Inovação aberta em saúde para o enfrentamento à Covid-19 pelo governo do estado de são paulo: dificuldades e aprendizados

Abstract

This study aimed to identify and interpret the difficulties and lessons learned from the IdeiaGov Artificial Intelligence Imaging Challenge, launched in partnership with the Hospital das Clínicas of the Faculty of Medicine of the University of São Paulo, among other actors, to face the Covid-19 pandemic and which relied on startup solutions to create an artificial intelligence algorithm capable to identifying Covid-19 in imaging exams, at a critical moment when the health crisis was plaguing society and when there were no Covid-19 tests on the market. This is a qualitative-exploratory research, which had two fundamental stages, the first being a documentary research for historical and methodological understanding of the IdeaGov Innovation in Government Program and the second, which included in-depth interviews with actors from the artificial intelligence in imaging. The methodology applied for data reading was content analysis. The research identified 18 difficulties, based on 39 reports and 23 lessons learned, based on 38 corresponding reports. By conducting this research, it was expected to contribute to new and future open innovation programs in governments and that these can provide improvements in the delivery of health services to the population.