Supply Chain In The Hematology Department

Caicedo-Rolon, Alvaro Junior, Luna-Pereira, Henry Orlando, Palacios-Alvarado Wlamyr

Abstract


This article presents literature research on the logistics and supply chain of the metrological service, analyzing and representing the four main links in the supply chain: collection, process, inventory and distribution, for which an analysis of the study methods applied in each of them was performed. The main contribution of this research is to make known each process carried out in the supply chain, its problems and the results obtained from the different study methodologies found.


Keywords


Blood banks; Blood supply chains, Logistics, Blood.

Full Text:

PDF

References


R. Kazemi Matin, M. Azadi, and R. F. Saen, “Measuring the sustainability and resilience of blood supply chains,” Decis. Support Syst., no. June, p. 113629, 2021, doi: 10.1016/j.dss.2021.113629.

J. Banthao and P. Jittamai, “An analysis of alternative blood bank locationswith emergency referral,” Lect. Notes Eng. Comput. Sci., vol. 2, pp. 1304–1308, 2012.

S. Sulaiman, A. A. K. Abdul Hamid, and N. A. Najihah Yusri, “Development of a Blood Bank Management System,” Procedia - Soc. Behav. Sci., vol. 195, pp. 2008–2013, 2015, doi: 10.1016/j.sbspro.2015.06.215.

N. Hazzazi, D. Wijesekera, and S. Hindawi, “Formalizing and Verifying Workflows Used in Blood Banks,” Procedia Technol., vol. 16, pp. 1271–1280, 2014, doi: 10.1016/j.protcy.2014.10.143.

J. Beliën and H. Forcé, “Supply chain management of blood products: A literature review,” Eur. J. Oper. Res., vol. 217, no. 1, pp. 1–16, 2012, doi: 10.1016/j.ejor.2011.05.026.

M. R. G. Samani, S. M. Hosseini-Motlagh, and S. F. Ghannadpour, “A multilateral perspective towards blood network design in an uncertain environment: Methodology and implementation,” Comput. Ind. Eng., vol. 130, no. January, pp. 450–471, 2019, doi: 10.1016/j.cie.2019.02.049.

K. Katsaliaki, N. Mustafee, and S. Kumar, “A game-based approach towards facilitating decision making for perishable products: An example of blood supply chain,” Expert Syst. Appl., vol. 41, no. 9, pp. 4043–4059, 2014, doi: 10.1016/j.eswa.2013.12.038.

B. Hamdan and A. Diabat, “Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation,” Transp. Res. Part E Logist. Transp. Rev., vol. 134, no. August 2019, p. 101764, 2020, doi: 10.1016/j.tre.2019.08.005.

R. A. Cuervo Cruz, J. Martínez Bernal, and J. A. Orjuela-Castro, “Modelos logísticos estocásticos aplicados a la cadena de suministro: una revisión de la literatura,” Ingeniería, vol. 26, no. 3, pp. 334–366, 2022, doi: 10.14483/23448393.16357.

M. Y. N. Attari and E. N. Jami, “Robust stochastic multi-choice goal programming for blood collection and distribution problem with real application,” J. Intell. Fuzzy Syst., vol. 35, no. 2, pp. 2015–2033, 2018, doi: 10.3233/JIFS-17179.

O. S. Silva Filho, M. A. Carvalho, W. Cezarino, R. Silva, and G. Salviano, “Demand forecasting for blood components distribution of a blood supply chain,” IFAC Proc. Vol., vol. 6, no. PART 1, pp. 565–571, 2013, doi: 10.3182/20130911-3-BR-3021.00092.

A. Jabbarzadeh, B. Fahimnia, and S. Seuring, “Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application,” Transp. Res. Part E Logist. Transp. Rev., vol. 70, no. 1, pp. 225–244, 2014, doi: 10.1016/j.tre.2014.06.003.

M. Habibi-Kouchaksaraei, M. M. Paydar, and E. Asadi-Gangraj, “Designing a bi-objective multi-echelon robust blood supply chain in a disaster,” Appl. Math. Model., vol. 55, pp. 583–599, 2018, doi: 10.1016/j.apm.2017.11.004.

A. Torrado and A. Barbosa-Póvoa, “Towards an Optimized and Sustainable Blood Supply Chain Network under Uncertainty: A Literature Review,” Clean. Logist. Supply Chain, vol. 3, no. December 2021, p. 100028, 2022, doi: 10.1016/j.clscn.2022.100028.

J. M. Stolwijk et al., “Red blood cells contain enzymatically active GPx4 whose abundance anticorrelates with hemolysis during blood bank storage,” Redox Biol., vol. 46, p. 102073, 2021, doi: 10.1016/j.redox.2021.102073.

D. F. Batero-Manso and J. A. Orjuela-Castro, “Inventory Routing Problem in Perishable Supply Chains: A Literature Review,” Ingeniería, vol. 23, no. 2, pp. 117–143, 2018.

A. F. Osorio Muriel, S. Brailsford, and H. Smith, “Un modelo de optimización bi-objetivo para la selección de tecnología y asignación de donantes en la cadena de suministro de sangre,” Rev. Sist. &Telemática, vol. 12, no. 30, pp. 9–24, 2014.

A. F. Osorio, S. C. Brailsford, and H. K. Smith, “A structured review of quantitative models in the blood supply chain: A taxonomic framework for decision-making,” Int. J. Prod. Res., vol. 53, no. 24, pp. 7191–7212, 2015, doi: 10.1080/00207543.2015.1005766.

M. C. Testik, B. Y. Ozkaya, S. Aksu, and O. I. Ozcebe, “Discovering blood donor arrival patterns using data mining: A method to investigate service quality at blood centers,” J. Med. Syst., vol. 36, no. 2, pp. 579–594, 2012, doi: 10.1007/s10916-010-9519-7.

R. Ramezanian and Z. Behboodi, “Blood supply chain network design under uncertainties in supply and demand considering social aspects,” Transp. Res. Part E Logist. Transp. Rev., vol. 104, pp. 69–82, 2017, doi: 10.1016/j.tre.2017.06.004.

A. van Dongen, R. Ruiter, C. Abraham, and I. Veldhuizen, “Predicting blood donation maintenance: the importance of planning future donations,” Transfusion, vol. 54, no. 3pt2, pp. 821–827, 2014, doi: 10.1111/trf.12397.

E. Alfonso, X. Xie, V. Augusto, and O. Garraud, “Modeling and simulation of blood collection systems,” Health Care Manag. Sci., vol. 15, no. 1, pp. 63–78, 2012, doi: 10.1007/s10729-011-9181-8.

E. A. Lizarazo et al., “Weekly Bloodmobile Collection Planning To cite this version : Mathematical Programming Models for Annual and Weekly Bloodmobile Collection Planning,” 2016.

R. Mousavi, A. Salehi-Amiri, A. Zahedi, and M. Hajiaghaei-Keshteli, “Designing a supply chain network for blood decomposition by utilizing social and environmental factor,” Comput. Ind. Eng., vol. 160, no. June, p. 107501, 2021, doi: 10.1016/j.cie.2021.107501.

S. Gunpinar and G. Centeno, “Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals,” Comput. Oper. Res., vol. 54, pp. 129–141, 2015, doi: 10.1016/j.cor.2014.08.017.

H. Ensafian and S. Yaghoubi, “Investigación de Transporte Parte E distribución integradas en la cadena de suministro de plaquetas,” vol. 103, pp. 32–55, 2017.

J. T. Blake and M. Hardy, “A generic modelling framework to evaluate network blood management policies: The Canadian Blood Services experience,” Oper. Res. Heal. Care, vol. 3, no. 3, pp. 116–128, 2014, doi: 10.1016/j.orhc.2014.05.002.

Q. Duan and T. W. Liao, “A new age-based replenishment policy for supply chain inventory optimization of highly perishable products,” Int. J. Prod. Econ., vol. 145, no. 2, pp. 658–671, 2013, doi: 10.1016/j.ijpe.2013.05.020.

S. Rajendran and A. Ravi Ravindran, “Inventory management of platelets along blood supply chain to minimize wastage and shortage,” Comput. Ind. Eng., vol. 130, no. July 2018, pp. 714–730, 2019, doi: 10.1016/j.cie.2019.03.010.

M. Shokouhifar, M. M. Sabbaghi, and N. Pilevari, “Inventory management in blood supply chain considering fuzzy supply/demand uncertainties and lateral transshipment,” Transfus. Apher. Sci., vol. 60, no. 3, p. 103103, 2021, doi: 10.1016/j.transci.2021.103103.

A. Simonetti, R. A. Forshee, S. A. Anderson, and M. Walderhaug, “A stock-and-flow simulation model of the US blood supply.,” Transfusion, vol. 54, no. 3 Pt 2, pp. 828–838, 2014, doi: 10.1111/trf.12392.

A. Shah, D. Shah, D. Shah, D. Chordiya, N. Doshi, and R. Dwivedi, “Blood Bank Management and Inventory Control Database Management System,” Procedia Comput. Sci., vol. 198, pp. 404–409, 2021, doi: 10.1016/j.procs.2021.12.261.

F. Baesler, M. Nemeth, C. Martínez, and A. Bastías, “Analysis of inventory strategies for blood components in a regional blood center using process simulation,” Transfusion, vol. 54, no. 2, pp. 323–330, 2014, doi: 10.1111/trf.12287.

S. H. W. Stanger, N. Yates, R. Wilding, and S. Cotton, “Blood Inventory Management: Hospital Best Practice,” Transfus. Med. Rev., vol. 26, no. 2, pp. 153–163, 2012, doi: 10.1016/j.tmrv.2011.09.001.

S. Gunpinar and G. Centeno, “An integer programming approach to the bloodmobile routing problem,” Transp. Res. Part E Logist. Transp. Rev., vol. 86, pp. 94–115, 2016, doi: 10.1016/j.tre.2015.12.005.

F. G. Şahinyazan, B. Y. Kara, and M. R. Taner, “Selective vehicle routing for a mobile blood donation system,” Eur. J. Oper. Res., vol. 245, no. 1, pp. 22–34, 2015, doi: 10.1016/j.ejor.2015.03.007.

M. P. Atkinson, M. J. Fontaine, L. T. Goodnough, and L. M. Wein, “A novel allocation strategy for blood transfusions: Investigating the tradeoff between the age and availability of transfused blood,” Transfusion, vol. 52, no. 1, pp. 108–117, 2012, doi: 10.1111/j.1537-2995.2011.03239.x.

Y. Zhou, T. Zou, C. Liu, H. Yu, L. Chen, and J. Su, “Blood supply chain operation considering lifetime and transshipment under uncertain environment,” Appl. Soft Comput., vol. 106, p. 107364, 2021, doi: 10.1016/j.asoc.2021.107364.

U. Abdulwahab and M. I. M. Wahab, “Approximate dynamic programming modeling for a typical blood platelet bank,” Comput. Ind. Eng., vol. 78, no. 2011, pp. 259–270, 2014, doi: 10.1016/j.cie.2014.07.017.

M. Eskandari-Khanghahi, R. Tavakkoli-Moghaddam, A. A. Taleizadeh, and S. H. Amin, “Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty,” Eng. Appl. Artif. Intell., vol. 71, no. June 2017, pp. 236–250, 2018, doi: 10.1016/j.engappai.2018.03.004.

Q. Duan and T. W. Liao, “Optimization of blood supply chain with shortened shelf lives and ABO compatibility,” Int. J. Prod. Econ., vol. 153, pp. 113–129, 2014, doi: 10.1016/j.ijpe.2014.02.012.

T. E. Martínez, R. A. Ledón, and C. M. Osés, “Aplicación De Un Procedimiento Para La Determinación Y Evaluación De Los Fallos En Un Banco De Sangre.,” Ing. Ind., vol. 31, no. 1, pp. 1–4, 2010, [Online]. Available: http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=60258573〈=es&site=ehost-live

A. Fallahi, H. Mokhtari, and S. T. A. Niaki, “Designing a closed-loop blood supply chain network considering transportation flow and quality aspects,” Sustain. Oper. Comput., vol. 2, no. June, pp. 170–189, 2021, doi: 10.1016/j.susoc.2021.07.002.

S. M. Zahraee, J. M. Rohani, A. Firouzi, and A. Shahpanah, “Efficiency Improvement of Blood Supply Chain System Using Taguchi Method and Dynamic Simulation,” Procedia Manuf., vol. 2, no. February, pp. 1–5, 2015, doi: 10.1016/j.promfg.2015.07.001.

Y. C. Li and H. C. Liao, “The optimal parameter design for a blood supply chain system by the taguchi method,” Int. J. Innov. Comput. Inf. Control, vol. 8, no. 11, pp. 7697–7712, 2012.

J. T. Blake, M. Hardy, G. Delage, and G. Myhal, “Déjà-vu all over again: Using simulation to evaluate the impact of shorter shelf life for red blood cells at Héma-Québec,” Transfusion, vol. 53, no. 7, pp. 1544–1558, 2013, doi: 10.1111/j.1537-2995.2012.03947.x.

B. Abbasi, T. Babaei, Z. Hosseinifard, K. Smith-Miles, and M. Dehghani, “Predicting solutions of large-scale optimization problems via machine learning: A case study in blood supply chain management,” Comput. Oper. Res., vol. 119, p. 104941, 2020, doi: 10.1016/j.cor.2020.104941.

E. J. Tabares Molina and B. Hernández Ramírez, “Evaluación psicométrica de la escala de calidad de servicios de atención en donantes de un banco de sangre en Medellín, Colombia, 2019,” Rev. Fac. Nac. Salud Pública, vol. 39, no. 3, p. e343606, 2021, doi: 10.17533/udea.rfnsp.e343606.

N. Haghjoo, R. Tavakkoli-Moghaddam, H. Shahmoradi-Moghadam, and Y. Rahimi, “Reliable blood supply chain network design with facility disruption: A real-world application,” Eng. Appl. Artif. Intell., vol. 90, no. January, p. 103493, 2020, doi: 10.1016/j.engappai.2020.103493.

M. R. Ghatreh Samani, S. A. Torabi, and S. M. Hosseini-Motlagh, “Integrated blood supply chain planning for disaster relief,” Int. J. Disaster Risk Reduct., vol. 27, pp. 168–188, 2018, doi: 10.1016/j.ijdrr.2017.10.005.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Journal of Language and Linguistic Studies
ISSN 1305-578X (Online)
Copyright © 2005-2022 by Journal of Language and Linguistic Studies