Big Data has become one of the most popular buzzwords throughout many industries. But how does it fit into healthcare? There has been a rapid increase in the amount of data we generate in our daily lives; so much, in fact, that it has become known as “Big Data” and it is used to improve efficiency and productivity of businesses. This could soon become the case in healthcare too, where the power of Big Data is used to predict health epidemics and, in some situations, provide early diagnoses for individuals. So, is it ethical to use Big Data to improve healthcare for the masses?
There are several parties to consider here – the healthcare providers, patients, policymakers and engineers. Currently, healthcare providers want to give patients the best care they can so, according to a KPMG partner, most healthcare providers prioritise spending on new equipment over cybersecurity. This means that they are unlikely to upgrade existing security because, without proper equipment present in the medical facilities, patients would receive lower quality treatment and thus negatively affect their reputation and revenue. It goes without saying that patients want to receive the best healthcare they can afford and expect their data to be kept confidential. In the case of most NHS patients, they don’t have much choice in how their data is secured; however, patients who use private practices can move to a practice that takes better care of them and their data.
Is prevention better than cure?
Application of Big Data in healthcare industry addresses two vital challenges; firstly, data analytics can not only assist the doctors in personalised treatment but also prevent the onset. Secondly, according a recent report, using Big Data promises NHS an increase in efficiency up to 60% whilst saving approximately GBP40 billion annually. Are these two benefits justifiable to implement Big Data in healthcare?
Let’s momentarily focus our attention to sepsis, a fatal condition that causes 750,000 deaths each year in the United States alone. Sepsis is difficult to diagnose and leads to death in a matter of hours. However, a study by Stanford University demonstrated that using Big Data revealed the potential for the creation of a simple diagnostic test, which could save countless lives. Imagine what else Big Data could help us achieve within the healthcare sector. Nevertheless, the use of Big Data faces criticism, predominantly from patients who are reluctant to disclose personal medical information.
Hence, the options for action are conspicuous. Firstly, healthcare providers and engineers could take the necessary steps to create efficient and accurate data analytical systems.
This is justifiable according to the utility principle as the economic benefits to medical enterprises and the advantages to patients from early diagnosis result in the greatest happiness to the majority. Furthermore, upon undertaking the Hippocratic oath, medical practitioners swear to prevent illnesses, as it is better than cure. The Engineering Council’s codes of conduct oblige engineers to prevent avoidable danger to health and adverse impact on society. Hence, the implementation of Big Data ensures that both practitioners and engineers adhere to their professional codes of conduct.
However, it could be argued that this theory disregards the pleasures of the minorities. Thus, using this framework to justify the use of Big Data could result in the exploitation of minorities that may not agree with this proposition.
The Kantian theory provides the view of the minority of patients. Kant’s first categorical imperative implies the equality postulate, which is the prescription to treat all people with equal concern and respect. According to this even the minority should be treated equal to the majorities. This could potentially lead to a solution that considers both parties where Big Data could be implemented based on the data provided by only those who consent.
What if someone else had access to your data?
Imagine a complete stranger using your medical record to file false insurance claims or to buy medication to sell on the black market. An annual survey found that the number of healthcare organisations reporting criminal cyber attacks had doubled between 2009 and 2013. Engineers need to be part of the solution by proactively working to increase the security of the software being used and raise up any major concerns to their employers.
Healthcare providers have to make a choice on how they spend their budget. Should they spend their money on cybersecurity, neglecting the purchase of new equipment? Should they spend all their money on new equipment? Or should they continue spending the same proportionately? Based on the post-utilitarian perspective, medical providers should prioritise cybersecurity over the purchasing of new medical equipment according to the principle of prudence. Furthermore, according to the principle of justice, policy makers and healthcare providers should treat the personal data they are responsible for in the same manner they would want their personal data to be treated. A double effect of this, though, is if healthcare providers allocated all funds towards increasing cybersecurity, there would be no money to spend on new equipment, resulting in lower quality care for patients.
Even then, patients and other stakeholders would not necessarily understand or be aware of the new policy implementations. Following this, what degree of hacking occurrences need to occur before proper action is taken to prevent it?
On the other hand, another approach to this issue would be to essentially spend no money on security and instead allocate all of it to the medical equipment. While this may provide short term benefit to the medical providers, in the long run they would be negatively affected as more and more medical providers around them follow the new big data trend and implement more effective measures in improving healthcare services. Furthermore, how does one justify having better cybersecurity when the cases of big data files being hacked are infrequent and largely spread out? In this sense, is it really worth spending on new equipment instead of on better cybersecurity?
Considering our arguments, is the use of Big Data in healthcare worth the risk? What are your thoughts?
Group 9: Kevin Fernando, Subodh Sardeshmukh, Dave Sanjay Shah & Alasdair Stringer