Funding entity Universidad Pontificia Comillas
Participated by IOON Technologies
After the medical crisis produced in the Spanish health system due to the COVID-19 pandemic, a collapse of mental health problems is looming as a result of the psychological impact that the pandemic has generated in Spanish society. Sources from the General Council of Psychology, the MIT Technology Review magazine, or the director of the WHO Mental Health Area herself, warn of the possible collapse of the mental health and primary care system. It is estimated that 10 million Spaniards are at risk of presenting psychological problems derived from COVID-19. The psychological affectation will be deep and prolonged in time. In previous investigations of SARS suffered in 2003, post-traumatic symptoms were observed in affected people after 3 years of the disease (Brooks et al., 2020). Taking into account the harshness with which this crisis has occurred, we have to be prepared to attend to many people affected directly (health workers, sick people, relatives of the deceased, people who have lost their jobs) and indirectly (confined people, reorganization of the social system…).
Given these data, it is necessary to prepare and offer the population resources, as personalized as possible, to meet two objectives. In the first place, offer psychological help to all those who may need it and, secondly, protect the health system, which has been so depleted.
In order to meet both objectives, it is necessary to provide mental health and primary care professionals with technological tools that allow serving a significant number of people. The application developed in this project will allow professionals to carry out psychological triage in real time. In this way, many people can be cared for and those with the greatest psychological risk referred to the healthcare service, avoiding the collapse of the system. The flow of derivations generated by the application would be as follows. The person who needs it accesses the application, fills in a series of screening questions and through decision trees and underlying algorithms, the person can be classified as “risk” or “no risk”. If it is classified as "risk", it is referred to a healthcare service of the corresponding health center; but if it is classified as “no risk”, the application is capable of offering a series of guidelines that help the person to better cope with the situation for which they have requested the use of the tool; in this way, the application supports and serves a significant volume of people who are not at risk. From the previous experience with iCygnus ( https://www.proyectocygnus.com ), this volume of people who could be served through the application would be 75%, while the remaining 25% would be referred to "risk". With these data we can say that the collapse of the health system would be avoided.