Journal of Medical Systems

, 40:209 | Cite as

Big Data in Health: a Literature Review from the Year 2005

  • Isabel de la Torre Díez
  • Héctor Merino Cosgaya
  • Begoña Garcia-Zapirain
  • Miguel López-Coronado
Education & Training
Part of the following topical collections:
  1. Education & Training


The information stored in healthcare systems has increased over the last ten years, leading it to be considered Big Data. There is a wealth of health information ready to be analysed. However, the sheer volume raises a challenge for traditional methods. The aim of this article is to conduct a cutting-edge study on Big Data in healthcare from 2005 to the present. This literature review will help researchers to know how Big Data has developed in the health industry and open up new avenues for research. Information searches have been made on various scientific databases such as Pubmed, Science Direct, Scopus and Web of Science for Big Data in healthcare. The search criteria were “Big Data” and “health” with a date range from 2005 to the present. A total of 9724 articles were found on the databases. 9515 articles were discarded as duplicates or for not having a title of interest to the study. 209 articles were read, with the resulting decision that 46 were useful for this study. 52.6 % of the articles used were found in Science Direct, 23.7 % in Pubmed, 22.1 % through Scopus and the remaining 2.6 % through the Web of Science. Big Data has undergone extremely high growth since 2011 and its use is becoming compulsory in developed nations and in an increasing number of developing nations. Big Data is a step forward and a cost reducer for public and private healthcare.


Big data Databases Health Review 



This research has been partially supported by the European Commission and the Ministry of Industry, Energy and Tourism under the project AAL-20125036 named “WetakeCare: ICT- based Solution for (Self-) Management of Daily Living”.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interests.


  1. 1.
    Martínez Sesmero, J.M., “Big Data”; Aplicación y utilidad para el sistema sanitario. Farm. Hosp. 39(2):69–70, 2015.PubMedGoogle Scholar
  2. 2.
    Shin, D., Sahama, T., and Gajanayake, R., Secured e-health data retrieval in DaaS and Big Data. Presented at: IEEE 15th International e-Health Networking, Applications & Services (Healthcom) 255–259, 2013.Google Scholar
  3. 3.
    Chang, V., A model to compare cloud and non-cloud storage of big data. Futur. Gener. Comput. Syst. 57:56–76, 2016.CrossRefGoogle Scholar
  4. 4.
    Huang, T., Lan, L., Fang, X., An, P., Min, J., and Wang, F., Promises and challenges of big data computing in health sciences. Big Data Res. 2:2–11, 2015.CrossRefGoogle Scholar
  5. 5.
    Costa, F., Big data in biomedicine. Drug Discov. Today. 19(4):433–440, 2014.CrossRefPubMedGoogle Scholar
  6. 6.
    Parra Calderón, C.L., Big data in health in Spain: Now is the time for a national strategy. Gac. Sanit. 30(1):63–65, 2016.CrossRefPubMedGoogle Scholar
  7. 7.
    Ting Wong, H., Yin, Q., Qi Guo, Y., Murray, K., Hau Zhou, D., and Slade, D., Big data as a new approach in emergency medicine research. J. Acute Dis. 4(3):178–179, 2015.CrossRefGoogle Scholar
  8. 8.
    O’Driscoll, A., Daugelaite, J., and Sleator, R., ‘Big data’, Hadoop and cloud computing in genomics. J. Biomed. Inform. 46:774–781, 2013.CrossRefPubMedGoogle Scholar
  9. 9.
    Merelli, I., Pérez-Sánchez, H., Gesing, S., and D’Agostino, D., Managing. Analysing, and integrating big data in medical bioinformatics: Open problems and future perspectives. Biomed. Res. Int. 2014:1–13, 2014.Google Scholar
  10. 10.
    Blanke, T., Big data collecting. Digit. Asset Ecosyst.:87–117, 2014.Google Scholar
  11. 11.
    Cunhaa, J., Silvaa, C., and Antunesa, M., Health twitter big bata management with Hadoop framework. Procedia Comput. Sci. 64:425–431, 2015.CrossRefGoogle Scholar
  12. 12.
    Ahmad, A., Paul, A., and Rathore, M., An efficient divide-and-conquer approach for big data analytics in machine-to-machine communication. Neurocomputing. 174:439–453, 2016.CrossRefGoogle Scholar
  13. 13.
    Chen, M., Mao, S., and Liu, Y., Big data: A survey. Mobile Netw. Appl. 19:171–209, 2014.CrossRefGoogle Scholar
  14. 14.
    Archenaa, J., and Anita, M., A survey of big data analytics in healthcare and government. Procedia Comput. Sci. 50:408–413, 2015.CrossRefGoogle Scholar
  15. 15.
    Young, S., A “big data” approach to HIV epidemiology and prevention. Prev. Med. 70:17–18, 2015.CrossRefPubMedGoogle Scholar
  16. 16.
    Kumar, S., Eswari, S., and Lavanya, S., Predictive methodology for diabetic data analysis in big data. Procedia Comput. Sci. 50:203–208, 2015.CrossRefGoogle Scholar
  17. 17.
    Scopus. Available from: (last accessed 30 May 2016).
  18. 18.
    PubMed. Available from: (last accessed 30 May 2016).
  19. 19.
    Science Direct. Available from: (last accessed 20 May 2016).
  20. 20.
    Web of Science. Available from: (last accessed 30 May 2016).
  21. 21.
    Clarke, R., Big data, big risks. Inf. Syst. J. 26:77–90, 2016.CrossRefGoogle Scholar
  22. 22.
    Vayena, E., Salathé, M., Madoff, L., and Brownstein, J., Ethical challenges of big data in public health. PLoS Comput. Biol. 11(2):e1003904, 2015.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Perez, J., Poon, C., Merrifield, R., Wong, S., Yang, G., and Fellow, Big data for health. IEEE J. Biomed. Health Inform. 19(4):1193–1208, 2015.CrossRefGoogle Scholar
  24. 24.
    Belle, A., Thiagarajan, R., Soroushmehr, R., Navidi, F., Beard, D., and Najarian, K., Big data analytics in healthcare. BioMed. Res. Int. 2015:1–16, 2015.CrossRefGoogle Scholar
  25. 25.
    Kshetri, N., Big data’s impact on privacy, security and consumer welfare. Telecommun. Policy. 38:1134–1145, 2014.CrossRefGoogle Scholar
  26. 26.
    Margolis, R., Derr, L., Dunn, M., Huerta, M., Larkin, J., Sheehan, J., Guyer, M., and Green, E., The national institutes of health’s big data to knowledge (BD2K) initiative: Capitalizing on biomedical big data. J. Am. Med. Inform. Assoc. 21:957–958, 2014.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Zhang, X., Liu, C., Nepal, S., Yang, C., and Chen, J.S., Privacy preservation over big data in cloud systems. In: Security, Privacy and Trust in Cloud Systems. Springer-Verlag, Berlin Heidelberg, pp. 239–257, 2014.CrossRefGoogle Scholar
  28. 28.
    Nambiar R, Sethi A, Bhardwaj, R., Vargheese, R., A Look at Challenges and Opportunities of Big Data Analytics in Healthcare. Presented at: IEEE International Conference on Big Data 17–22, 2013.Google Scholar
  29. 29.
    Brinkmanna, B., Bowera, M., Stengel, K., Worrell, G., and Steada, M., Large-scale electrophysiology: Acquisition, compression, encryption, and storage of big data. J. Neurosci. Methods. 180:185–192, 2009.CrossRefGoogle Scholar
  30. 30.
    Kemp, R., Legal aspects of managing big data. Comput. Law Secur. Rev. 30:482–491, 2014.CrossRefGoogle Scholar
  31. 31.
    Lafuente, G., The big data security challenge. Netw. Secur. 1:12–14, 2015.CrossRefGoogle Scholar
  32. 32.
    Elsebakhi, E., Leeb, F., Schendela, E., Haquea, A., Kathireasona, N., Patharea, T., Syeda, N., and Al-Ali, R., Large-scale machine learning based on functional networks for biomedical big data with high performance computing platforms. J. Comput. Sci. 11:69–81, 2015.CrossRefGoogle Scholar
  33. 33.
    Jina, X., Waha, B., Chenga, X., and Wanga, Y., Significance and challenges of big data research. Big Data Res. 2:59–64, 2015.CrossRefGoogle Scholar
  34. 34.
    Satell, G., 6 things you should know about the future. Futur. Online Secur. 237–258, 2014.Google Scholar
  35. 35.
    Cumbley, R., and Church, P., Is “big data” creepy? Comput. Law Secur. Rev. 29:601–609, 2013.CrossRefGoogle Scholar
  36. 36.
    Shen, Y., and Zhang, Y., Transmission protocol for secure big data in two-hop wireless networks with cooperative jamming. Inf. Sci. 281:201–210, 2014.CrossRefGoogle Scholar
  37. 37.
    Ladha, K., Arora, V., Dutton, R., and Hyder, J., Potential and pitfalls for big data in health research. Adv. Anesth. 33:97–111, 2015.CrossRefGoogle Scholar
  38. 38.
    Chen, P., and Zhang, C., Data-intensive applications, challenges, techniques and technologies: A survey on big data. Inf. Sci. 275:314–347, 2014.CrossRefGoogle Scholar
  39. 39.
    Pérez, G., Risks of the use of big data in research in public health and epidemiology. Gac. Sanit. 30(1):66–68, 2016.CrossRefPubMedGoogle Scholar
  40. 40.
    Trifiletti, D., and Showalter, T., Big data and comparative effectiveness research in radiation oncology: Synergy and accelerated discovery. Front. Oncol. 5:274, 2015.CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Hesse, B., Moser, R., and Riley, W., From big data to knowledge in the social sciences. Ann. Am. Acad. Pol. Soc. Sci. 659(1):16–32, 2015.CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Alyass, A., Turcotte, M., and Meyre, D., From big data analysis to personalized medicine for all: Challenges and opportunities. BMC Med. Genet. 8:33, 2015.Google Scholar
  43. 43.
    Wyber, R., Vaillancourt, S., Perry, W., Mannava, P., Folaranmi, T., and Celi, L., Big data in global health: Improving health in low- and middle-income countries. Bull. World Health Organ. 93:203–208, 2015.CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Moskowitz, A., McSparron, J., Stone, D., and Celi, L., Preparing a new generation of clinicians for the era of big data. Harv. Med. Stud. Rev. 2(1):24–27, 2015.PubMedPubMedCentralGoogle Scholar
  45. 45.
    Hood, L., Lovejoy, J., and Price, N., Integrating big data and actionable health coaching to optimize wellness. BMC Med. 13(4):1–4, 2015.Google Scholar
  46. 46.
    Otero, P., Hersh, W., and Ganesh, J., Big data: Are biomedical and health informatics training programs ready? IMIA Yearb. Med. Inform. 9:177–181, 2014.CrossRefPubMedGoogle Scholar
  47. 47.
    Krishnan, E., Big data and clinicians: A review on the state of the science. JMIR Med. Inform. 2(1):e1, 2014.CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Doarn, C.R., and Merrell, R.C., Accessibility and vulnerability: Ensuring security of data in telemedicine. Telemed. J. E. Health. 21(3):143–144, 2015.CrossRefPubMedGoogle Scholar
  49. 49.
    Wang, F., The role of cost in telemedicine evaluation. Telemed. J. E. Health. 15(10):949–955, 2009.CrossRefPubMedGoogle Scholar
  50. 50.
    Yao, Q., et al., Design and development of a medical big data processing system based on Hadoop. J. Med. Syst. 39:23, 2015.CrossRefPubMedGoogle Scholar
  51. 51.
    Mezghani, E., A semantic big data platform for integrating heterogeneous wearable data in healthcare. J. Med. Syst. 39:185, 2015.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Isabel de la Torre Díez
    • 1
  • Héctor Merino Cosgaya
    • 1
  • Begoña Garcia-Zapirain
    • 2
  • Miguel López-Coronado
    • 1
  1. 1.Department of Signal Theory and Communications, and Telematics EngineeringUniversity of ValladolidValladolidSpain
  2. 2.University of DeustoBilbaoSpain

Personalised recommendations