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

• Type: Article in International Scientific Journal
• Date: 2014

Authors

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

Journal

Title: Journal of Biomedical Informatics

Vol. 52

Pages: 427-437

ISSN: 1532-0464

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 16 Citations

ISI Web of Science

Scopus - 22 Citations

Scientific classification

FOS: Engineering and technology

CORDIS: Technological sciences > Engineering

Associated Projects

UI0511 - PROJECTO ESTRATÉGICO - UI 511 - 2013-2014

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11