Journal of Medical Systems

, 43:28 | Cite as

An Analysis of Re-configured Blood Transfusion Network of Urban India to Improve the Service Level: a Simulation Approach

  • S. SelvakumarEmail author
  • P. Shahabudeen
  • T. Paul Robert
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Wearable Computing Techniques for Smart Health


In India, blood banks are owned by state hospitals, private hospitals, NGOs and private laboratories. The aim of this study is to improve the service levels of the blood supply chain by maximizing the availability and minimizing the wastage of blood. New configuration approaches are adapted from the successful methods of manufacturing sectors. In this retrospective cross-sectional study, whole blood (WB) demand and supply data between April 2015 to March 2016 has been taken. Data analytics tool “R” is used for statistical analysis. Two new configurations, namely a) Zonal Network and b) Pull system models have been developed to compare the existing blood supply chain. The performances of the proposed configurations have been compared with the existing system using suitable indicators computed using Arena simulation software12.0. The total shortage index (TSI) and total wastage index (TWI) are used as indicators of performance measures. Weights are assigned for shortage and wastage indices to the reconfigured models. The pull system model outperforms existing model and zone model by achieving zero wastage. In transfusion medicine, importance is given to the achievement of lesser percentage shortage than wastage. If the WB inventory in blood centers is sufficient enough and we have more than one zone for distribution, then we can reduce wastages level in the blood supply chain.


Healthcare supply chain Blood transfusion Data analytics Clustering Pull system Simulation 


  1. 1.
    Family Welfare, N. Delhi, Assessment of Blood Banks of India - 2016. NACO report, 2017.Google Scholar
  2. 2.
    Shukla, J. C., Second management consultation on healthcare in India. Indian Institute of Management: Ahmedabad, 1-356, 2007.Google Scholar
  3. 3.
    Garraud, O., Politis, C., Vuk, T., and Tissot, J. D., Rethinking transfusion medicine with a more holistic approach. Transfus. Clin. Biol. 25(1):81–82, 2017.CrossRefGoogle Scholar
  4. 4.
    Pierskalla, W., Supply chain management of blood banks. In: Brandeau, M., Sanfort, F., and Pierskalla, W. (Eds.), Operations research and health care: A handbook of methods and applications. Boston, Massachusetts: Kluwer Academic Publishers, 103–145, 2004.Google Scholar
  5. 5.
    Katsaliaki, K., Cost-effective practices in the blood service sector. Health policy (Amsterdam, Netherlands) 86(2–3):276–287, 2008.CrossRefGoogle Scholar
  6. 6.
    Erhabor, O., and Adias, T. C., From whole blood to component therapy: The economic, supply/demand need for implementation of component therapy in sub-Saharan Africa. Transfus. Clin. Biol. 18(5–6):516–526, 2011.CrossRefGoogle Scholar
  7. 7.
    Alfonso, E., Xie, X., Augusto, V., and Garraud, O., Modeling and simulation of blood collection systems. Health Care Manag. Sci. 15(1):63–78, 2012.Google Scholar
  8. 8.
    Dhingra, N., International challenges of self-sufficiency in blood products. Transfus. Clin. Biol. 20(2):148–152, 2013.CrossRefGoogle Scholar
  9. 9.
    Lowalekar, H., and Ravichandran, N., Blood bank inventory management in India. Op. Search 51(3):376–399, 2013.Google Scholar
  10. 10.
    Alfonso, E., Xie, X., Augusto, V., and Garraud, O., Modelling and simulation of blood collection systems: Improvement of human resources allocation for better cost-effectiveness and reduction of candidate donor abandonment. Vox Sang. 104(3):225–233, 2013.CrossRefGoogle Scholar
  11. 11.
    Duan, Q., and Liao, T. W., Optimization of blood supply chain with shortened shelf lives and ABO compatibility. Int. J. Prod. Econ. 153:113–129, 2014.CrossRefGoogle Scholar
  12. 12.
    Varela, I. R., and Tjahjono, B., Big data analytics in supply chain management: trends and related research. In: 6th International Conference on Operations and Supply Chain Management. Vol. 1(1):2013–2014, 2014.Google Scholar
  13. 13.
    Jabbarzadeh, A., Fahimnia, B., and Seuring, S., Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application. Transport. Res. E-Log. 70(1):225–244, 2014.CrossRefGoogle Scholar
  14. 14.
    Ganesh, K., Narendran, T. T., and Anbuudayasankar, S. P., Evolving cost-effective routing of vehicles for blood bank logistics. International Journal of Logistics Systems and Management 17(4):381, 2014.CrossRefGoogle Scholar
  15. 15.
    Bhatia, V., Raghuwanshi, B., and Sahoo, J., Current status of blood banks in India. Global Journal of Transfusion Medicine 1(2):72, 2016.CrossRefGoogle Scholar
  16. 16.
    Lowalekar, H., and Ravi, R. R., Revolutionizing blood bank inventory management using the TOC thinking process: An Indian case study. Int. J. Prod. Econ. 186(February):89–122, 2017.Google Scholar
  17. 17.
    Hosseinifard, Z., and Abbasi, B., The inventory centralization impacts on sustainability of the blood supply chain. Comput. Oper. Res. 89:206–212, 2018.CrossRefGoogle Scholar
  18. 18.
    Ramezanian, R., and Behboodi, Z., Blood supply chain network design under uncertainties in supply and demand considering social aspects. Transport. Res. E-Log. 104:69–82, 2017.CrossRefGoogle Scholar
  19. 19.
    Rajmohan, M., Theophilus, C., Sumalatha, M. R., Saravanakumar, S., Facility location of organ procurement organisations in Indian health care supply chain management. S. Afr. J. Ind. Eng. 28(1):90–102, 2017.Google Scholar
  20. 20.
    Wang, Y. et al., Service supply chain management: A review of operational models. Eur. J. Oper. Res. 247(3):685–698, 2015.CrossRefGoogle Scholar
  21. 21.
    Osorio, A. F., Brailsford, S. C., Smith, H. K. and Blake, J., Designing the blood supply chain: how much, how and where? Vox Sang. 113(8):760–769, 2018.Google Scholar
  22. 22.
    Duan, J., Su, Q., Zhu, Y., Lu,Y., Study on the centralization strategy of the blood allocation among different departments within a hospital. J. Syst. Sci. Syst. Eng. 27(4):417–434, 2018.Google Scholar
  23. 23.
    Nagurney, A., and Masoumi, A. H., Supply chain network design of a sustainable blood banking system, sustainable supply chains: models, methods and public policy implications. Springer 49–72, 2012.Google Scholar
  24. 24.
    Testik, M. C. et al., Discovering blood donor arrival patterns using data mining: A method to investigate service quality at blood centers. J. Med. Syst. 36(2):579–594, 2012.CrossRefGoogle Scholar
  25. 25.
    Blake, J., and Hardy, M., Using simulation to evaluate a blood supply network in the Canadian maritime provinces. J. Enterp. Inf. Manag. 26(2):119–134, 2013.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Industrial EngineeringCollege of Engineering Guindy, Anna UniversityChennaiIndia

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