Identification of high-risk beneficiaries in private healthcare insurance

• Published in: Health informatics journal Vol. 30; no. 1; p. 14604582241230384
• Main Authors: Santos, Adauto, Leal, Gislaine Camila Lapasini, Balancieri, Renato
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2024; SAGE PUBLICATIONS, INC
• Subjects: Algorithms; Bayes Theorem; Databases, Factual; Health care; Health insurance; Humans; Insurance; Machine Learning; knowledge discovery in databases; machine learning; health insurance; data mining; healthcare

The objective of this study was to apply the Knowledge Discovery in Databases process to find out if beneficiaries of a private healthcare insurance would belong, at least once, to the ‘very high cost’ and ‘complex cases’ groups throughout the 12 months after the month when algorithms were applied....