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Reduction of the Cycle Time in the Biopsies Diagnosis Through a Simulation Based on the Box Müller Algorithm.
Badilla-Murillo, Félix; Vargas-Vargas, Bernal; Víquez-Acuña, Oscar; García-Sanz-Calcedo, Justo.
Afiliação
  • Badilla-Murillo F; Industrial Production Engineering, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica.
  • Vargas-Vargas B; Industrial Production Engineering, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica.
  • Víquez-Acuña O; Computer Engineering, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica.
  • García-Sanz-Calcedo J; Engineering Projects Area, University de Extremadura, Badajoz, Spain.
Front Public Health ; 10: 809534, 2022.
Article em En | MEDLINE | ID: mdl-35444982
Anatomic pathology services study disease in hospitals on the basis of macroscopic and microscopic examination of organs and tissues. The focus of this research investigation was on improving clinical biopsy diagnosis times through simulation based on the Box-Muller algorithm to reduce the waiting time in the diagnosis of clinical biopsies. The data were provided by a hospital in San José (Costa Rica). They covered 5 years and showed waiting times for a pathological diagnosis that for some biopsies were close to 120 days. The correlation between the main causes identified and the cycle time in the biopsy diagnostic process was defined. A statistical analysis of the variables most representative of the process and of the waiting times was carried out. It followed the DMAIC structure (Define, Measure, Analyse, Improve, Control) for the continuous improvement of processes. Two of the activities of the process were identified as being the main bottlenecks. Their processing times had a normal distribution, for which reason a Box-Muller algorithm was used to generate the simulation model. The results showed that waiting times for a diagnosis can be reduced to 3 days, for a productive capacity of 8 000 biopsies per annum, optimizing the logistics performance of health care.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Atenção à Saúde Tipo de estudo: Diagnostic_studies / Prognostic_studies Aspecto: Determinantes_sociais_saude Idioma: En Revista: Front Public Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Costa Rica País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Atenção à Saúde Tipo de estudo: Diagnostic_studies / Prognostic_studies Aspecto: Determinantes_sociais_saude Idioma: En Revista: Front Public Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Costa Rica País de publicação: Suíça