Optimization of surgery scheduling problems based on prescriptive analytics

• Autor(a) principal: Lopes, João
• Data de Publicação: 2023
• Outros Autores: Vieira, Gonçalo, Veloso, Rita, Ferreira, Susana, Salazar, Maria, Santos, Manuel
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/1822/89771
• topic: Prescriptive analytics; Surgery scheduling problems; Engenharia e Tecnologia::Outras Engenharias e Tecnologias; Saúde de qualidade

Surgery scheduling plays a crucial role in modern healthcare systems, ensuring efficient use of resources, minimising patient waiting times and improving organisations’ operational performance. Additionally, healthcare faces enormous challenges, with a general modernisation of all clinical and administrative processes expected, requiring organisations to keep up with the latest advances in Information Technology. The scheduling of surgeries is a crucial sector for the good functioning of hospitals, and the management of waiting lists is directly related to this process, which has seen the COVID-19 pandemic cause a significant increase in waiting times in some specialities. Surgery scheduling is considered a highly complex problem, influenced by numerous factors such as resource availability, operating shifts, patient priorities and scheduling restrictions, putting significant challenges to healthcare providers. In this research, in collaboration with one of the leading hospitals in P ortugal, the Centro Hospitalar Universitário de Santo António (CHUdSA), we propose an approach based on Prescriptive Analytics, using optimisation algorithms to evaluate their performance in the management of the operating room. The results allow identifying the feasibility of this approach, taking into account the number of surgeries to be scheduled and surgical spaces in a time perspective, prevailing the priority of each surgery in the waiting list.