In January 2020, I took part in the Bristol Wellbeing Data Jam, hosted by Bristol City Council in collaboration with Bristol Health Partners and Bristol Is Open. The aim of this hackathon was to use open data to produce something to improve the wellbeing of Bristol citizens. I partnered up with Ben Wainwright, a Computer Science with Innovation student, and Ellie Leopold, a Psychology with Innovation student to produce PAVE - the Patient Access Visualisation Engine.
Recognising that the Bristol North Somerset and South Gloucestershire Clinical Commissioning group (BNSSG CCG) found it difficult to visualise hollistically how patients were utilising the health service, we decided to create a visualisation tool that would allow commissioners to plug in patient data to visualise where there are strains on the system that need to be alleviated. However, much of the data we needed to test our idea is behind closed doors. In order to demonstrate the idea, we generated mock data sets to represent what might be going on in the system. This version, PAVE Flow, can be found here.
During the COVID-19 Crisis of 2020, the PAVE team took part in The Global Hack in order to adapt our system to be useful to capacity planners in healthcare crises. Our adaptation saw us remove the flow element and strip PAVE down to show capacity and occupancy data of key COVID response centres within Bristol. Our system would allow planners to trace capacity history in order to visually estimate where greater need for increased capacity might occur. This tool is intended only to be used at the planning stage, however, as hosting it online would pose a security and national fear risk if the visualisation was misread or the data mishandled. As before the data required is was not available to us, so we developed more mock data for the new visualisation which is available here.
We are currently opening discussions with key individuals from the Bristol healthcare system about consulting on the development of PAVE for integration into mission critical systems.
Watch this space:

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