Rodríguez Aguilar, Román
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Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
Rodríguez-Aguilar, Román
Rodríguez-Aguilar, R.
Aguilar, R.R.
Rodriguez-Aguiler, R.
Rodríguez, R.
Roman, R.A.
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ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

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Optimization of public resources through an ensemble-learning model to measure quality perception in the social protection system in health of Mexico

2018 , Rodríguez Aguilar, Román , Rivera-Peña, Gustavo

In order to optimize the use of public resources, a model of ensemble learning was proposed to measure the perception of quality in the medical care granted to the people affiliated to the social protection in health system of Mexico. Which allows a more efficient allocation of resources based on the main areas of opportunity identified in the measurement of service quality. Identify the effect of the main factors that are directly related to the satisfaction level and perception of quality of health services. A satisfaction index was built using an ensemble model using principal component analysis, logistic model and bagging meta-estimator, to identify the effect of a group of factors in the perception of quality of health services and monitor the perceived quality of users in real time. The survey data collected for the “Social Protection System in Health-SPSS 2014” was used, considering a sample of 28,290 users. The proposed index shows, in general, the positive perception of quality of health services, the national average index was of 0.0756, 95% CI [− 9.714 to 2.027]. There are factors statistically significant (P < 0.05) that influence these results, among the most important that can be highlighted is the good perception of infrastructure OR 2.12; CI [95% 1.9–2.36]; the gratuity of the service provided OR 1.98; CI [95% 1.42–2.76]; and full medicines supply OR 1.81; CI [95% 1.91–2.36]. The key factors identified that determine the perception of quality allow to define focused strategies and lines of action to improve service quality as well as better allocation of resources. ©Springer, The Authors.

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Catastrophic health spending in Mexico and its determinants, 2002-2014

2017 , Rodríguez Aguilar, Román , Rivera-Peña, Gustavo

Objective: To assess the financial protection of public health insurance by analyzing the percentage of households with catastrophic health expenditure (HCHE) in Mexico and its relationship with poverty status, size of locality, federal entity, insurance status and items of health spending. Method: Mexican National Survey of Income and Expenditures 2002-2014 was used to estimate the percentage of HCHE. Through a probit model, factors associated with the occurrence of catastrophic spending are identified. Analysis was performed using Stata-SE 12. Results: In 2014 there were 2.08% of HCHE (1.82-2.34%; N = 657,474). The estimated probit model correctly classified 98.2% of HCHE (Pr (D) ≥ 0.5). Factors affecting the catastrophic expenditures were affiliation, presence of chronic disease, hospitalization expenditure, rural condition and that the household is below the food poverty line. Conclusions: The percentage of HCHE decreased in recent years, improving financial protection in health. This decline seems to have stalled, keeping inequities in access to health services, especially in rural population without affiliation to any health institution, below the food poverty line and suffering from chronic diseases. ©2017 Gaceta Médica de México, Los autores.

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An analytical intelligence model for the management of resources for the treatment of high-cost diseases: the case of HIV in Mexico

2020 , Rodríguez Aguilar, Román , Rivera-Peña, Gustavo

In the health sector, it is very important to have adequate control over the allocation of resources; this becomes much more relevant in the case of high-cost diseases, HIV is one example of this. The use of analytical intelligence allows the transformation of raw data into meaningful and useful information to make decisions. To support the management of resources in the health sector an analytical intelligence model based on survival analysis of patients under antiretroviral treatment in the Ministry of Health of Mexico is proposed. A survival model was carried out using a cohort of people with HIV under antiretroviral treatment attended by the Ministry of Health for the period 2007–2015. Sociodemographic variables, viral load, dates of treatment initiation and death were used. Kaplan–Meier method and the logarithmic rank test, as well as the Cox proportional-hazard model, were used. The proposed model can serve as a strategic information management tool for decision-making about the care and financing of high-cost diseases in the health sector. The results show that the probability of survival in people with HIV is higher for currently preferred treatments for treatment initiation and recently incorporated. Increasing the level of CD4 for the start of treatment generates greater probabilities of survival for patients. It is necessary to comprehensively evaluate the prescription and initiation of treatment policies according to CD4 levels to guarantee the financial sustainability of antiretroviral treatment in the Ministry of Health since these measures imply greater use of resources. It would be helpful to implement this type of analytical intelligence model for the monitoring and management of resources in the health sector. © Springer Nature

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Gasto catastrófico en salud en México y sus factores determinantes, 2002-2014

2017 , Rodríguez Aguilar, Román , Rivera-Peña, Gustavo

Objetivo: Evaluar la protección financiera del aseguramiento público de salud mediante el análisis del porcentaje de hogares con gasto catastrófico en salud (HGCS) en México y su relación con la condición de pobreza, el tamaño de la localidad, la entidad federativa, la condición de aseguramiento y los rubros de gasto en salud. Método: Se utilizó la Encuesta Nacional de Ingreso y Gasto de los Hogares 2002-2014 para estimar el porcentaje de HGCS. Mediante un modelo probit se identificaron los factores asociados a la ocurrencia de gasto catastrófico. El análisis se realizó con Stata-SE 12. Resultados: En 2014 había un 2.08% de HGCS (1.82-2.34%; N = 657,474). El modelo probit estimado clasificó correctamente el 98.2% de los HGCS (Pr(D)≥0.5). Los factores que incidieron en el gasto catastrófico fueron la afiliación, la presencia de enfermedades crónicas, el gasto en hospitalización, la condición rural y que el hogar estuviera por debajo de la línea de pobreza alimentaria. Conclusiones: El porcentaje de HGCS disminuyó en los últimos años, mejorando la protección financiera en salud. Esta disminución pareciera haberse estancado, manteniendo inequidades en el acceso a servicios de salud, sobre todo en población rural, sin afiliación a alguna institución de salud, por debajo de la línea de pobreza alimentaria y con enfermedades crónicas. ©2017 Gaceta Médica de México, Los autores.

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