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.
Main Affiliation
ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

Research Output
Now showing 1 - 4 of 4
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Catastrophic Health Spending by COVID-19 in the Mexican Insurance Sector

2024-01-01 , Domínguez-Gutiérrez, Ulises , Rodríguez Aguilar, Román

The COVID-19 pandemic that the world has been suffering for 3 years has generated major impacts worldwide, both in public health systems and in the private insurance industry. The high costs of care derived from cases with complications have likewise generated a great impact on the private insurance industry. In the case of Mexico, the mortality rates observed are among the first places, in addition to generating a great impact on private insurance. This work deals with the measurement of the impact of catastrophic expenses derived from COVID-19 in an insurance company; using a set of machine learning models, the key variables in the estimation of patients with potential catastrophic expenses were determined. The results show that the estimated classification model has a positive performance in addition to allowing the identification of the main risk factors of the insured as well as their potentially catastrophic impact on insurance companies.© 2024 Springer Nature

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Machine Learning for Digital Shadow Design in Health Insurance Sector

2024 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio , Rodríguez-Aguilar, Miriam , Marmolejo-Saucedo, Liliana

The digital transformation process in organizations has accelerated significantly in recent years; the COVID-19 pandemic was a catalyst that highlighted the need for digitalization in all sectors. In the case of the health sector, this process is complex due to the processes inherent in health care as well as the integration of multiple sectors that allow the provision of health services. A first approach towards the construction of a Digital Twin in health organizations is a Digital Shadow that allows an orderly transition towards digital operation in real time. This paper presents a first approach to the design of a Digital Shadow for the health insurance sector and specifically for the care of patients diagnosed with COVID-19 through the implementation of an analytical intelligence system based on machine learning models to forecast and monitor to patients who represent catastrophic cases for the insurer. © 2024 Springer Nature

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Application of Spectral Clustering for the Detection of High Priority Areas of Attention for COVID-19 in Mexico

2021 , Rodríguez Aguilar, Román

The recent COVID-19 pandemic has represented a great challenge for health systems around the world. That is why it is necessary to propose strategies for prioritizing care and containing the pandemic. This work proposes the use of spectral clustering to characterize high-priority areas of care based on key information on the performance of the pandemic as well as health system variables. The result shows the generation of high priority areas not only due to the deaths observed but also due to the clinical, demographic and health system variables. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

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Designing a resilient supply chain: An approach to reduce drug shortages in epidemic outbreaks

2020 , Lozano-Díez, José Antonio , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

Introduction: Supply network design is a long-studied topic that has evolved to address disruptive situations. The risk of supply chain disruption leads to the development of resilient supply chains that are capable of reacting effectively. Objectives: In the context of public health, drug supply networks face shortage challenges in many situations, such as current epidemic outbreaks such as COVID-19. Drug shortages can occur due to manufacturing problems, lack of infrastructure, and immediate reaction mechanisms. Methods: The case study is solved with anyLogistix optimization and simulation software. RESULTS: We present the results of a hypothetical study on the impact of COVID-19 on a regional supply network. The results of this research are intended to be the basis for the design of resilient supply chains in epidemic outbreaks. Conclusión: Drug providers should consider strategies to prevent or reduce the impact of shortages as well as disruption spreads. ©2020 José Antonio Lozano Díez, José Antonio Marmolejo Saucedo & Roman Rodríguez Aguilar, licensed to European Alliance for Innovation.

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