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Big data ‘set to lower healthcare costs’
The implementation of advanced big data analytics solutions in the healthcare sector could help significantly lower costs in the marketplace by changing the way treatments are developed, prepared and delivered.
This is according to a new study by Lux Research, which noted that soaring costs are a problem that is continuing to plague the industry, as previous efforts to address this have had little impact.
In the US, for example, it stated the introduction of the Affordable Care Act has had limited success in tackling the problem, while in the UK, it has been reported that the government is unlikely to direct additional funding towards the NHS in the upcoming Autumn Statement, despite political pressures to create a full seven-day service.
However, the emergence of new, advanced big data analytics solutions can help healthcare providers reduce their costs without resorting to cutting services, Lux stated.
Mark Bünger, Lux Research vice-president and lead author of the report, titled 'Industrial Big Data and Analytics in Digital Health', said: "Whereas solving many past healthcare problems seemed to be a matter of scientific discovery, health policy, or adequate funding, today's most pressing problems are due to a lack of information – or lack of understanding of what to do with it."
He added that big data solutions that meet these challenges are already delivering measurable benefits in terms of both cost and patient outcomes, while partnerships between large technology providers, pharmaceutical firms and academics are bearing fruit.
Among the findings highlighted in the report, Lux noted that big data can help providers offer more personalised therapies, which have the potential to greatly enhance the fight against some of the most severe diseases.
It stated that by studying molecular biomarkers and genetic profiles, cloud-based analytics enable decisions to be made faster, resulting in better outcomes and reduced costs.
Coupling big data with artificial intelligence (AI) also holds a great deal of promise for the healthcare sector, as it offers a more efficient way of analysing very large data sets.
Applications for this in the healthcare sector may include radiology, where AI can help doctors review patient images and CT scans and spot anomalies that may be missed by a human eye.
AI also has a key role to play in the development of therapeutic and caregiving robots, as well as other aids that help monitor cognitive function and diagnostics, Lux stated.
Elsewhere, big data analytics can also help hospitals cut costs by, for example, helping optimise resource allocation, both when it comes to direct patient care and other activities.
Lux added: "Cost gains come from semi-automated diagnostic tools and decision-support algorithms that help focus expensive interventions, medical equipment, and caregivers' time on the patients who need them most."