Modelo de gestión de pronóstico de la demanda de medicamentos para la atención de enfermedades de interés en salud pública

dc.contributor.advisorOsorio Ramírez, Carlosspa
dc.contributor.authorHernández Acevedo, Laura Bibianaspa
dc.contributor.refereeSuarez Moreno, Juan Davidspa
dc.contributor.refereeVanegas Escamilla, Egdda Patriciaspa
dc.contributor.researchgroupSociedad, Economia y Productividad -spa
dc.date.accessioned2024-06-17T19:51:20Z
dc.date.available2024-06-17T19:51:20Z
dc.date.issued2023
dc.descriptionilustraciones, diagramasspa
dc.description.abstractLa efectividad de los programas destinados a mitigar eventos de interés en salud pública radica en la disponibilidad a nivel nacional de los medicamentos esenciales. En su papel como rector y administrador, el Estado tiene dentro de sus responsabilidades asegurar la accesibilidad de estos medicamentos, con el fin de reducir las disparidades en la salud y mejorar las condiciones de vida. Con el propósito de garantizar esta disponibilidad, se ha diseñado un modelo de gestión para el pronóstico de la demanda de medicamentos desde los entes territoriales. Para ello, se realizó una caracterización exhaustiva de la cadena de suministro de medicamentos, permitiendo comprender los flujos de información y medicamentos, así como identificar prácticas exitosas y desafíos. Adicionalmente, se aplicó un modelo ARIMA (1,1,0) para pronosticar la demanda de medicamentos destinados a la atención de la Malaria P. Faciparum en el departamento del Chocó. Este modelo fue ajustado y verificado mediante la metodología Box-Jenkins, proporcionando un pronóstico para el año 2022 con un error MAPE del 19.2%. En última instancia, se desarrolló un modelo integral de gestión de la demanda, compuesto por dos elementos clave: el primero implementa el concepto de planificación de ventas y operaciones (S&OP), el cual promueve la colaboración interna a través del pronóstico de consenso y el intercambio de información, mientras que el segundo extiende esta colaboración a lo largo de toda la cadena de suministro mediante planificación, previsión y reposición colaborativa (CPFR). Este enfoque integral busca optimizar la gestión de la demanda, fortaleciendo la colaboración tanto interna como externa para asegurar la disponibilidad de medicamentos a nivel nacional. (Texto tomado de la fuente).spa
dc.description.abstractThe effectiveness of programs aimed at mitigating public health events depends on the national availability of essential medicines. In its role as regulator and administrator, the State has among its responsibilities to ensure access to these medicines, in order to reduce health disparities and improve living conditions. With the purpose of ensuring this availability a management model has been designed for forecasting medicine demand from territorial entities. To achieve this, a comprehensive characterization of the medicine supply chain was carried out, allowing for an understanding of information and medicine flows, as well as the identification of successful practices and challenges. Additionally, an ARIMA (1,1,0) model was applied to forecast the demand for medications intended for the treatment of Malaria P. Faciparum in the department of Chocó. This model was adjusted and verified using the Box-Jenkins methodology, providing a forecast for the year 2022 with a MAPE of 19.2%. Ultimately, a comprehensive demand management model was developed, composed of two key elements: the first implements the concept of sales and operations planning (S&OP), which promotes internal collaboration through consensus forecasting and information exchange, while the second extends this collaboration throughout the entire supply chain through collaborative planning, forecasting and replenishment (CPFR). This comprehensive approach aims to optimize demand management, strengthening both internal and external collaboration to ensure the availability of medicines at the nationwide.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Ingeniería Industrialspa
dc.description.researchareaInvestigación de operaciones – Logísticaspa
dc.format.extentxviii, 212 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/86245
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Industrialspa
dc.relation.indexedBiremespa
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dc.relation.referencesWHO. 2017. “Access to medicines: making market forces serve the poor”. WHO 9. Recuperado el 29 de junio de 2019 (https://www.who.int/publications/10-year-review/medicines/en/).spa
dc.relation.referencesWHO. 2018a. Roadmap for access 2019-2023. Comprehensive support for access to medicines and vaccines.spa
dc.relation.referencesWHO. 2018b. “The world health report: health systems financing: the path to universal coverage. Geneva: WHO; 2010”. Contract No.: WHO Report ISBN 978(92):4.spa
dc.relation.referencesWing, Larry, y Glynn Perry. 2001. “Toward twenty-first-century pharmaceutical sales and operations planning”. Pharmaceutical Technology 20.spa
dc.relation.referencesYu, Kangkang, Jack Cadeaux, y Hua Song. 2017. “Flexibility and quality in logistics and relationships”. Industrial Marketing Management 62:211–25. doi: 10.1016/j.indmarman.2016.09.004.spa
dc.relation.referencesZhang, G. Peter, y Min Qi. 2005. “Neural network forecasting for seasonal and trend time series”. European journal of operational research 160(2):501–14.spa
dc.relation.referencesZhu, X., A. Ninh, H. Zhao, y Z. Liu. 2021. “Demand Forecasting with Supply-Chain Information and Machine Learning: Evidence in the Pharmaceutical Industry”. Production and Operations Management 30(9):3231–52. doi: 10.1111/poms.13426.spa
dc.relation.referencesZinn, Walter, y Peter C. Liu. 2001. “Customer response to retail stockouts”. Journal of Business Logistics 22(1):50–53.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.ddc610 - Medicina y salud::614 - Medicina Forense; incidencia de lesiones, heridas, enfermedades; medicina preventiva públicaspa
dc.subject.decsAccesibilidad a los Servicios de Salud/organización & administraciónspa
dc.subject.decsHealth Services Accessibility/organization & administrationeng
dc.subject.decsAdministración en Salud Públicaspa
dc.subject.decsPublic Health Administrationeng
dc.subject.decsMedicamentos para Atención Básicaspa
dc.subject.decsDrugs for Primary Health Careeng
dc.subject.proposalSistema de salud en Colombiaspa
dc.subject.proposalGestión de demandaspa
dc.subject.proposalPronóstico de demandaspa
dc.subject.proposalARIMAeng
dc.subject.proposalS&OPeng
dc.subject.proposalCPFReng
dc.subject.proposalDemand managementeng
dc.subject.proposalForecastingeng
dc.subject.proposalHealth system in Colombiaeng
dc.titleModelo de gestión de pronóstico de la demanda de medicamentos para la atención de enfermedades de interés en salud públicaspa
dc.title.translatedA model for medicines demand management for the treatment of diseases of public health interesteng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
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dc.type.driverinfo:eu-repo/semantics/masterThesisspa
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dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
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dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentMaestrosspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.awardtitleTecnologías en gestión de demanda y operación logística para la red de atención en salud en la región costera del departamento de Chocó. Un enfoque desde el beneficiario hacia la institucionalidadspa
oaire.fundernameMinCienciasspa

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