When in need of taking a child to an emergency, in addition to all the transportation and difficulties to find the nearest and empty hospitals, it is necessary to go through a check-in and screening process that can often delay and worsen patients' symptoms depending on the degree of the emergency. Also, more than 50% of the cases treated in the ER are not emergency cases and could be being treated in another way. These cases increase the queue for assistance and prolonging the waiting time.
Arcanjo is a WhatsApp bot designed to improve several processes during the procedure of taking a child to a pediatric emergency. With our solution, when the person responsible for the child decides that it's time to go to the hospital, during the way he can perform a pre-screening of the patient, where he informs the bot about the various symptoms the child is feeling. Using Artificial Intelligence, the bot can classify these symptoms as 'Urgent' or 'Non-Urgent' and already set up a queue after check-in. This process provides more information about the waiting time inside the hospital, in addition to allowing the child's guardian to have an estimate of his position on the waiting list for care in the screening.
After performing this procedure, the bot can suggest nearby hospitals that have the necessary expertise to treat the child, showing the waiting time of each one. Also, knowing the severity of the patient's case, the bot can suggest a consultation if it identifies that the child's case is not so serious. This helps in solving a very common situation to happen in emergency services for children, 70% of children who are attended in the emergency do not have an urgent case.
After that, the child's guardian moves to the check-in phase prior to arrival at the hospital. The bot asks for documentation, which also allows to speed up the waiting time for check-in inside the hospital, receiving a QR Code for identification when getting to the hospital. Through this QR Code, it is possible to have control of all patient information, which can be transmitted from the moment of symptom information in the pre-screening, until the moment aftercare. In addition, the system allows the control of the user's stay in the hospital, making it possible to measure the average waiting time and to control productivity within the hospital.
After the ER care, the bot sends a follow-up message suggesting an appointment to perform a follow-up consultation, ensuring the user's return to the hospital and minimizing the chance of recurrence in the emergency.
