Previsão da ocupação hospitalar usando análise multivariada de séries temporais

Abstract

Effective management of the flow of hospitalized patients is crucial to ensure the balance between installed capacity and demand for health services, ensuring the safety of care and the financial sustainability of the hospital. Aligning the interests of various involved groups, including entrepreneurs and society, proved crucial for maximizing hospital infrastructure use and offering patients high-quality and safe services. This study used key indicators, such as average length of stay and bed turnover, to develop a predictive model to the hospital bed occupancy rate. A Vector Autoregressive (VAR) model with a trend was applied, assessing the impact of patient flow variables on the hospital occupancy rate. The results provided valuable information for strategic and operational decision-making in hospital management, demonstrating the usefulness of predictive models in improving service efficiency and quality.