Published Jun 17, 2021



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Francisco Andrés Chuchoque-Urbina, MSc https://orcid.org/0000-0003-2982-5906

Martha Patricia Caro-Gutierrez, PhD https://orcid.org/0000-0003-2403-3838

Carlos Eduardo Montoya-Casa, PhD https://orcid.org/0000-0002-6472-8485

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Abstract

Objective: Designing a CPFR (collaborative planning forecasting and replenishment) model for the delivery of diabetes and arterial hypertension medicines from a health insurance company (EPS) to a healthcare provider (IPS) and comparing the performance of this collaborative chain to that of the traditional one through their corresponding supply chain costs. Methodology: A series of collaboration agreements involved in joint planning were established according to the designed CPFR model. This allowed (i) raising the levels of interaction between the health insurance company, the healthcare provider, the supplying pharmaceutical laboratories, and the patients; (ii) determining demand forecasts; (iii) locating distribution centers; and (iv) defining medicine distribution strategies oriented to the minimization of costs along the chain. Subsequently, the main differences between the current operation and CPFR models at the level of structure and decisions were characterized and then evaluated in terms of supply chain costs. Results: The significant impact of the proposed model is demonstrated. The total monthly cost of operating the chain is reduced by 11.2 % on average. Within the proposed innovation, an outstanding place is held by the savings reached in the purchase and distribution of medicines from the laboratory to the distribution centers, and by the customer satisfaction differences, which increased 15.3 % on average during the studied six-month period.

Keywords

CPFR, medicamentos, optimización, cadena de abastecimientoCPFR, Medicine, optimization supply chain

References
[1] “Eurostat Mortality Statistics,” 2012. [Online]. Available: https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=hlth_cd_aperrto&lang=en
[2] Organización Mundial de la Salud (OMS), “Temas de salud: hipertensión,” Oct. 2015. [Online]. Available: http://www.who.int/topics/hypertension/es/. Accessed on: July 15, 2018.
[3] C. Muñoz, “Enfermedad cerebrovascular,” acn.web, 2011. Available: http://www.acnweb.org/guia/g1c12i.pdf
[4] Instituto Mexicano del Seguro Social (IMSS), Diagnóstico y Tratamiento de la Cardiopatía Isquémica Crónica. Ciudad de México: IMSS, 2019. Available: http://www.imss.gob.mx/sites/all/statics/guiasclinicas/000GERCardiopatiaIsquemica.pdf
[5] K. Gallardo, F. Benavides, and R. Rosales, “Costo de la enfermedad crónica no transmisible: la realidad colombiana,” Rev. Cienc. Salud, vol. 14, no. 1, pp. 103–114, 2016. doi: dx.doi.org/10.12804/revsalud14.01.2016.09
[6] W. Stevenson, Operations Management. New York: McGraw-Hill, 2002.
[7] M. Cao, M. Vonderembse, Q. Zhang, and T. S. Ragu-Nathan, “Supply chain collaboration: Conceptualization and instrument development,” Int. J. Prod. Res., vol. 48, no. 22, pp. 6613–6635, 2010. DOI: 10.1080/00207540903349039
[8] J. L. Calderón and F. Lario, “Análisis del modelo SCOR para la gestión de la cadena de suministro,” presented at IX Congr. Ing. Organiz., Gijón, September 8-9, 2005, pp. 1–10. Available: http://www.adingor.es/Documentacion/CIO/cio2005/items/ponencias/41.pdf
[9] J. Rohde, H. Meyr, and M. Wagner, “Die supply chain planning matrix,” PPS Manage., vol. 5, no. 1, pp. 10–15, 2000.
[10] J. Cooke, “VMI: Very mixed impact?,” Logist. Manage. Distrib. R., vol. 37, no. 12, pp. 51–54, 1998.
[11] I. Ribas and R. Companys, “Estado del arte de la planificación colaboritiva en la cadena de suministro: contexto determinista e incierto,” Intangible Capital, vol. 3, no. 3, pp. 91–121, 2017. Available: https://www.intangiblecapital.org/index.php/ic/article/view/30/59
[12] C. A. Hill, G. P. Zhang, and K. E. Miller, “Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation,” Int. Sharing Coordination Make-to-Order Supply Chains, vol. 23, no. 6, pp. 579–598, 2005.
[13] N. Sanders, “An empirical study of the impact of e-business technologies on organizational collaboration and performance,” J. Oper. Manage., vol. 25, no. 6, pp. 1332–1347, 2007. Available: https://doi.org/10.1016/j.jom.2007.01.008
[14] F. Sahin and E. Robinson, “Information sharing and coordination in make-to-order supply chain,” J. Oper. Manage., vol. 23, no. 6, pp. 579–598, 2005. Available: https://doi.org/10.1016/j.jom.2004.08.007
[15] H. Lee, V. Padmanabhan, and S. Whang, “The bullwhip effect in supply chains,” Sloan Manage. Rev., vol. 38, no. 1, pp. 93–102, 1997. Available: https://sloanreview.mit.edu/wp-content/uploads/1997/04/633ecdb037.pdf
[16] Q. Gu, T. Jitpaipoon, and J. Yang, “The impact of information integration on financial performance: A knowledge-based view,” Int. J. Prod. Econ., vol. 191, no. 1, pp. 221–232, 2017. Available: https://doi.org/10.1016/j.ijpe.2017.06.005
[17] G. Fliedner, “CPFR: An emerging supply chain tool,” Ind. Manage. Data Syst., vol. 103, no. 1, pp. 14–21, 2003. doi: 10.1108/02635570310456850
[18] T. Chang, H. Pu, W. Lee, and Y. Lin,“A study of an augmented CPFR model for the 3C retail industry,” Supply Chain Manag. Int. J., vol. 12, no. 3, pp. 200–209, 2007. doi: 10.1108/13598540710742518
[19] X. Du, S. Leung, J. Zhang, and K. Lai, “Procurement of agricultural products using the CPFR approach,” Supply Chain Manage. Int. J., vol. 14, no. 4, pp. 253–258, 2009. Available: https://doi.org/10.1108/13598540910970081
[20] J. Karolefsky, “Collaborating across the supply chain,” Food Logist. Retailtech, vol. 3, no. 1, pp. 24–34, 2001.
[21] R. Lin and P. Ho, “The study of CPFR implementation model in medical SCM of Taiwan,” Prod. Plann. Control, vol. 25, no. 3, pp. 260–271, 2014. doi: 10.1080/09537287.2012.673646
[22] F. Panahifar, C. Heavey, P. J. Byrne, and H. Fazlollahtabar, “A framework for collaborative planning, forecasting and replenishment (CPFR) state of the art,” J. Enterprise Inf. Manage., vol. 28, no. 6, pp. 838–871, 2015. doi: 10.1108/JEIM-09-2014-0092
[23] Ministerio de Salud y Protección Social, “Encuesta de evaluación de los servicios de la EPS 2017,” Ministerio de Salud y Protección Social, 2017. Available: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/CA/Informe-encuesta-satisfaccion-eps-2017.pdf
[24] Ministerio de Salud y Protección Social, May 17, 2013, “Resolución 1604 de 2013, por la cual se reglamenta el artículo 131 del Decreto Ley 019 de 2012 y se dictan otras disposiciones”. Available: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/DIJ/resolucion-1604-de-2013.pdf
[25] Consultor Salud, “Resultados encuestas mipres-medicamentos no pos no están siendo entregados,” 2017 [Online]. Available: https://consultorsalud.com/resultados-encuesta-mipres-medicamentos-no-pos-no-estan-siendo-entregados/
[26] A. Ruiz, “Factores claves en la planeación de demanda en el sector farmacéutico,” 2014 [Online]. Available: https://repository.unimilitar.edu.co/bitstream/handle/10654/11584/ANDREA %20MILENA %20RUIZ %20RUIZ.pdf;jsessionid=A203263E9B567BBBB9BDC1F3C97E838F?sequence=1. Accessed on: Jun. 6, 2019.
[27] Organización Panamericana de la Salud and Ministerio de Salud y Protección Social, “Resúmenes de política: intervenciones poblacionales en factores de riesgo de enfermedades cronicas no transmisibles,” Ministerio de Salud y Protección Social, 2015. Available: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/PP/ENT/intervenciones-poblacionales-factores-riesgo-enfermedades-no-transmisibles.PDF
[28] Ministerio de Salud y Protección Social, “SABE Colombia 2015: Estudio Nacional de Salud, Bienestar y Envejecimiento,” Ministerio de Salud y Protección Social, 2016. Available: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/ED/GCFI/Resumen-Ejecutivo-Encuesta-SABE.pdf
[29] Ministerio de Salud y Protección Social, “Diagnóstico preliminar sobre personas mayores, dependencia y servicios sociales en Colombia,” Ministerio de Salud y Protección Social, 2017. Available: https://www.minsalud.gov.co/proteccionsocial/Documents/Situacion%20Actual%20de%20las%20Personas%20adultas%20mayores.pdf
[30] K. Sari, “Exploring the impacts of radio frecuency identification (RFID) technology on supply chain performance,” Eur. J. Oper. Res., vol. 207, no. 1, pp. 174–183, 2010. doi: 10.1016/j.ejor.2010.04.003
[31] Y. Aviv, “Gaining benefits from joint forecasting and replenishment processes: The case of auto-correlated demand,” Manuf. Serv. Oper. Manage., vol. 4, no. 1, pp. 55–74, 2002. doi: 10.1287/msom.4.1.55.285
[32] C. Ryu, “An investigation of impacts of advanced coordination mechanisms on supply chain performance: consignment, VMI I, VMI II, and CPFR,” Ph.D. dissertation, State University of New York at Buffalo, 2006. http://hdl.handle.net/10477/49189
[33] X. Yuan, L. Shen, and J. Ashayeri, “Dynamic simulation assessment of collaboration strategies to mange demand gap in high-tech product diffusion,” Robot. Comput.-Int. Manuf., vol. 26, no. 6, pp. 647–657, 2010. Available: https://doi.org/10.1016/j.rcim.2010.06.020
[34] C. ReVelle and H. Eiselt, “Location analysis: A synthesis and survey,” Eur. J. Oper. Res., vol. 165, no. 1, pp. 1–19, 2015. Available: https://doi.org/10.1016/j.ejor.2003.11.032
[35] S. Nahmias and T. Olsen, Production and Operations Analysis, 7th Ed. Chicago: Waveland Press, 2015.
[36] S. Basu, M. Sharma, and P. S. Ghosh, “Metaheuristic applications on discrete facility location problems: A survey,” Opsearch, vol. 52, no. 3, pp. 530–561, 2015. doi: 10.1007/s12597-014-0190-5
[37] S. N. Kumar and R. Panneerselvam, “A survey on the vehicle routing problem and its variants,” Intell. Inf. Manage., vol. 4, no. 1, pp. 66–74, 2012. doi: 10.4236/iim.2012.43010
[38] M. Bushuev, A. Guiffrida, M. Jaber, and M. Khan, “A review of inventory lotsizing review papers,” Manage. Res. Rev., vol. 38, no. 3, pp. 283–298, 2015. doi: 10.1108/MRR-09-2013-0204
[39] R. Roldán, R. Basagoiti, and L. Coelho, “A survey on the inventory-routing problem with stochastic lead times and demands,” Comput. Oper. Res., vol. 24, pp. 15–24, 2017. Available: https://doi.org/10.1016/j.jal.2016.11.010
[40] R. Farahani, H. Rashidi-Bajgan, B. Fahimnia, and M. Kaviani, “Location-inventory problem in supply chains: A modelling review,” Int. J. Prod. Res., vol. 53, no. 12, p. 3769–3788, 2015. Available: https://doi.org/10.1080/00207543.2014.988889
[41] Voluntary Interindustry Commerce Standards, Collaborative planning, and replenishment (CPFR): An overview. Lawrenceville: VICS, 2004. Available: https://www.gs1us.org/DesktopModules/Bring2mind/DMX/Download.aspx?Command=Core_Download&EntryId=492
[42] R. Ballou, Logistica: administración de la cadena de suministro. Ciudad de México: Prentice Hall, 2004.
[43] J. Hanke and D. Wichern, Pronósticos en los negocios. Ciudad de México: Pearson Education, 2005.
[44] M. Hamidi, K. Farahmand, and R. Sajjadi, “Modeling a four-layer location-routing problem,” Int. J. Ind. Eng. Comput., vol. 3, no. 1, pp. 43–52, 2012. doi: 10.5267/j.ijiec.2011.08.015
[45] J. Gonzalez-Feliu, “The N-echelon location routing problem: concepts and methods for tactical and operational planning,” Int. T. Oper. Res., vol. 1, no. 1, pp. 1–11, 2009. Available: https://pdfs.semanticscholar.org/4fe0/588e3800e989900e353dd7fc9e6676a2a683.pdf?_ga=2.201196526.1528262281.1592860987-707412495.1592328274
[46] S. Kim and K. Heeyoung, “A new metric of absolute percentage error for intermittent demand,” Int. J. Forecast., vol. 32, no. 3, pp. 669–679, 2016. Available: https://doi.org/10.1016/j.ijforecast.2015.12.003
[47] M. Drexi and M. Scheneider, “A survey of variants and extensions of the location-routing problem,” Eur. J. Oper. Res., vol. 241, no. 1, pp. 283–308, 2015. doi: 10.1016/j.ejor.2014.08.030
How to Cite
Chuchoque-Urbina, F. A., Caro-Gutiérrez, M. P., & Montoya-Casas, C. E. (2021). Design of a CPFR, Location, Inventory and Routing Approach to Diabetes and High Blood Pressure Medicine Supply Network Planning . Ingenieria Y Universidad, 25. https://doi.org/10.11144/Javeriana.iued25.dcli
Section
Special Section: Health Care Engineering

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