Mostrar el registro sencillo del ítem

dc.contributor.authorCaicedo-Rolón, Alvaro Jr
dc.contributor.authorcalixto, nelson javier
dc.contributor.authorMoreno Gamboa, Faustino
dc.date.accessioned2025-03-06T14:02:03Z
dc.date.available2025-03-06T14:02:03Z
dc.date.issued2024-03-29
dc.identifier.urihttps://repositorio.ufps.edu.co/handle/ufps/9175
dc.description.abstractThe emergency department plays a fundamental role in hospitals and critically affects a hospital's overall efficiency. Inadequate staff planning in emergency departments generates high costs, overcrowding, and patient dissatisfaction due to long waiting times, possibly putting the patient's health and life at risk. This research designed two mixed integer linear programming mathematical models. The first determined the optimal number of physicians required per shift and weekday in an adult emergency department to minimize the deviation between available and required capacity. The results of the optimization model would reduce by 16.07 % the required medical office staff per week, from 56 physicians in the current situation to 47, reducing staffing costs without impacting waiting times. Moreover, the overall physician utilization would be 95.01 % compared to 77.79 % in the current situation, indicating an adequate distribution of physicians on each shift of each day according to patient demand. These results contribute to the problem of high medical staff costs and overcrowding without sacrificing timeliness and quality of care. In contrast, the second model that minimized the number of physicians considering capacity constraints would increase the staff by 7.14 % concerning the current situation. This research was based on a model presented in the literature, but the objective function included the deviation variables as unrestricted in sign and a constraint to ensure that they were positive. The first model designed is presented as a tool to support emergency department managers in the medium-term planning of medical staff, ensuring an optimal solution to this problemeng
dc.format.extent8 Páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherEureka physics and engineeringspa
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 International License.eng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.sourcehttps://journal.eu-jr.eu/engineering/article/view/3265spa
dc.titleDesign of a mathematical model for staff planning in an emergency departmenteng
dc.typeArtículo de revistaspa
dcterms.references[1]Nezamoddini, N., Chou, C.-A. (2016). Staff level optimization in emergency department using two-stage stochastic program-ming. In Proceedings of the 2016 Industrial and Systems Engineering Research Conference, ISERC 2016. Anaheim, 1573–1578.spa
dcterms.references[2]Daldoul, D., Nouaouri, I., Bouchriha, H., Allaoui, H. (2015). Optimization on human and material resources in Emergency De-partment. 2015 International Conference on Industrial Engineering and Systems Management (IESM). https://doi.org/10.1109/iesm.2015.7380224spa
dcterms.references[3]Allihaibi, W., Masoud, M., Cholette, M., Burke, J., Karim, A., Liu, S. Q. (2017). Optimising the service of emergency depart-ment in a hospital. International Congress on Modelling and Simulation. https://doi.org/10.36334/modsim.2017.i2.allihaibispa
dcterms.references[4]Ahsan, K. B., Alam, M. R., Morel, D. G., Karim, M. A. (2019). Emergency department resource optimisation for improved perfor-mance: a review. Journal of Industrial Engineering International, 15 (S1), 253–266. https://doi.org/10.1007/s40092-019-00335-xspa
dcterms.references5]Erhard, M., Schoenfelder, J., Fügener, A., Brunner, J. O. (2018). State of the art in physician scheduling. European Journal of Operational Research, 265 (1), 1–18. https://doi.org/10.1016/j.ejor.2017.06.037spa
dcterms.references6]Reveco, C., Weber, R. (2011). Gestion de Capacidad en el Servicio de Urgencia en un Hospital Publico. Revista Ingenier ́ıa de Sistemas, 25, 57–75. Available at: https://www.dii.uchile.cl/~ris/RISXXV/hospital.pdfspa
dcterms.references7]Ganguly, S., Lawrence, S., Prather, M. (2014). Emergency Department Staff Planning to Improve Patient Care and Reduce Costs. Decision Sciences, 45 (1), 115–145. https://doi.org/10.1111/deci.12060spa
dcterms.references[8]Güler, M. G., Geçici, E. (2020). A decision support system for scheduling the shifts of physicians during COVID-19 pandemic. Computers & Industrial Engineering, 150, 106874. https://doi.org/10.1016/j.cie.2020.106874spa
dcterms.references[9]Loso, J. M., Filipp, S. L., Gurka, M. J., Davis, M. K. (2021). Using Queue Theory and Load-Leveling Principles to Identify a Simple Metric for Resource Planning in a Pediatric Emergency Department. Global Pediatric Health, 8, 2333794X2094466. https://doi.org/10.1177/2333794x20944665spa
dcterms.references[10]Savage, D. W., Woolford, D. G., Weaver, B., Wood, D. (2015). Developing emergency department physician shift schedules optimized to meet patient demand. CJEM, 17 (1), 3–12. https://doi.org/10.2310/8000.2013.131224spa
dcterms.references[11]Taha, H. A. (2012). Investigación de operaciones. México: Pearson Education, 2012. Available at: https://www.academia.edu/15590842/Investigaci%C3%B3n_de_Operaciones_9a_ed_Taha_H_2012_spa
dcterms.references[12]Resolución 5596 de 2015. Por la cual se definen los criterios técnicos para el Sistema de Selección y Clasificación de pacientes en los servicios de urgencias ‘Triage’.spa
dcterms.references[13]Bezanson, J., Karpinski, S., Shah, V. B., Edelman, A. (2012). Julia: A fast dynamic language for technical computing. arXiv. https://doi.org/10.48550/arXiv.1209.5145spa
dc.identifier.doi10.21303/2461-4262.2024.003265
dc.publisher.placeHarju maakond, Estoniaspa
dc.relation.citationeditionVol. No.2 (2024)spa
dc.relation.citationendpage177spa
dc.relation.citationissue2. (2024)spa
dc.relation.citationstartpage170spa
dc.relation.citesCaicedo-Rolon, A. J., Cely-Calixto, N. J., & Moreno-Gamboa, F. (2024). Design of a mathematical model for staff planning in an emergency department. EUREKA: Physics and Engineering, (2), 170-177. https://doi.org/10.21303/2461-4262.2024.003265
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.subject.proposalDecision-makingeng
dc.subject.proposalHealthcareeng
dc.subject.proposalOperations researcheng
dc.subject.proposalOptimizationeng
dc.subject.proposalLinear programmingeng
dc.subject.proposalHospitaleng
dc.subject.proposalEmergencyeng
dc.subject.proposalManagementeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

This work is licensed under a Creative Commons Attribution 4.0 International License.
Excepto si se señala otra cosa, la licencia del ítem se describe como This work is licensed under a Creative Commons Attribution 4.0 International License.