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Balancing patient demand and hospital resources: a newsvendor-based approach to bed and nurse optimization
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| 1.62 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
Using a two-period Newsvendor-based model, this study examines a data-driven strategy
for optimizing nurse staffing and bed allocation in private hospitals. Leveraging a
framework initially aimed at optimizing airline seat inventory, the model incorporates
probabilistic demand estimation and overbooking strategies to balance patient demand
with hospital resources. Despite limitations in assumptions, such as linear cost structures
and parameter estimation, the analysis based on data from a cardiac unit in India reveals
valuable insights for hospital management, demonstrating the model’s potential to
improve revenue and minimize costs associated with over and understaffing.
Descrição
Palavras-chave
Newsvendor problem Cost optimization Nurse staffing Data-driven Hospital management Private healthcare