do clinical factors explain the difference?Decision-making in the ICU: An analysis of the ICU admission decision-making process using a '20 Questions' approach author indexsubject indexarticles search
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Southern African Journal of Critical Care (Online)

On-line version ISSN 2078-676X
Print version ISSN 1562-8264

Abstract

GOPALAN, P D  and  PERSHAD, S. Identifying ICU admission decision patterns in a '20-questions game' approach using network analysis. South. Afr. j. crit. care (Online) [online]. 2021, vol.37, n.1, pp.27-36. ISSN 2078-676X.  http://dx.doi.org/10.7196/SAJCC.2021.v37i1.473.

BACKGROUND: The complex intensive care unit (ICU) admission decision process has numerous non-linear relationships involving multiple factors. To better describe and analyse this process, exploration of novel techniques to clearly delineate the importance and interrelationships of factors is warranted. Network analysis (NA), based on graph theory, attempts to identify patterns of connections within a network and may be useful in this regard. OBJECTIVES: To identify patterns of ICU decision-making pertaining to patients referred for admission to ICU and to identify key factors, their distribution, connection and relative importance. The secondary aim was to compare subgroups as per decision outcomes and case labels. METHODS: NA was performed using Gephi software package as a secondary analysis on a dataset generated from a previous study on ICU admission decision-making process using a 20-questions game approach. The data were standardised and coded up to a quaternary level for this analysis. RESULTS: The coding process generated 31 nodes and 964 edges. Regardless of the measure used (centrality, prestige, authority and hubs), properties of the acute illness, progress of the acute illness and properties of comorbidities emerged consistently as among the most important factors and their relative rankings differed. Using different measures allowed important factors to emerge differentially. The six subgroups that emerged from the modularity measure bore little resemblance to traditional factor subgroups. Differences were noted in the subgroup comparisons of decision outcomes and case prognoses. CONCLUSIONS: The use of NA with its various measures has facilitated a more comprehensive exploration of the ICU admission decision, allowing us to reflect on the process. Further studies with larger datasets are needed to elucidate the exact role of NA in decision-making processes.

Keywords : critical care; intensive care unit; ICU admission; network analysis; ICU decision-making; 20-questions game.

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