Abstract
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.
Similar content being viewed by others
References
Martínez Sesmero, J.M., “Big Data”; Aplicación y utilidad para el sistema sanitario. Farm. Hosp. 39(2):69–70, 2015.
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.
Chang, V., A model to compare cloud and non-cloud storage of big data. Futur. Gener. Comput. Syst. 57:56–76, 2016.
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.
Costa, F., Big data in biomedicine. Drug Discov. Today. 19(4):433–440, 2014.
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.
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.
O’Driscoll, A., Daugelaite, J., and Sleator, R., ‘Big data’, Hadoop and cloud computing in genomics. J. Biomed. Inform. 46:774–781, 2013.
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.
Blanke, T., Big data collecting. Digit. Asset Ecosyst.:87–117, 2014.
Cunhaa, J., Silvaa, C., and Antunesa, M., Health twitter big bata management with Hadoop framework. Procedia Comput. Sci. 64:425–431, 2015.
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.
Chen, M., Mao, S., and Liu, Y., Big data: A survey. Mobile Netw. Appl. 19:171–209, 2014.
Archenaa, J., and Anita, M., A survey of big data analytics in healthcare and government. Procedia Comput. Sci. 50:408–413, 2015.
Young, S., A “big data” approach to HIV epidemiology and prevention. Prev. Med. 70:17–18, 2015.
Kumar, S., Eswari, S., and Lavanya, S., Predictive methodology for diabetic data analysis in big data. Procedia Comput. Sci. 50:203–208, 2015.
Scopus. Available from: http://www.scopus.com/ (last accessed 30 May 2016).
PubMed. Available from: http://www.ncbi.nlm.nih.gov/pubmed/advanced (last accessed 30 May 2016).
Science Direct. Available from: http://www.sciencedirect.com (last accessed 20 May 2016).
Web of Science. Available from: https://www.accesowok.fecyt.es (last accessed 30 May 2016).
Clarke, R., Big data, big risks. Inf. Syst. J. 26:77–90, 2016.
Vayena, E., Salathé, M., Madoff, L., and Brownstein, J., Ethical challenges of big data in public health. PLoS Comput. Biol. 11(2):e1003904, 2015.
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.
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.
Kshetri, N., Big data’s impact on privacy, security and consumer welfare. Telecommun. Policy. 38:1134–1145, 2014.
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.
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.
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.
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.
Kemp, R., Legal aspects of managing big data. Comput. Law Secur. Rev. 30:482–491, 2014.
Lafuente, G., The big data security challenge. Netw. Secur. 1:12–14, 2015.
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.
Jina, X., Waha, B., Chenga, X., and Wanga, Y., Significance and challenges of big data research. Big Data Res. 2:59–64, 2015.
Satell, G., 6 things you should know about the future. Futur. Online Secur. 237–258, 2014.
Cumbley, R., and Church, P., Is “big data” creepy? Comput. Law Secur. Rev. 29:601–609, 2013.
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.
Ladha, K., Arora, V., Dutton, R., and Hyder, J., Potential and pitfalls for big data in health research. Adv. Anesth. 33:97–111, 2015.
Chen, P., and Zhang, C., Data-intensive applications, challenges, techniques and technologies: A survey on big data. Inf. Sci. 275:314–347, 2014.
Pérez, G., Risks of the use of big data in research in public health and epidemiology. Gac. Sanit. 30(1):66–68, 2016.
Trifiletti, D., and Showalter, T., Big data and comparative effectiveness research in radiation oncology: Synergy and accelerated discovery. Front. Oncol. 5:274, 2015.
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.
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.
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.
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.
Hood, L., Lovejoy, J., and Price, N., Integrating big data and actionable health coaching to optimize wellness. BMC Med. 13(4):1–4, 2015.
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.
Krishnan, E., Big data and clinicians: A review on the state of the science. JMIR Med. Inform. 2(1):e1, 2014.
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.
Wang, F., The role of cost in telemedicine evaluation. Telemed. J. E. Health. 15(10):949–955, 2009.
Yao, Q., et al., Design and development of a medical big data processing system based on Hadoop. J. Med. Syst. 39:23, 2015.
Mezghani, E., A semantic big data platform for integrating heterogeneous wearable data in healthcare. J. Med. Syst. 39:185, 2015.
Acknowledgments
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”.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no competing interests.
Additional information
This article is part of the Topical Collection on Education & Training
Rights and permissions
About this article
Cite this article
de la Torre Díez, I., Cosgaya, H.M., Garcia-Zapirain, B. et al. Big Data in Health: a Literature Review from the Year 2005. J Med Syst 40, 209 (2016). https://doi.org/10.1007/s10916-016-0565-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10916-016-0565-7