An optimization based on simulation approach to the patient admission scheduling problem using a linear programing algorithm

• Tipo: Artigo em Revista Científica Internacional
• Data: 2014

Autores

C. Granja (Autor) FEUP; B. Almada Lobo (Autor) FEUP; F. Janela (Autor) Outra; J. Seabra (Autor) Outra; A. Mendes (Autor) FEUP

Revista

Título: Journal of Biomedical Informatics

Vol. 52

Páginas: 427-437

ISSN: 1532-0464

Editora: Elsevier

Indexação

ISI Web of Knowledge - 16 Citações

ISI Web of Science

Scopus - 22 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas > Engenharia

Projetos Associados

UI0511 - PROJECTO ESTRATÉGICO - UI 511 - 2013-2014

Outras Informações

ID Authenticus: P-00A-2H8

DOI: 10.1016/j.jbi.2014.08.007

Abstract (EN): Background: As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Method: Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. Results: The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11