Addressing corruption is crucial for building a sustainable healthcare system that ensures access, quality, and equity in healthcare delivery. Despite that, many current strategies to combat corruption in the healthcare sector do not evaluate high-level corruption, such as corruption risks occurring at sub-national levels. This work bridges this gap by providing corruption risk profiles of Italian contracting authorities responsible for procuring goods and services for healthcare facilities in the public procurement process. Using an array of 14 red flags of corruption risk and an extended Item Response Theory model applied to a big data source made available by the Italian Anti-corruption Authority, our main findings show that: i. the risk of corruption is a multidimensional occurrence, which can be represented as a four-dimensional latent variable; ii. there are eight clusters of contracting authorities, having distinct and well-defined risk profiles over the four ascertained dimensions of corruption risk; iii. the distribution of risk profiles at sub-national level showcases relevant geographic variations and emphasises the need for tailored anti-corruption strategies to effectively address region-specific challenges and risk factors.

Sustainability and high-level corruption in healthcare procurement: Profiles of Italian contracting authorities

Del Sarto, Simone
;
Gnaldi, Michela;
2024

Abstract

Addressing corruption is crucial for building a sustainable healthcare system that ensures access, quality, and equity in healthcare delivery. Despite that, many current strategies to combat corruption in the healthcare sector do not evaluate high-level corruption, such as corruption risks occurring at sub-national levels. This work bridges this gap by providing corruption risk profiles of Italian contracting authorities responsible for procuring goods and services for healthcare facilities in the public procurement process. Using an array of 14 red flags of corruption risk and an extended Item Response Theory model applied to a big data source made available by the Italian Anti-corruption Authority, our main findings show that: i. the risk of corruption is a multidimensional occurrence, which can be represented as a four-dimensional latent variable; ii. there are eight clusters of contracting authorities, having distinct and well-defined risk profiles over the four ascertained dimensions of corruption risk; iii. the distribution of risk profiles at sub-national level showcases relevant geographic variations and emphasises the need for tailored anti-corruption strategies to effectively address region-specific challenges and risk factors.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1588603
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