Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Big Data Enabled Healthcare Supply Chain Management: Opportunities and Challenges

  • Conference paper
  • First Online:
Smart Societies, Infrastructure, Technologies and Applications (SCITA 2017)

Abstract

It is estimated that healthcare spending in the world’s major regions will increase from 2.4% of GDP to 7.5% during 2015 to 2020. Healthcare providers are required to deliver high quality medical services to their customers. Since most of their budgets are spent on high cost medical equipment and medicines, there is a pressing need for them to optimize their supply chain activities such that high-quality services could be provided at lower costs. Relatedly, medical equipment and devices generate massive amounts of unused data. Big data analytics is proven to be helpful in forecasting and decision-making, and, hence, can be a powerful tool to improve healthcare supply chains. This paper presents a review on the use of big data in healthcare supply chains. We review the various concepts related to the topic of this paper including big data, big data analytics, and the role of big data in healthcare, and in healthcare supply chain management. The opportunities and challenges for big data enabled healthcare supply chains are discussed along with several directions for future developments. We conclude that the use of big data in healthcare supply chains is of immense potential and demands further investigation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Deloitte: 2017 Global Health Care Sector Outlook 2015 (2017)

    Google Scholar 

  2. Sultanow, E., Chircu, A.M.: Improving healthcare with data-driven track-and-trace systems. In: Strategic Data Based Wisdom in the Big Data Era, pp. 65–82 (2015)

    Google Scholar 

  3. Kwon, I.W.G., Kim, S.H., Martin, D.G.: Healthcare supply chain management; strategic areas for quality and financial improvement. Technol. Forecast. Soc. Change 113, 422–428 (2016)

    Article  Google Scholar 

  4. Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19, 171–209 (2014)

    Article  Google Scholar 

  5. Malik, M.M., Abdallah, S., Ala’raj, M.: Data mining and predictive analytics applications for the delivery of healthcare services: a systematic literature review. Ann. Oper. Res. 247, 1–26 (2016)

    Article  MathSciNet  Google Scholar 

  6. Naoui, F.: Customer service in supply chain management: a case study. J. Enterp. Inf. Manag. 27, 786–801 (2014)

    Article  Google Scholar 

  7. Akyuz, G.A., Rehan, M.: Requirements for forming an “e-supply chain”. Int. J. Prod. Res. 47, 3265–3287 (2009)

    Article  Google Scholar 

  8. Butner, K.: The smarter supply chain of the future. Strateg. Leadersh. 38, 22–31 (2010)

    Article  Google Scholar 

  9. Hessman, T.: The dawn of the smart factory. IndustryWeek 14, 14–19 (2013)

    Google Scholar 

  10. Ahmad, N., Mehmood, R.: Enterprise systems: are we ready for future sustainable cities. Supply Chain Manag. Int. J. 20, 264–283 (2015)

    Article  Google Scholar 

  11. Ahmad, N., Mehmood, R.: Enterprise systems and performance of future city logistics 27, 500–513 (2016). http://dx.doi.org/10.1080/09537287.2016.1147098

  12. Mehmood, R., Faisal, M.A., Altowaijri, S.: Future networked healthcare systems: a review and case study. In: Information Resources Management Association (ed.) Big Data: Concepts, Methodologies, Tools, and Applications, pp. 2429–2457. IGI Global (2016)

    Google Scholar 

  13. Mehmood, R., Meriton, R., Graham, G., Hennelly, P., Kumar, M.: Exploring the influence of big data on city transport operations: a Markovian approach. Int. J. Oper. Prod. Manag. 37, 75–104 (2017)

    Article  Google Scholar 

  14. Suma, S., Mehmood, R., Albugami, N., Katib, I., Albeshri, A.: Enabling next generation logistics and planning for smarter societies. Procedia - Procedia Comput. Sci. 104C, 1–6 (2017)

    Google Scholar 

  15. Enabling Smarter Societies through Mobile Big Data Fogs and Clouds. http://www.sciencedirect.com/science/article/pii/S1877050917311213

  16. Alam, F., Mehmood, R., Katib, I., Albogami, N.N., Albeshri, A.: Data fusion and IoT for smart ubiquitous environments: a survey. IEEE Access 5, 9533–9554 (2017)

    Article  Google Scholar 

  17. Mehmood, R., Alam, F., Albogami, N.N., Katib, I., Albeshri, A., Altowaijri, S.M.: UTiLearn: a personalised ubiquitous teaching and learning system for smart societies. IEEE Access 5, 2615–2635 (2017)

    Article  Google Scholar 

  18. Feki, M., Wamba, S.F.: Big data analytics-enabled supply chain transformation : a literature review. In: 49th Hawaii International Conference on System Sciences, pp. 1123–1132 (2016)

    Google Scholar 

  19. Hogarth, R.M., Soyer, E.: Using simulated experience to make sense of big data. MIT Sloan Manag. Rev. 56, 49–54 (2015)

    Google Scholar 

  20. Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manag. 35, 137–144 (2015)

    Article  Google Scholar 

  21. Waller, M.A., Fawcett, S.E.: Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logist. 34, 77–84 (2013)

    Article  Google Scholar 

  22. Zhong, R.Y., Newman, S.T., Huang, G.Q., Lan, S.: Big data for supply chain management in the service and manufacturing sectors: challenges, opportunities, and future perspectives. Comput. Ind. Eng. 101, 572–591 (2016)

    Article  Google Scholar 

  23. Altowaijri, S., Mehmood, R., Williams, J.: A quantitative model of grid systems performance in healthcare organisations. In: ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, pp. 431–436 (2010)

    Google Scholar 

  24. Srinivasan, U., Arunasalam, B.: Leveraging big data analytics to reduce healthcare costs. IT Prof. 15, 21–28 (2013)

    Article  Google Scholar 

  25. Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Health Inf. Sci. Syst. 2, 3 (2014)

    Article  Google Scholar 

  26. Feldman, B., Martin, E.M., Skotnes, T.: Big Data in Healthcare - Hype and Hope (2012). http://www.riss.kr/link?id=A99883549

  27. Bates, D.W., Saria, S., Ohno-Machado, L., Shah, A., Escobar, G.: Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. 33, 1123–1131 (2014)

    Article  Google Scholar 

  28. Tawalbeh, L.A., Mehmood, R., Benkhlifa, E., Song, H.: Mobile cloud computing model and big data analysis for healthcare applications. IEEE Access 4, 6171–6180 (2016)

    Article  Google Scholar 

  29. Tawalbeh, L.A., Bakhader, W., Mehmood, R., Song, H.: Cloudlet-based mobile cloud computing for healthcare applications. In: 2016 IEEE Global Communications Conference (GLOBECOM), pp. 1–6. IEEE (2016)

    Google Scholar 

  30. Mehmood, R., Graham, G.: Big data logistics: a health-care transport capacity sharing model. Procedia Comput. Sci. 64, 1107–1114 (2015)

    Article  Google Scholar 

  31. Varela, I.R., Tjahjono, B.: Big data analytics in supply chain management: trends and related research. In: 6th International Conference on Operations and Supply Chain Management, 1, 2013–2014 (2014)

    Google Scholar 

  32. Dobrzykowski, D., Saboori Deilami, V., Hong, P., Kim, S.C.: A structured analysis of operations and supply chain management research in healthcare (1982–2011). Int. J. Prod. Econ. 147, 514–530 (2014)

    Article  Google Scholar 

  33. Xu, S., Tan, K.H.: Data-driven inventory management in the healthcare supply chain (2016)

    Google Scholar 

  34. Bughin, J., Chui, M., Manyika, J.: Clouds, big data, and smart assets: ten tech-enabled business trends to watch. McKinsey Q. 56, 75–86 (2010)

    Google Scholar 

  35. Tan, K.H., Zhan, Y.Z., Ji, G., Ye, F., Chang, C.: Harvesting big data to enhance supply chain innovation capabilities: an analytic infrastructure based on deduction graph. Int. J. Prod. Econ. 165, 223–233 (2015)

    Article  Google Scholar 

Download references

Acknowledgments

The work carried out in this paper is supported by the HPC Center at the King Abdulaziz University.

Author information

Authors and Affiliations

  1. Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz Univeristy, Jeddah, Saudi Arabia

    Shoayee Alotaibi

  2. High Performance Computing Center, King Abdulaziz University, Jeddah, Saudi Arabia

    Rashid Mehmood

Authors
  1. Shoayee Alotaibi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rashid Mehmood
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shoayee Alotaibi .

Editor information

Editors and Affiliations

  1. King Abdulaziz University, Jeddah, Saudi Arabia

    Rashid Mehmood

  2. Geographic Information Science and Technology, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

    Budhendra Bhaduri

  3. King Abdulaziz University, Jeddah, Saudi Arabia

    Iyad Katib

  4. European Alliance for Innovation, Bratislava, Slovakia

    Imrich Chlamtac

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alotaibi, S., Mehmood, R. (2018). Big Data Enabled Healthcare Supply Chain Management: Opportunities and Challenges. In: Mehmood, R., Bhaduri, B., Katib, I., Chlamtac, I. (eds) Smart Societies, Infrastructure, Technologies and Applications. SCITA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-94180-6_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-94180-6_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94179-0

  • Online ISBN: 978-3-319-94180-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation