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Judicial claims for access to treatment in the private health insurance sector in Brazil

Published online by Cambridge University Press:  27 May 2025

Daniel Wei Liang Wang*
Affiliation:
Law School, FGV SP, São Paulo, Brazil
Natalia Pires de Vasconcelos
Affiliation:
Department of Sociology, University of Georgia, Athens, USA
Ezequiel Fajreldines dos Santos
Affiliation:
Law School, FGV SP, São Paulo, Brazil
Fernanda Mascarenhas de Souza
Affiliation:
Faculty of Law, University of São Paulo, São Paulo, Brazil
Luísa Bolaffi Arantes
Affiliation:
Department of Political Science, University of São Paulo, São Paulo, Brazil
Nathalia Molleis Miziara
Affiliation:
Faculty of Law, University of São Paulo, São Paulo, Brazil
Bruno da Cunha de Oliveira
Affiliation:
Law School, FGV SP, São Paulo, Brazil
Jacqueline Leite de Souza
Affiliation:
Law School, FGV SP, São Paulo, Brazil
Ana Maria Malik
Affiliation:
Business Administration School, FGV SP, São Paulo, Brazil
*
Corresponding author: Daniel Wei Liang Wang; Email: daniel.wang@fgv.br
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Abstract

While the literature has largely focused on legal challenges to public healthcare rationing decisions, claims against private insurance companies in voluntary health insurance (VHI) schemes have received less attention. This paper aims to fill this gap by analysing a representative sample of 1,547 court of appeal decisions related to treatment funding claims filed against private insurance companies in Brazil from 2018 to 2021. Courts decided 83.6% of cases in favour of patients, ordering VHI companies to fully fund the claimed treatment. Patients´ rate of success is even higher (96%) in the cases in which insurance companies denied coverage on the grounds that the claimed treatment was not listed in the benefits package mandated by regulation. Court decisions present additional challenges to setting priorities through health technology assessment and explicit packages in the VHI sector. This has broader implications for health care equality and access in Brazil.

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Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Flowchart of court cases from universe to sample by state.6

Figure 1

Table 1. Most common reasons given by insurance companies to deny coveragea

Figure 2

Graph 1. Distribution of cases by year and state.

Figure 3

Graph 2. Claimant´s rate of success by year and state court*. *Rate of success calculated based on the number of decisions where the court fully granted the claimant’s request.

Figure 4

Graph 3. Court position on ANS list for cases in which the defendant argues treatment was not part of the mandatory benefits package. *Percentages calculated based on the total number of cases where the VHI company claimed the treatment requested was not part of ANS’s list (669 cases). These include 198 cases in MG, 206 in RJ, and 265 in SP.

Figure 5

Graph 4. VHI sector´s health care expenditure and revenues from premium per year in BR$ (2012–2023). *The data on health care expenditure, revenue from premiums, and the number of users of private health plans were extracted from the Brazilian National Supplementary Health Agency (ANS) website (https://www.gov.br/ans/pt-br/acesso-a-informacao/perfil-do-setor/dados-gerais). Plans that cover dental care only were excluded. Values adjusted by inflation for current values as of December 2023 using the IPCA inflation index and calculated through the Central Bank of Brazil’s calculator available at: https://www3.bcb.gov.br/CALCIDADAO/publico/exibirFormCorrecaoValores.do?method=exibirFormCorrecaoValores&aba=1.

Figure 6

Table 2. Most common health conditions reported by claimantsa

Figure 7

Table 3. Types of health treatments requireda

Figure 8

Table 4. Correlation matrix between the 10 most common health conditions and types of health treatments requested

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