Um estudo sobre a sobrevivência das operadoras de planos de saúde no mercado de saúde suplementar pós regulação

• Ano de defesa: 2015
• Autor(a) principal: Pauxis, Alexandre Ripardo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Saúde Suplementar
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/15333

In spite of its existence dating since the 1950’s, it wasn’t until the creation of the Brazilian Law on Health Insurance in 1998 and of the federal autarchy (independent agency) named ANS – National Agency for Supplementary Health – in 2000, that supplementary health market came to being regulated. Amongst the Agency’s many attributions is taking the Health Care Operator out of the supplementary market, either for not obeying the regulatory norms or for having its extrajudicial liquidation declared on account of dire financial and economic problems that prevent the Operator from assisting its beneficiaries. In this perspective, we notice a number of Health Care Operators exiting the market usually causing a series of social-economic “issues” for the participant agents such as temporary health care assistance stoppage, financial default by the Operator regarding providers’ services – at times bringing the providers to endure financial difficulties due to lack of payment, unforeseen necessity of action by the regulatory agency in order to relocate beneficiaries to different Operators - thus creating complications to these Operators in receiving new beneficiaries with no grace period and restrained demand increasing loss, and so forth. Therefore it proves to be relevant an investigation towards defining a profile of Operators fated to failure, from traits that are known to determine the financial strength of these companies. To this end we use variables, chosen based on scientific studies or empirical knowledge, to be applied on a 129 months’ time series Cox regression model, which is recommended by the scientific community as an important Survival Analysis model.