Risk Adjustment Revisited Using Machine Learning Techniques

Riascos, Álvaro; Romero, Mauricio; Serna, Natalia

doi:10.2139/ssrn.2973514

Cited by 2 publications

(2 citation statements)

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“…From 2013 to 2019, the remote region presents the greatest severity, on average, 1.34 million COP, followed by cities with 1.1 million, normal with 0.9 million and special with 0.7 million. During this period, severity in the remote region grew 7.9% in real terms, in cities 11.5%, in normal region 44 Figure 3 shows that the number of people exposed to risk in the CR has grown from 2013 to 2019. In 2013 there were 19.5 million exposed and in 2019 22.3 million, which means a growth of 13.9% over the seven years of analysis.…”

Section: Datamentioning

confidence: 97%

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Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021

et al. 2023

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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.

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Section: Datamentioning

confidence: 97%

“…In this scenario, the analysis of the CPU's pricing becomes relevant. In this regard, the specialized literature has investigated alternatives for risk adjustment in SGSSS health spending [4,21,43,44]. However, no studies have been found that develop a particular method for calculating the CPU of the risk groups defined by the legislation.…”

Section: Introductionmentioning

confidence: 99%