Using self organising feature maps to unravel process complexity in a hospital emergency department: A decision support perspective

Abstract

In systems that are complex and have ill-defined inputs and outputs, and in situations where insufficient data is gathered to permit exhaustive analysis of activity pathways, it is difficult to get at process descriptions. The complexity conceals patterns of activity, even to experts, and the system is resistant to statistical modelling because of its high dimensionality. Such is the situation in hospital emergency departments, as borne out by the paucity of process models for them despite the continued and vociferous efforts of experts over many years. In such complex and ill-defined situations, it may be possible to access fairly complete records of activities that have taken place. This i..