Monitoring and Care Impact of Participants Predicted to Have High Variability in Healthcare Expenditures: An Artificial Intelligence Application in the Brazilian Supplementary Health System

Authors

  • Frank Ney Sousa Lima Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF
  • Carlos Wilson Gomes de Barros Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF
  • Antônio Cipriano Neto Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF
  • Bruna Matter dos Santos Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF
  • Wanderley Akira Shiguti Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF
  • Weverton Vieira da Silva Rosa Caixa de Assistência dos Funcionários do Banco do Brasil (CASSI) – Brasília/DF

DOI:

https://doi.org/10.66305/jbas.v6i1.17

Keywords:

Artificial intelligence, Predict models

Abstract

This study aims to identify participants with a high probability of significantly impacting future healthcare expenditure variability and to generate information to support the continuous monitoring of the predicted population.

Published

2026-02-06

How to Cite

Sousa Lima, F. N., Wilson Gomes de Barros, C., Cipriano Neto, A., Matter dos Santos, B., Akira Shiguti, W., & Vieira da Silva Rosa, W. (2026). Monitoring and Care Impact of Participants Predicted to Have High Variability in Healthcare Expenditures: An Artificial Intelligence Application in the Brazilian Supplementary Health System. Brazilian Journal of Health Auditing, 6(1), e2606004. https://doi.org/10.66305/jbas.v6i1.17

Issue

Section

Original articles