SATIStally is a new addition to the SATIS first response IT range. It gives Command and Control immediate visibility of the numbers of people in or between different locations and maintains a full log. It has been developed to be used in disasters or emergencies together with the SATIS field medical clinic as part of the SATIS first response range of IT systems. However, it has uses in a wide range of situations such as managing crowds at events or in the different locations of a building site.
In a major disaster or emergency, there is often limited information about the numbers of people affected. Some estimates suggest that information is captured on as few as 20% of the total numbers. SATIStally will provide considerably more accurate data about the extent and nature of the event than attempting to record the situation in other ways, particularly using paper. Its use will aid significantly in both enabling effective control and in informing agencies of the true extent and nature of a crisis.
SATIStally is a simple app that runs on an iPhone and allows people who are labelled using a bar- or QR-coded wristband to be assessed using up to six simple binary (Yes / No) questions. It also records their location. This information is immediately transferred via network (normally Wi-Fi) to Command and Control where it is logged displayed on a configurable dashboard. If there is no connection, the information is retained on the phone until connection resumes.
The dashboard can be set up with different thresholds for each location so that problems are instantly visible.
SATIStally is fully integrated into the SATIS field medical clinic and can be used when people arrive as the first stage of a triage process, allowing people to be sent to the appropriate location, such as emergency room, nurse-led clinic or childrens’s room.
SATIStally is also an important tool in providing detailed and, in particular, accurate information about people affected during a disaster or emergency, information that is otherwise elusive as data tends to be incomplete and necessary estimates often prove significantly low.