Predicting medicine demand in hospitals through stochastic approaches
ilustraciones
- Autores:
-
Vélez Cárdenas, Daniel Fernando
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/83248
- Palabra clave:
- 620 - Ingeniería y operaciones afines
Medicamentos
Provisión y distribición
supply & distribution
Gestión de inventarios
Predicción de la demanda
Farmacia hospitalaria
Modelos estocásticos
Cadena de Markov
Inventory management
Demand forecasting
Hospital pharmacy
Stochastic models
Markov chain
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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Predicting medicine demand in hospitals through stochastic approaches |
| dc.title.translated.spa.fl_str_mv |
Predicción de la demanda de medicamentos en hospitales a través de enfoques estocásticos |
| title |
Predicting medicine demand in hospitals through stochastic approaches |
| spellingShingle |
Predicting medicine demand in hospitals through stochastic approaches 620 - Ingeniería y operaciones afines Medicamentos Provisión y distribición supply & distribution Gestión de inventarios Predicción de la demanda Farmacia hospitalaria Modelos estocásticos Cadena de Markov Inventory management Demand forecasting Hospital pharmacy Stochastic models Markov chain |
| title_short |
Predicting medicine demand in hospitals through stochastic approaches |
| title_full |
Predicting medicine demand in hospitals through stochastic approaches |
| title_fullStr |
Predicting medicine demand in hospitals through stochastic approaches |
| title_full_unstemmed |
Predicting medicine demand in hospitals through stochastic approaches |
| title_sort |
Predicting medicine demand in hospitals through stochastic approaches |
| dc.creator.fl_str_mv |
Vélez Cárdenas, Daniel Fernando |
| dc.contributor.advisor.none.fl_str_mv |
Rocha González, Jair Eduardo Yahouni, Zakaria |
| dc.contributor.author.none.fl_str_mv |
Vélez Cárdenas, Daniel Fernando |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines |
| topic |
620 - Ingeniería y operaciones afines Medicamentos Provisión y distribición supply & distribution Gestión de inventarios Predicción de la demanda Farmacia hospitalaria Modelos estocásticos Cadena de Markov Inventory management Demand forecasting Hospital pharmacy Stochastic models Markov chain |
| dc.subject.decs.spa.fl_str_mv |
Medicamentos Provisión y distribición |
| dc.subject.decs.eng.fl_str_mv |
supply & distribution |
| dc.subject.proposal.spa.fl_str_mv |
Gestión de inventarios Predicción de la demanda Farmacia hospitalaria Modelos estocásticos Cadena de Markov |
| dc.subject.proposal.eng.fl_str_mv |
Inventory management Demand forecasting Hospital pharmacy Stochastic models Markov chain |
| description |
ilustraciones |
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2023 |
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2023-02-02T16:56:45Z |
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2023-02-02T16:56:45Z |
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2023-01-31 |
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Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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eng |
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eng |
| dc.relation.references.spa.fl_str_mv |
Abdulsalam, Y., Gopalakrishnan, M., Maltz, A., & Schneller, E. (2018). The impact of physician-hospital integration on hospital supply management. Journal of Operations Management, 57, 11–22. https://doi.org/10.1016/j.jom.2018.01.001 Addis, B., Carello, G., Grosso, A., Lanzarone, E., Mattia, S., & Tànfani, E. (2015). Handling uncertainty in health care management using the cardinality-constrained approach: Advantages and remarks. Operations Research for Health Care, 4, 1–4. https://doi.org/10.1016/j.orhc.2014.10.001 Anderson, T., & Goodman, L. (1957). Statistical Inference About Markov Chains. The Annals of Mathematical Statistics, 28. https://doi.org/10.1214/aoms/1177707039 Aptel, O., & Pourjalali, H. (2001). Improving activities and decreasing costs of logistics in hospitals: A comparison of U.S. and French hospitals. The International Journal of Accounting, 36(1), 65–90. https://doi.org/10.1016/S0020-7063(01)00086-3 Attanayake, N., Kashef, R. F., & Andrea, T. (2014). A simulation model for a continuous review inventory policy for healthcare systems. 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 1–6. https://doi.org/10.1109/CCECE.2014.6901005 de Vries, J. (2011). The shaping of inventory systems in health services: A stakeholder analysis. International Journal of Production Economics, 133(1), 60–69. https://doi.org/10.1016/j.ijpe.2009.10.029 Du, H., Zhao, Z., & Xue, H. (2020). ARIMA-M: A New Model for Daily Water Consumption Prediction Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction. MDPI Water, 12(3), 760. https://doi.org/10.3390/w12030760 Gebicki, M., Mooney, E., Chen, S.-J., & Mazur, L. M. (2014). Evaluation of hospital medication inventory policies. Health Care Management Science, 17(3), 215–229. https://doi.org/10.1007/s10729-013-9251-1 Goltsos, T. E., Syntetos, A. A., Glock, C. H., & Ioannou, G. (2021). Inventory – forecasting: Mind the gap. European Journal of Operational Research, S0377221721006500. https://doi.org/10.1016/j.ejor.2021.07.040 Hermosilla, A., Carmagnola, R., Sauer, C., Redondo, E., & Centurion, L. (2020). Demand forecasts for chronic cardiovascular diseases medication based on Markov chains. 5(2), 6. Koala, D., Yahouni, Z., Alpan, G., & Si Mohand, D. (2022). Correlation Analysis of Factors Impacting Health Product Consumption in French Hospitals. 10th IFAC Conference on Manufacturing Modelling, Management and Control: MIM. Kocer, U. U. (n.d.). FORECASTING INTERMITTENT DEMAND BY MARKOV CHAIN MODEL. International Journal of Innovative Computing, Information and Control, 13. Landry, S., & Philippe, R. (2004). How Logistics Can Service Healthcare. Supply Chain Forum: An International Journal, 5(2), 24–30. https://doi.org/10.1080/16258312.2004.11517130 Lopez Ramirez, A. J., Jurado, I., Fernandez Garcia, M. I., Isla Tejera, B., Del Prado Llergo, J. R., & Maestre Torreblanca, J. M. (2014). Optimization of the demand estimation in hospital pharmacy. Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA), 1–6. https://doi.org/10.1109/ETFA.2014.7005057 Pan, Z. X. (Thomas), & Pokharel, S. (2007). Logistics in hospitals: A case study of some Singapore hospitals. Leadership in Health Services, 20(3), 195–207. https://doi.org/10.1108/17511870710764041 Pokharel, S. (2005). Perception on information and communication technology perspectives in logistics: A study of transportation and warehouses sectors in Singapore. Journal of Enterprise Information Management, 18(2), 136–149. https://doi.org/10.1108/17410390510579882 Polanecký, L., & Lukoszová, X. (2016). Inventory Management Theory: A Critical Review. Littera Scripta, 9(2), 11. Roni, M. S., Eksioglu, S. D., Jin, M., & Mamun, S. (2016). A hybrid inventory policy with split delivery under regular and surge demand. International Journal of Production Economics, 172, 126–136. https://doi.org/10.1016/j.ijpe.2015.11.015 Saha, E., & Ray, P. K. (2018). Inventory Management and Analysis of Pharmaceuticals in a Healthcare System. In P. K. Ray & J. Maiti (Eds.), Healthcare Systems Management: Methodologies and Applications: 21st Century Perspectives of Asia (pp. 71–95). Springer. https://doi.org/10.1007/978-981-10-5631-4_7 Saha, E., & Ray, P. K. (2019a). Patient condition-based medicine inventory management in healthcare systems. http://www.tandfonline.com/doi/epub/10.1080/24725579.2019.1638850?needAccess=true Saha, E., & Ray, P. K. (2019b). Modelling and analysis of inventory management systems in healthcare: A review and reflections. Computers & Industrial Engineering, 137, 106051. https://doi.org/10.1016/j.cie.2019.106051 Varghese, V., Rossetti, M., Pohl, E., Apras, S., & Marek, D. (2012). Applying Actual Usage Inventory Management Best Practice in a Health Care Supply Chain. International Journal of Supply Chain Management, 1(2), 10. Vila-Parrish, A. R., Ivy, J. S., & King, R. E. (2008). A simulation-based approach for inventory modeling of perishable pharmaceuticals. 2008 Winter Simulation Conference, 1532–1538. https://doi.org/10.1109/WSC.2008.4736234 Villegas, M. A., Pedregal, D. J., & Trapero, J. R. (2018). A support vector machine for model selection in demand forecasting applications. Computers & Industrial Engineering, 121, 1–7. https://doi.org/10.1016/j.cie.2018.04.042 Volland, J., Fügener, A., Schoenfelder, J., & Brunner, J. O. (2017). Material logistics in hospitals: A literature review. Omega, 69, 82–101. https://doi.org/10.1016/j.omega.2016.08.004 |
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xviii, 40 páginas |
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application/pdf |
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Universidad Nacional de Colombia |
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Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Industrial |
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Facultad de Ingeniería |
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Bogotá - Colombia |
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Universidad Nacional de Colombia - Sede Bogotá |
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Universidad Nacional de Colombia |
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Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Rocha González, Jair Eduardo4f8345ff1cc463b6c9891a44d68262e8Yahouni, Zakaria2953de1c620c41f4bb5480cd9d966ec0Vélez Cárdenas, Daniel Fernando15f9b4d37b69aba3909575dba732c3d42023-02-02T16:56:45Z2023-02-02T16:56:45Z2023-01-31https://repositorio.unal.edu.co/handle/unal/83248Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesHoy en día, el sector sanitario está cambiando rápidamente. Los hospitales se enfrentan a presupuestos cada vez más limitados y costos elevados. Las actividades logísticas de los hospitales en Francia (gestión de existencias, entrega, etc.) representan uno de los componentes de mayor costo. Los costos logísticos pueden reducirse mediante un sistema optimizado de gestión de inventarios. La optimización del inventario depende en gran medida de la precisión de la predicción de la demanda de medicamentos. El primer objetivo consiste en realizar un estado del arte de los métodos existentes para predecir la demanda de medicamentos en los centros sanitarios. Muchos factores influyen en esta demanda, como su estacionalidad, el tamaño y la ubicación del hospital. En consecuencia, un método estocástico puede ser relevante para captar las fluctuaciones de la demanda. Un segundo objetivo es utilizar los datos históricos de un hospital de Francia para predecir el consumo de medicamentos mediante una cadena de Markov. Se propone un análisis de los resultados experimentales para evaluar la eficacia del método. El resultado podría contribuir a la gestión y el dimensionamiento de los inventarios hospitalarios. (Texto tomado de la fuente)Nowadays, the healthcare sector is rapidly changing. The hospitals are facing limited budgets and high costs. The logistics activities of the hospitals in France (stock management, delivery, etc.) represent one of the highest cost components. The logistic costs can be reduced through an optimized inventory management system. The inventory optimization is strongly dependent on the accuracy of the demand prediction of medicines. The first objective consists of making a state of the art of existing methods for predicting medicines demand in healthcare facilities. Many factors influence this demand, such as seasonality, hospital size and location, etc. As a consequence, a stochastic method can be relevant to capture the demand fluctuations. A second objective is to use the historical data of one hospital in France to predict the consumption of medicines using a Markov chain. An analysis of the experimental results is proposed to assess the effectiveness of the method. The result could contribute to the management and dimensioning of hospital inventories.Esta investigación será publicada para alcanzar el título de Master en ingeniería en la Universidad Institut polytechnique de Grenoble dentro del convenio de doble titulación que mantiene con la Universidad Nacional de Colombia, Facultad de Ingeniería, Sede Bogotá y ahora se publica en versión idéntica para satisfacer las condiciones de grado en Colombia y para su difusión en el repositorio institucional.MaestríaMagister en Ingeniería IndustrialGestión de operacionesxviii, 40 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería IndustrialFacultad de IngenieríaBogotá - ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afinesMedicamentosProvisión y distribiciónsupply & distributionGestión de inventariosPredicción de la demandaFarmacia hospitalariaModelos estocásticosCadena de MarkovInventory managementDemand forecastingHospital pharmacyStochastic modelsMarkov chainPredicting medicine demand in hospitals through stochastic approachesPredicción de la demanda de medicamentos en hospitales a través de enfoques estocásticosTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAbdulsalam, Y., Gopalakrishnan, M., Maltz, A., & Schneller, E. (2018). The impact of physician-hospital integration on hospital supply management. Journal of Operations Management, 57, 11–22. https://doi.org/10.1016/j.jom.2018.01.001Addis, B., Carello, G., Grosso, A., Lanzarone, E., Mattia, S., & Tànfani, E. (2015). Handling uncertainty in health care management using the cardinality-constrained approach: Advantages and remarks. Operations Research for Health Care, 4, 1–4. https://doi.org/10.1016/j.orhc.2014.10.001Anderson, T., & Goodman, L. (1957). Statistical Inference About Markov Chains. The Annals of Mathematical Statistics, 28. https://doi.org/10.1214/aoms/1177707039Aptel, O., & Pourjalali, H. (2001). Improving activities and decreasing costs of logistics in hospitals: A comparison of U.S. and French hospitals. The International Journal of Accounting, 36(1), 65–90. https://doi.org/10.1016/S0020-7063(01)00086-3Attanayake, N., Kashef, R. F., & Andrea, T. (2014). A simulation model for a continuous review inventory policy for healthcare systems. 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 1–6. https://doi.org/10.1109/CCECE.2014.6901005de Vries, J. (2011). The shaping of inventory systems in health services: A stakeholder analysis. International Journal of Production Economics, 133(1), 60–69. https://doi.org/10.1016/j.ijpe.2009.10.029Du, H., Zhao, Z., & Xue, H. (2020). ARIMA-M: A New Model for Daily Water Consumption Prediction Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction. MDPI Water, 12(3), 760. https://doi.org/10.3390/w12030760Gebicki, M., Mooney, E., Chen, S.-J., & Mazur, L. M. (2014). Evaluation of hospital medication inventory policies. Health Care Management Science, 17(3), 215–229. https://doi.org/10.1007/s10729-013-9251-1Goltsos, T. E., Syntetos, A. A., Glock, C. H., & Ioannou, G. (2021). Inventory – forecasting: Mind the gap. European Journal of Operational Research, S0377221721006500. https://doi.org/10.1016/j.ejor.2021.07.040Hermosilla, A., Carmagnola, R., Sauer, C., Redondo, E., & Centurion, L. (2020). Demand forecasts for chronic cardiovascular diseases medication based on Markov chains. 5(2), 6.Koala, D., Yahouni, Z., Alpan, G., & Si Mohand, D. (2022). Correlation Analysis of Factors Impacting Health Product Consumption in French Hospitals. 10th IFAC Conference on Manufacturing Modelling, Management and Control: MIM.Kocer, U. U. (n.d.). FORECASTING INTERMITTENT DEMAND BY MARKOV CHAIN MODEL. International Journal of Innovative Computing, Information and Control, 13.Landry, S., & Philippe, R. (2004). How Logistics Can Service Healthcare. Supply Chain Forum: An International Journal, 5(2), 24–30. https://doi.org/10.1080/16258312.2004.11517130Lopez Ramirez, A. J., Jurado, I., Fernandez Garcia, M. I., Isla Tejera, B., Del Prado Llergo, J. R., & Maestre Torreblanca, J. M. (2014). Optimization of the demand estimation in hospital pharmacy. Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA), 1–6. https://doi.org/10.1109/ETFA.2014.7005057Pan, Z. X. (Thomas), & Pokharel, S. (2007). Logistics in hospitals: A case study of some Singapore hospitals. Leadership in Health Services, 20(3), 195–207. https://doi.org/10.1108/17511870710764041Pokharel, S. (2005). Perception on information and communication technology perspectives in logistics: A study of transportation and warehouses sectors in Singapore. Journal of Enterprise Information Management, 18(2), 136–149. https://doi.org/10.1108/17410390510579882Polanecký, L., & Lukoszová, X. (2016). Inventory Management Theory: A Critical Review. Littera Scripta, 9(2), 11.Roni, M. S., Eksioglu, S. D., Jin, M., & Mamun, S. (2016). A hybrid inventory policy with split delivery under regular and surge demand. International Journal of Production Economics, 172, 126–136. https://doi.org/10.1016/j.ijpe.2015.11.015Saha, E., & Ray, P. K. (2018). Inventory Management and Analysis of Pharmaceuticals in a Healthcare System. In P. K. Ray & J. Maiti (Eds.), Healthcare Systems Management: Methodologies and Applications: 21st Century Perspectives of Asia (pp. 71–95). Springer. https://doi.org/10.1007/978-981-10-5631-4_7Saha, E., & Ray, P. K. (2019a). Patient condition-based medicine inventory management in healthcare systems. http://www.tandfonline.com/doi/epub/10.1080/24725579.2019.1638850?needAccess=trueSaha, E., & Ray, P. K. (2019b). Modelling and analysis of inventory management systems in healthcare: A review and reflections. Computers & Industrial Engineering, 137, 106051. https://doi.org/10.1016/j.cie.2019.106051Varghese, V., Rossetti, M., Pohl, E., Apras, S., & Marek, D. (2012). Applying Actual Usage Inventory Management Best Practice in a Health Care Supply Chain. International Journal of Supply Chain Management, 1(2), 10.Vila-Parrish, A. R., Ivy, J. S., & King, R. E. (2008). A simulation-based approach for inventory modeling of perishable pharmaceuticals. 2008 Winter Simulation Conference, 1532–1538. https://doi.org/10.1109/WSC.2008.4736234Villegas, M. A., Pedregal, D. J., & Trapero, J. R. (2018). A support vector machine for model selection in demand forecasting applications. Computers & Industrial Engineering, 121, 1–7. https://doi.org/10.1016/j.cie.2018.04.042Volland, J., Fügener, A., Schoenfelder, J., & Brunner, J. O. (2017). Material logistics in hospitals: A literature review. Omega, 69, 82–101. https://doi.org/10.1016/j.omega.2016.08.004EstudiantesInvestigadoresMaestrosLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83248/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1121897186.2022.pdf1121897186.2022.pdfTesis de Maestría en Ingeniería Industrialapplication/pdf777794https://repositorio.unal.edu.co/bitstream/unal/83248/2/1121897186.2022.pdf070be37dad33d267842aebc1b19f5b9cMD52THUMBNAIL1121897186.2022.pdf.jpg1121897186.2022.pdf.jpgGenerated Thumbnailimage/jpeg4353https://repositorio.unal.edu.co/bitstream/unal/83248/3/1121897186.2022.pdf.jpg200e4f53f49339a8fb6b5133503c810cMD53unal/83248oai:repositorio.unal.edu.co:unal/832482023-08-14 23:04:59.849Repositorio Institucional Universidad Nacional de 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