Bibliographic citations
Montes, J., Elmenthaler, M. (2023). Sistema asistido por voz para la reserva predictiva de citas médicas en un hospital de categoría III-1 utilizando redes bayesianas [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/667803
Montes, J., Elmenthaler, M. Sistema asistido por voz para la reserva predictiva de citas médicas en un hospital de categoría III-1 utilizando redes bayesianas [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/667803
@misc{renati/405181,
title = "Sistema asistido por voz para la reserva predictiva de citas médicas en un hospital de categoría III-1 utilizando redes bayesianas",
author = "Elmenthaler Gonzales, Michael Martin",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
This project was born out of the need to reduce the increase in complaints from patients in a public hospital. In just one month, 3,000 claims have been registered, whose main causes are: Congestion in General Medicine offices, lack of knowledge of the admission staff, long queues to book a medical appointment and that the only channel to request a reservation is in person . The high number of claims has a high impact on the health entity because it could cause fines of up to 100 UIT (S/. 460,000.00) imposed by the National Superintendency of Health (SUSALUD), decrease in economic income, decrease in category level as a hospital until temporary closure. For this reason, this project proposes a mobile application that allows the patient to schedule medical care in an agile, direct and precise way through a chatbot in which the patient indicates his symptoms of discomfort through a pre-diagnosis based on Bayesian networks that refers the patient to the corresponding medical speciality. As a result, patient satisfaction has increased to 75% after having conducted a survey after using the software. It is concluded that the solution brings benefits to the patient and the hospital because it allows reducing the time to schedule a medical appointment, thanks to the system based on Bayesian networks. This reduces claims and avoids the sanctions granted by SUSALUD, as well as recategorization, the temporary closure and the decrease in economic income.
This item is licensed under a Creative Commons License