Abstract
To analyze the influence of the COVID-19 pandemic on the productivity of general teaching hospitals in Brazil, by region and legal entity, and to propose parameters of care. This was an observational study by means of mathematical modeling with data envelopment analysis and Malmquist index, using data on inputs and healthcare output before (2019) and during (2021) the pandemic. A total of 149 general teaching hospitals were analyzed, 32 of which were considered efficient. There was a decrease in productivity across all regions and legal entity. To bring all inefficient hospitals to the efficiency frontier generated by the model, there is a need to increase output by 2,205,856 (96.5%) hospitalizations and 872,264 (107.4%) surgeries. The decline in hospital productivity resulted from the social commitment of hospitals during the pandemic, with a change in the care delivery pattern. The mathematical model used allows for the generation of parameters to facilitate the efficient recovery of care services after the end of public health emergency, and can be applied to hospital planning. The COVID-19 pandemic led to a reduction in productivity of general teaching hospitals in Brazil across all regions and in all legal entity types. In order to recover, these hospitals will need to increase their average hospitalizations by 96.5% and surgeries by 107.4%. The study presents a methodology that can be adapted and replicated in the management of healthcare services in the country, by defining an efficiency score and calculating the parameters, in a scenario of care recovery following the end of the public health emergency. Additional qualitative analysis and application of DEA- Malmquist in subsequent years will validate dynamic planning, which considers multiple fluctuations and the influence of new factors and contexts that impact productivity (such as the pandemic).
Published Version
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