Design of a triage chatbot to rule out respiratory diseases: Systematic Review

Ponte Santos A.; Ordoñez Kevin Albert D.; Condor Baldeon A.A. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/laccei2024.1.1.567

Resumen

Nowadays, companies, in order to increase their productivity, have incorporated AI such as chatbots which are computer programs capable of conversing naturally with humans in a more efficient way. In this sense, chatbots are considered worthy of research in healthcare, as they play a crucial role in the triage of respiratory diseases. Their impact lies in their ability to streamline healthcare triage, in the initial assessment of the patient by providing a quick and accessible way to describe their symptoms, which facilitates the early identification of severe cases and thus reduce hospital collapse. In addition, the implementation of this chatbot provides information, answers questions and efficiently directs patients to relevant resources and recommendations to be subsequently diagnosed and treated by the physician. To address this issue, two systematic review methodologies were employed, such as the PICO and PRISMA method. Furthermore, by formulating research questions and inclusion and exclusion criteria, 10 open-access research articles were collected from Scopus and Redalyc databases. In the end, the results revealed that detailed information gathering by the chatbot, supported by advanced algorithms, improves the accuracy of triage when assessing symptom severity. Therefore, this chatbot not only functions as a preliminary diagnostic tool, but also plays a crucial role in providing information on preventive measures and self-care guidelines.

Instituciones: Universidad Tecnológica del Perú