Treat Your Data Right - It Could Save Lives

Big data is all around us, but our understanding of how to make the most of it is often left wanting. Proper use and analysis of data can help improve the way we work by making better-informed decisions.
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Big data is all around us, but our understanding of how to make the most of it is often left wanting. Proper use and analysis of data can help improve the way we work by making better-informed decisions. This use of data is perhaps most critical within health services, where decisions regarding human life are frequently made - and better insights from data can help save lives.

The newspaper front pages regularly highlight shocking activity from the UK's National Health Service. While the issues are so often over-hyped by the papers, it does highlight some very real issues within the NHS, which could help be resolved with better analysis of data.

We recently heard about the backlog of patients at Belfast's Victoria hospital along with issues at Cardiff's University Hospital with an influx of A&E patients.

While both of these incidents have been described as isolated incidents, they result from unforeseen surges in demand. But, given that the NHS missed its four-hour A&E waiting time target in January, it does raise an important point about how to use data and information in the best way to help patients get the necessary care.

Serious spikes in demand may be infrequent, but it is imperative that the NHS is prepared. These events are just the latest in a long line of NHS mismanagement and mistreatment scandals. The effects prove that inaccurate, unreliable, fragmented and outdated information can have a big impact on patient care. The NHS is a relentless producer of big data but this information is underused, which costs lives. By using data and information in the right way, the NHS can plan ahead and allocate resources effectively, removing the need for further support.

In healthcare, data has the power to inform best practice patient care guidelines and identify the risk factors involved in certain treatments. However, the biggest impact for A&E in particular is analysing data to make better decisions based on evidence. This can lead to prompt intervention that prevents illness in the first place. It also creates a more informed system of integrated care in the community among GPs and social services when people do fall ill. This insight then helps prevent unnecessary visits to A&E. SAS recently carried out research, which discovered that one in 10 people admitted heading to hospital for treatment when a visit to the doctor would have sufficed.

In addition, analysing all available data, including external factors like the time of the year and weather, coupled with analysis of factors within the hospital and understanding of patient conditions, allows hospitals to better forecast demand and plan how best to allocate resources like staff and beds. Prevention and alternative pathways will ease the pressure on A&E.

According to the CEBR report on 'Data Equity - Unlocking the value of big data', the use of big data analytics across the healthcare sector could deliver additional revenues of £14 billion from 2012 to 2017. It would also give the NHS ability to plan ahead and be better prepared for all eventualities, reducing waiting times and preventing further incidents. The solution to this lies outside of their walls.