Análisis del efecto de la afiliación al Seguro Integral de Salud en el gasto de bolsillo en salud realizado por adultos mayores pobres con enfermedades crónicas en Perú: Un análisis del 2009 - 2019 mediante una variable instrumental

Abstract

This project focuses on optimizing customer service processes at the Municipal Government of Marañon by implementing a bilingual (Spanish-Quechua) chatbot developed with artificial intelligence. The language barrier in assisting Quechua-speaking citizens and the administrative staff’s workload have created the need for this technological solution, aimed at improving service efficiency and quality. The chatbot, developed using an agile methodology, will allow citizens to access information about documentary procedures immediately and in their native language. Expected outcomes include reduced response times, reduced workload for staff, and improved citizen satisfaction. The implementation relies on Dialogflow for natural language processing and Facebook Messenger as the interaction platform. Furthermore, project management will follow the PMBOK guidelines, ensuring efficient resource management, scheduling, and quality control throughout the project's lifecycle.

Latin America is experiencing an accelerated aging process, according to the Inter-American Development Bank estimations between 2030 and 2050, the proportion of older adults will increase from 17% to 25%. In the case of Peru, this proportion is expected to reach approximately 22%. Currently, 4 out of 10 Peruvian households have an elderly person among their members. The high prevalence of chronic diseases in this population group (70%), makes it extremely urgent to address complex public health problems affecting them. In this context, factors such as access to healthcare, the efficiency of healthcare systems, reducing out-of-pocket health expenditures (OHE), and equity in resource distribution are crucial. This research proposes to analyze the effect of SIS affiliation on the OHE assumed by the elderly population living in poverty and suffering from chronic diseases. To achieve this, the level of SIS penetration will be used as an instrumental variable (IV). Cross-sectional data from the National Household Survey for 2009-2019 will be used.