We identified a lapse in clinical pathways for a daily evolving outbreak of SARS CoV. We wanted to bring two systems and add value by creating a clinical pathway based on evidence.
Our objective was to add value and provide a secondary information pathway for the general public that are concerned about contracting the disease or unclear on what they should do if they or a loved one was to contract the disease. Current information available through the 111 questionnaire online is limited, and leads t many members of the public calling the phone service for further information. We wanted to create an application that lets the public know when to present to a hospital and when to not worry in a more thorough format. At current rates the public calling the 111 service are experiencing waiting times of up to 3 hours and even being cut off at points.
We wanted to add to this by using a convolutional neural network image interpreter for identifying chest xrays for pneumonia and build a clinical pathway based on a literate review conducted in the hackathon to give recommendations embedded in clear evidence and clinical facts.