[Risks of the use of big data in research in public health and epidemiology]

[Review of the methodological, ethical, legal and social issues of research projects in healthcare with big data]

The current model for reviewing research with human beings basically depends on decision-making processes within research ethics committees. These committees must be aware of the importance of the new digital paradigm based on the large-scale exploitation of datasets, including personal data on health. This article offers guidelines, with the application of the EU's General Data Protection Regulation, for the appropriate evaluation of projects that are based on the use of big data analytics in healthcare. The processes for gathering and using this data constitute a niche where current research is developed. In this context, the existing protocols for obtaining informed consent from participants are outdated, as they are based not only on the assumption that personal data are anonymized, but that they will continue to be so in the future. As a result, it is essential that research ethics committees take on new capabilities and revisit values such as privacy and freedom, updating protocols, methodologies and working procedures. This change in the work culture will provide legal security to the personnel involved in research, will make it possible to guarantee the protection of the privacy of the subjects of the data, and will permit orienting the exploitation of data to avoid the commodification of personal data in this era of deidentification, so that research meets actual social needs and not spurious or opportunistic interests disguised as research.

A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector

The main objective of this paper is to present a review of existing researches in the literature, referring to Big Data sources and techniques in health sector and to identify which of these techniques are the most used in the prediction of chronic diseases. Academic databases and systems such as IEEE Xplore, Scopus, PubMed and Science Direct were searched, considering the date of publication from 2006 until the present time. Several search criteria were established as 'techniques' OR 'sources' AND 'Big Data' AND 'medicine' OR 'health', 'techniques' AND 'Big Data' AND 'chronic diseases', etc. Selecting the paper considered of interest regarding the description of the techniques and sources of Big Data in healthcare. It found a total of 110 articles on techniques and sources of Big Data on health from which only 32 have been identified as relevant work. Many of the articles show the platforms of Big Data, sources, databases used and identify the techniques most used in the prediction of chronic diseases. From the review of the analyzed research articles, it can be noticed that the sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality.

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

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.