Big data has the potential to radically change the way clinical healthcare is done. Though in many industries the term ‘big data’ feels like a vacuous buzzword, big data in healthcare has huge potential
As with every new technology, there are steep hurdles to overcome for big data to reach maximum saturation, maturity and real-world efficacy within this industry. We are already seeing healthcare organisations consider how they can harness big data to benefit clinical study.
Most businesses and organisations across all sectors realise that to sustain success, they need to embrace digitisation and technological advancements. This is especially true for the healthcare industry. Harnessing the power of big data has the potential to fundamentally transform the healthcare industry.
Processing and analysing clinical data can speed up the rate of drug discovery, development and approval. Utilising big data can allow us to create more focused, effective clinical trials.
Ultimately, if we embrace big data to its full potential within healthcare organisations, we could see a wave of highly effective new drugs, improve patients’ health and at the same time enable cost savings for the NHS.
Big data in clinical trials
Data is key in clinical trials, even at the conception stage. In almost every trial, routinely collected data is used to gain a better understanding of how a drug or therapy could affect a patient. The data sources can be wide ranging from electronic health records (EHRs) to public registries or scientific research.
In order to gain an even better understanding of how experimental drugs and treatments work, clinical trials need to embrace data from outside the conventional sources. Much of this can come from consumer technology. Whether that is health data from Fitbits, data from supermarkets and takeaway apps showing food buying habits, there is are masses of unused data that could be useful to get a 360 degree view of patients who take part in clinical trials.
The more we know about patients, the better we can conceive treatments that are personalised to specific subsets of a society and patient needs.
There are two clear obstacles impeding the integration of big data into the sector. Firstly, we would need patients and companies to be willing to let us use their data. Secondly, there is the issue of trawling and analysing these huge data pools to attain the information most relevant for specific clinical trials.
Using artificial intelligence and machine learning
Analysing the huge amounts of data we currently have within the health sector is a mammoth task. Though some of this data, will of course, need permissions beyond where we’re at today. Regardless, analysing such data is a task beyond the capabilities of even the best clinical minds. This is one of the doubts that is currently being aired.
But some solutions could be on the horizon with the rise of artificial intelligence and machine learning. Machine learning algorithms are nothing new. We encounter them daily, whether we realise it or not. Netflix use it to recommend shows, Amazon use it to offer products to buy based on your browsing and buying history. The same intelligent technology can be used within healthcare to analyse the vast pools of data needed to create clinical trials of the future.
How wearable tech could transform health care
The growing trend for wearables is one of the biggest transformations in personal health during the past decade. It seems almost everyone has a Fitbit or an Apple Watch on their wrist — from teachers to neuroscientist. As with all products created under the banner “the internet of things”, these devices collect huge amounts of data. Data that could be of massive use in clinical trials and personalised medicine.
From 24 hour blood pressure and heart rate monitoring, to the amount of physical activity done in the course of a week, all of this data can be useful in understanding how a drug or treatment can affect patient health. Though the devices currently on the market aren’t at a clinical standard, if we embrace big data in healthcare, it will be in tech companies’ interest to produce products that can be used for this.
How patient engagement and personal data are key to the future
One of the questions around using data in this way is how the public would feel. Recent Facebook controversies, and media coverage around the way Google and Amazon use our data have led some people to push back against big corporations using their data. May’s GDPR instigation has also helped bring personal data security into the forefront of public concerns. Maybe if people knew how it would be used in patient monitoring, to improve clinical trials and overall health, perhaps public opinion would change.
Why we need to embrace different, digital skill sets
If we are to create a healthcare sector built on big data, we need to incorporate different skill sets within our industry. That could mean hiring more data analysts. It could also mean that we need to hire more engineers to work with and create the machine learning algorithms we alluded to earlier. It could also entail hiring UX experts to create easy to use products. At the same time, people currently working in the industry may need to acquire a better understanding of how it all works.
This can create potential opportunities for upskilling. Whether through professional training courses, cross-industry collaboration or high-level apprenticeships, learning the skills necessary for future industry will become an essential part for people already working within the healthcare sector. At the same time, university courses will need to reflect the need for future skills too, so that the next generation have the requisite skills to be effective in a rapidly changing clinical environment.
Undoubtedly, we are going to see pushback from traditionalists, or those that have apprehensions towards technology. Especially those who have concerns over the safety of the data. Recent anxieties over Google’s involvement within the NHS spring to mind. Some of these concerns definitely need to be addressed, but collaboration of this sort may be necessary, at least at the outset.
A greater understanding that AI and machine learning are part of our future needs to be developed as soon as possible to allow big data to enhance this area. Not only will it permit for a more effective clinical experience — for both patients and professionals — it could create new opportunities. With the latest tech on board, our industry should become more attractive to the best young talent coming through our education system, potentially reducing the skills shortage gap.
We are at the cusp of significant change. The future of healthcare looks set to be exciting.