By Athanasia K.
Big Data applications in healthcare is probably the field with the most heated discussions about the controversial impacts of this new technology. In fact, I could bet that there are not so many other discourses in this field where there is such clear contrast of benefits vs harm, individual vs common good, public vs private, data identification vs identity or last but not least, a contrast between the virtual vs the real, as Kaplan also observes. It’s like an old spaghetti western, where after a closer look in the plot we realise that what is a “good” and justified against a “bad” and condemned behaviour, really depends on the observer. I’ll start with the positive part:
Part I: the good Dr. Jekyll
According to Ya-Ri Lee et al “the field that shows the most promise among the application areas of Big Data is the medical sector”.
As Alemayehu lists in a recent paper, in the context of healthcare Big Data includes “not only electronic health records, claims data but also data captured through every conceivable medium, including Social Media, Internet search, wearable devices, video streams, and personal genomic services; it may also include data collected from randomized controlled clinical trials (particularly when dealing with high dimensional data, including genomic, laboratory, or imaging data)”. And all this vast information could be exploited in different applications.
In epidemiology, Big Data analysis’ applications can indeed offer innovative approaches in communicable diseases’ outbreak investigations, adding useful tools for more effective and cost-efficient ways to prevent and manage outbreaks. One such example is a study by the Karolinska Institute and Columbia University in response to the cholera outbreak in Haiti, where researchers have used data from mobile phone providers in order to have a better overview of population movements, and thus plan a better and more efficient action plan for managing the outbreak.
The positive impact of what Big Data has to offer is probably even more visible in the field of human genetics which traditionally had a rather slow progress due to the nature of the experiments needed to prove the field’s theoretical models (most of the experiments could not be performed due to ethical concerns). However, following the sequencing of the human genome at the beginning of our century, a brave new world has opened for human geneticists since a vast volume of raw data waiting to be analysed. Terms like “computational biology and medicine” enter the medical students’ curricula, and at least basic knowledge of database and system analytics is now a must in the modern bioscience researcher’s armory.
The genome-wide data analysis could indeed identify the causes of rare or other serious hereditary diseases, which would otherwise be difficult to identify and investigate because of their rarity. For example, the analysis of the Icelandic genetic database led to the identification of genes linked to human diseases, as cited by Kaplan.
Moreover, as Alemayehu notes, Big Data and the use of biobanks are very useful in drug development and they open revolutionary possibilities in the development of more efficient and safer drugs, in the direction of a completely personalised medicine and patient care. Furthermore, the use of smart mobile phone applications (like e.g. apps which measure the blood pressure via a smartphone screen) provide new field of direct-time monitoring of patients, as well as healthy persons, which provide again a unprecedented level of statistical information to researchers.
Apart from the science-related opportunities however, Big Data applications in healthcare could also lead to the reduction of costs. As Kaplan notes: multiple healthcare professionals, payers, researchers, and commercial enterprises can access data and reduce costs by eliminating duplication of services and conducting research on effective care. In other words, Big Data is good for the business too, since healthcare organisations may benefit financially by selling medical records of their patients, at least in the US context described by Kaplan.
By browsing on tech-related articles, blogs and webpages one could find even more current, or futuristic applications of Big Data which will make our lives easier, safer and healthier.
But what’s the price for this? I’ll try to analyse some of the negative aspects of Big data applications in healthcare in my next post.