Cristin-resultat-ID: 1158679
Sist endret: 26. mai 2016 11:12
NVI-rapporteringsår: 2014
Resultat
Vitenskapelig artikkel
2014

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

Bidragsytere:
  • Conceicao Granja
  • B Almada-Lobo
  • F Janela og
  • A Mendes

Tidsskrift

Journal of Biomedical Informatics
ISSN 1532-0464
e-ISSN 1532-0480
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2014
Publisert online: 2014
Trykket: 2014
Volum: 52
Sider: 427 - 437

Importkilder

Scopus-ID: 2-s2.0-84919658073

Finansiering

  • Norges forskningsråd
    Prosjektkode: 174934

Beskrivelse Beskrivelse

Tittel

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

Sammendrag

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.

Bidragsytere

Conceicao Granja

  • Tilknyttet:
    Forfatter
    ved Universidade do Porto
  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF
  • Tilknyttet:
    Forfatter
    ved Portugal

B Almada-Lobo

  • Tilknyttet:
    Forfatter
    ved Universidade do Porto

F Janela

  • Tilknyttet:
    Forfatter
    ved Portugal

A Mendes

  • Tilknyttet:
    Forfatter
    ved Universidade do Porto
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