Since the NHS began in 1948, life expectancy has increased on an average by a decade, and chronic diseases such as heart disease and diabetes have risen dramatically thanks to rising obesity levels.

It is no secret that this is putting a major strain on the NHS – A&E waiting time targets have been missed every month since July 2015, and the NHS net deficit for the 2015/16 financial year was over £1.8bn.

However, the healthcare crisis has coincided with the technology revolution. The cost of 1GB of data has dropped from £30,000 to 7p between 1981 and 2010, and a range of analytics solutions have come to market.

Can big data help solve the NHS’ problems?

Early adoption

The NHS has only used big data in pockets so far, but there have been some interesting and effective use cases.

A £1.3 million research project by NHS Scotland is seeing it collect patient level data and implement big data analysis techniques to get a better understanding of the warning signs of diabetes.

The objective was to create computer algorithms that help doctors predict which people are most at risk and likely to benefit from targeted intervention, and it is estimated that this will lead to £200 million in savings, and result in a 30% drop in limb amputation over four years.

Meanwhile the National Institute for Health Research Health Informatics Collaborative (NIHR HIC) are producing an anonymised patient level data set made from five NHS Trusts.

The benefits of big data are clear, and it has become much easier for organisations to collect and store this level of data from its customers and stakeholders.

The challenge is to convert that data into information that can help improve operations.

The use of data analytics

This is where the implementation of data analytics is required, and organisations can choose from a range of solutions in the market that can cater for the even most niche areas of their business.

These analytics solutions can give a business a view of customer behaviours or consumer trends, and allow them to cater their products or services to meet those needs more effectively.

An example would be in the management of patient flow and ward capacity in hospitals during the notoriously busy winter months.

[easy-tweet tweet=”Predictive data analytics and risk scoring has the potential to shed light on patient flow and hospital demand” hashtags=”Data, Analytical”]

Predictive data analytics and risk scoring has the potential to shed light on patient flow and hospital demand, allowing the NHS to make informed decisions regarding allocation of resources and significantly improve the NHS’ ability to navigate this busy period.

The barriers to implementation

However, despite the potential of big data and data analytics, a seamless analytics offering requires heavy investment from the business involved.

It is not a simple case of an analytics solution plucking the raw data from the sky, the process is reliant on IT infrastructure, the organisation of data, and the flow within the business as a whole.

The challenge for the NHS is its complexity – it consists of 853 for-profit and not-for-profit independent sector organisations, providing care to NHS patients from 7,331 locations across England alone.

Therefore utilising big data and analytics would require a huge financial, planning and design operation to ensure the organisation has the right infrastructure to allow the effective flow of data across the organisation.

This is not forgetting the need to design effective systems for the management and access of that data, and implement effective training processes for staff to work with these technologies – it is certainly not something that will happen overnight.

The data protection question

In 2018 there will be a new challenge, with the 2018 European General Data Protection Regulation (GDPR) coming into place in the UK and forcing businesses to comply with stricter governance of the sharing of data.

A major concern for the NHS will be that these regulations hamper the flow of useful data within the organisation, and make it even more difficult to utilise.

Yet even more significantly it will require a financial investment, operational changes and effective training of staff on how to handle data.

It inevitably raises the question of whether the NHS can afford to invest the time and capital required to reap the rewards of big data when senior decision makers remain in a constant battle to keep their heads above water.

Is it worth it?

However, the benefits of big data are clear, and in the case of NHS Scotland, you can see its long-term potential to drive down costs across the NHS.

There is also significant faith in this big data movement across the NHS, evidenced by the decision of the Engineering and Physical Sciences Research Council (EPSRC) to fund five research centres around the UK that will apply analytical methodologies to assess healthcare sector concerns.

Given that the NHS will be investing in its data management as a result of GDPR, I would argue that it is in-fact the perfect time for the organisation to be investing into effective data analytics solutions that work across all of its Trusts.

Modern day computing power and the drop in the cost of data storage mean these solutions are more accessible than they ever have been.

It has the potential to revolutionise the way we run health and social care in the UK, and it is time for the NHS to embrace this opportunity.

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