Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021
Abstract The Capitation Payment Unit (CPU) financing mechanism constitutes more than 70% of health spending in Colombia, with a budget allocation of close to 60 trillion Colombian pesos for the year 2022 (approximately 15.7 billion US dollars). This article estimates actuarially, using modern techni...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-02-01
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| Series: | Health Economics Review |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13561-022-00416-5 |
| _version_ | 1797865642968219648 |
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| author | Oscar Espinosa Valeria Bejarano Jeferson Ramos Boris Martínez |
| author_facet | Oscar Espinosa Valeria Bejarano Jeferson Ramos Boris Martínez |
| author_sort | Oscar Espinosa |
| collection | DOAJ |
| description | Abstract The Capitation Payment Unit (CPU) financing mechanism constitutes more than 70% of health spending in Colombia, with a budget allocation of close to 60 trillion Colombian pesos for the year 2022 (approximately 15.7 billion US dollars). This article estimates actuarially, using modern techniques, the CPU for the contributory regime of the General System of Social Security in Health in Colombia, and compares it with what is estimated by the Ministry of Health and Social Protection. Using freely available information systems, by means of statistical copulas functions and artificial neural networks, pure risk premiums are calculated between 2015 and 2021. The study concludes that the weights by risk category are systematically different, showing historical pure premiums surpluses in the group of 0–1 years and deficits (for the regions normal and cities) in the groups over 54 years of age. |
| first_indexed | 2024-04-09T23:11:25Z |
| format | Article |
| id | doaj.art-f549a5fbf5fa43f89426865d886859b9 |
| institution | Directory Open Access Journal |
| issn | 2191-1991 |
| language | English |
| last_indexed | 2024-04-09T23:11:25Z |
| publishDate | 2023-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Health Economics Review |
| spelling | doaj.art-f549a5fbf5fa43f89426865d886859b92023-03-22T10:24:04ZengBMCHealth Economics Review2191-19912023-02-0113112010.1186/s13561-022-00416-5Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021Oscar Espinosa0Valeria Bejarano1Jeferson Ramos2Boris Martínez3Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de ColombiaEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de ColombiaEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de ColombiaDepartment of Mathematics, Universidad Nacional de ColombiaAbstract The Capitation Payment Unit (CPU) financing mechanism constitutes more than 70% of health spending in Colombia, with a budget allocation of close to 60 trillion Colombian pesos for the year 2022 (approximately 15.7 billion US dollars). This article estimates actuarially, using modern techniques, the CPU for the contributory regime of the General System of Social Security in Health in Colombia, and compares it with what is estimated by the Ministry of Health and Social Protection. Using freely available information systems, by means of statistical copulas functions and artificial neural networks, pure risk premiums are calculated between 2015 and 2021. The study concludes that the weights by risk category are systematically different, showing historical pure premiums surpluses in the group of 0–1 years and deficits (for the regions normal and cities) in the groups over 54 years of age.https://doi.org/10.1186/s13561-022-00416-5Pure risk premiumHealth systemCopulasArtificial neural networksActuarial science |
| spellingShingle | Oscar Espinosa Valeria Bejarano Jeferson Ramos Boris Martínez Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 Health Economics Review Pure risk premium Health system Copulas Artificial neural networks Actuarial science |
| title | Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 |
| title_full | Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 |
| title_fullStr | Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 |
| title_full_unstemmed | Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 |
| title_short | Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021 |
| title_sort | statistical actuarial estimation of the capitation payment unit from copula functions and deep learning historical comparability analysis for the colombian health system 2015 2021 |
| topic | Pure risk premium Health system Copulas Artificial neural networks Actuarial science |
| url | https://doi.org/10.1186/s13561-022-00416-5 |
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