• Run by Bristol, North Somerset and South Gloucestershire Clinical Commissioning Group (CCG).
  • Aimed to improve understanding of how care pathways are performing and enable ‘what if’ analysis to identify more effective and efficient service configurations.
  • A versatile pathway tool has been developed that will allow NHS analysts and managers to understand and model patient flow.

Although there are some pathway flow tools available to NHS organisations, there are few that are able to mechanistically model the dynamics of pathways, linking the various wards, clinics or surgeries.

This project, led by Bristol, North Somerset and South Gloucestershire CCG, and involving collaboration with the Centre for Healthcare Innovation and Improvement at University of Bath, explored how system-level data analytics can meet complex challenges such as maintaining fluidity in patient flow and reducing delayed transfers of care in acute beds. 

The project involved building an analytical tool that is sufficiently flexible to accommodate a number of interconnected services along a given patient pathway. The tool is based on an underlying model that represents the patient pathway as a network of ‘queues’ between the considered services, along which patient movements are simulated.

The tool promotes a better understanding of pathway dynamics through visualising patient flow, bottlenecks and waiting times, using various interactive illustrations. It is open source and easy to use, with a purpose-built user interface in R. A suite of documents accompany the tool, including technical documentation and manuals.

The tool is now being routinely used within the CCG, providing crucial support for live delivery projects, such as the multi-million pound reconfiguration towards a centralised stroke service. The tool is available to other organisations within the NHS, complete with a use case library demonstrating practical application of the model.

Information about the tool has been presented at conferences, and further dissemination through workshops and publications are forthcoming.


For more information about this project, please contact Dr Richard Wood, Head of Modelling and Analytics, Bristol, North Somerset and South Gloucestershire Clinical Commissioning Group.

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