Big data, algorithms, statistical models and other such tools have become omnipresent concepts in our daily lives, inextricable from any field and sector of society. Their dominance has been marked with the continuous demand for greater research into artificial intelligence and the better incorporation of such techniques into our systems of public governance. But is the use of big data confined only in the fields of decision – making, or is it rather cross – sectorial with increasingly frequent applications in the field of medicine and public health?
Over the past decades, there has been increasing eagerness about the potential usefulness of these large quantities of data in transforming personal healthcare, clinical care and public health in general. Despite the questions this might create at first, the alignment of big data and heatlh is here to redefine all conceptions of medical care.
The complexity of handling big data systems stems from their nature: the massive amount of combinatory data, which refers to multidimensional rather than single – defined concepts leads to challenges in their application across all fields. The recent explosion of new platforms, methods and tools in storing, structuring and comprehending such data has subsequently led to the development of the field of big data analysis and the increasing desire to understand how these data can be employed across sectors.
The expansion of this field has greatly benefited healthcare professionals. The large amount of data allows them to collect information from electronic healthcare records, patient summaries, social media genomic and pharmaceutical data, clinical trials and information from well – being, behaviour and socio – economic indicators. For instance, reports suggest that the US healthcare system alone stored approximately 150 exabytes of data in 2011, with the potential to collect even more.
The combination of individual with heterogenous data coming from different sources significantly improves the ability of healthcare professionals to predict and better understand the causes and outcomes of diseases, test the effectiveness and applicability of drugs for precision medicine and systematically enhance disease prediction and prevention. The potential benefits of the healthcare system and individual patients is enormous, should the correct data be collected and analysed using the correct tools and methods.
The study on Big Data in Public Health, Telemedicine and Healthcare of the European Commission carried out in 2016 suggested that big data can significantly contribute in “increasing earlier diagnosis and the effectiveness and quality of treatments” through the discovery of early signals, disease intervention, reduced probability of adverse reactions etc.
Big data also has the increasing potential to provide new insights into factors that lead to or that induce the escalation of disease. Public health institutions now have the possibility to better engage with individual patients more closely and acquire personal data from mobile health applications and devices, which will later be analysed and used in real – time to interpret changes in behaviour that can potentially reduce health risks and lead to the optimisation of health outcomes. The correct analysis of such data can also lead to greater precision of medicine, after detecting heterogeneity of patients and discovering individual needs because of genetic variations.
The greater benefit of the contribution of big data in healthcare is the increase in efficiency and improvement in cost containment of the healthcare system. The more precise the prescribed medicine and medical treatments, the more efficient they will be which in turn will lead to the emergence of a more specialised and skilled healthcare personnel and greater cost – minimization.
Despite the significant benefits and much – desired applications, a challenge lies in the heart of big data application: uncertainty. This complicates matters more than it simplifies them. Yet, the great array of methods and tools provided by data analysis turns these big data into more of a blessing, than a curse.
In an era when everything seems quantifiable and easily measured, big data has come to dominate every aspect of our lives. This, however, doesn’t mean that the field of big data analysis doesn’t experience its own challenges; which is exactly what happened with the recent outbreak of the coronavirus.
It was the small Canadian BlueDot company, with just 40 employees, which first sent the signal for the outbreak that soon turned into an epidemic on December 31st. Despite not providing information about the precise location of this virus, BlueDot paved the way to other healthcare monitoring companies to acquire more precise and hands – on data.
The 2019-nCov may be the most closely observed virus of the last decade, with the exception of the Ebola virus outbreak back in 2014 – 2016. Public health officials have at their disposal an array of data analysis tools which help them to better understand the causes of the virus, the immediate and long – term symptoms, possible treatment methods designed for each genetically diverse human and the virus’ movement as well as be able to forecast the movement of the virus. The outbreak, which has been likened to an epidemic of staggering size, is closely monitored on an international level all thanks to the plethora of disposable data across platforms and continents.
Data from different sources, like sentinel data, additionally enable data analysts to map the movement of the virus and locate inflicted areas, which in turn allows decision makers to employ specified treatment and containment methods for the virus and infected people. Business intelligence tools, like the Advanced Analytics Software (SAS) and methods from other vendors enable the tracking and close monitoring of the virus, which in turn gives healthcare professionals the time and data needed to produce an effective treatment. Geographic information systems (GIS) are also important in tracking how viruses spread through space and time. Decision makers at the World Health Organization, Global Health Surveillance and Centers for Disease Control have at their disposal an array of such and even better interfaces, which provide them with the necessary information on how to track, monitor and better understand the behaviour of such major viruses.
It becomes evident, therefore, that Big Data is beginning to revolutionize not only healthcare, but also public governance on an international scale. The analysis of big data has opened up paths, has provided valuable information and has paved the way for better – quality incorporation of acquired information in systems of governance and decision making, which have an immediate effect on citizens.
We live in fast – moving times, when the stakes of leaders’ decisions are high and when possessing the necessary information is a key for political survival and provision of public goods. Science and technology offer a host of invaluable tools which can deliver greater precision and more effectiveness in decision – making and crisis management.
Data are no longer just figures, statistics etc. They are indispensable tools, strategic assets and the new possible economic assets which lay at the foundations of our constantly evolving economic systems.
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Originally published at Traii Leoni (https://www.traileoni.it/2020/04/big-data-and-healthcare-a-greater-challenge/)
