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[Public-private partnerships in hospital administration in the Brazilian Unified National Health System in Bahia State, Brazil].

Laise Rezende de AndradeIsabela Cardoso de Matos Pinto
Published in: Cadernos de saude publica (2022)
The process of building Brazil´s Unified Health System has always been a space of dispute between the political forces that defend greater private sector participation in patient care and administration of services and those who defend strengthening public administration. In the context of underfinancing of the Brazilian Unified National Health System (SUS), associated with the restrictions imposed by the so-called Fiscal Responsibility Law, new management models have been adopted in hospital administration, including public-private partnerships (PPPs). Considering the relevance of investigating decision-making processes pertaining to the adoption of these models by State Health Departments, this study aims to analyze the decision-making processes and incorporation of this hospital administration model in the State of Bahia, Brazil, the first administrative concession in Brazil´s health sector. This is a case study in which the theoretical reference was Social Game Theory elaborated by Carlos Matus, linked to the Public Policy Cycle analytical model. The data were produced with document research and semi-structured interviews with key informants who participated in the pre-decision and decision-making stages of the PPP model. The article presents the political game involved in the choice of this alternative among other hospital administration models, besides debating the models´ advantages and disadvantages according to the key actors and concludes that determinants (not only financial, but also political and ideological) marked the decision-making process for the PPP model in Bahia, in which the driving factor and source of consultancy was the International Finance Corporation, an arm of the World Bank.
Keyphrases
  • healthcare
  • decision making
  • mental health
  • health information
  • primary care
  • risk assessment
  • electronic health record
  • young adults
  • artificial intelligence
  • quality improvement
  • human health
  • climate change