Budgets, and the importance of balancing the books, are an ever-present issue in healthcare. With costs rising around the world, and budgets limited whether in insurance- or state-funded systems, care providers are under increased pressure to manage costs effectively. Big data analytics may just provide the means that they have been seeking, and also bring improvements to clinical care and patient safety.
The prize is huge. Estimates from SAS Institute suggest that in the UK alone, healthcare could benefit from big data and the Internet of Things (IoT) to the tune of £16 billion between 2016 and 2020. Studies suggest that between 4% and 15% of healthcare funding is being improperly used, suggesting that budget optimization could be a key beneficiary of analytics. Detecting fraud and errors alone could have huge potential, given the amount that can be creamed off in individual fraud cases.
Fear overshadows healthcare benefits
But there are likely to be many challenges to using big data analytics in healthcare.
Primarily, the data in healthcare is often very sensitive. Not only is patient data personal, but it often contains information that many people would prefer others not to know: details of their illnesses and treatment. With the stigma that is still attached to many conditions, including mental illness, this is perhaps not surprising. Healthcare providers often do not have a great record of keeping data safe and secure, and as a result, patients are understandably wary of allowing data sharing.
At present, in many people’s minds, the risks of allowing sharing of healthcare data outweigh the benefits. But policy-makers have a key role to play in changing this. They need to overcome this fear among both patients and clinicians, not to mention the administrators who will be held to account for any lost or leaked data.
Shared success stories
One way to do so is by sharing stories of success and reassuring people of the benefits. And it may be significant to note that most of the successful use cases around big data analytics do not require much, if any, sharing of personal and sensitive information. They include, for example, improved laundry management, resource tracking applications, improved administration, as well as better tracking of patients. The point is that big data analytics does not need to include patient-specific and sensitive data, and also that the data does not need to be stored. It is a good business case to start with a non-sensitive area, build competence around big data analytics and realize obvious benefits.
Improving clinical and cost effectiveness
Healthcare reforms around the world have long aimed to improve clinical and cost-effectiveness. The target is always to get ‘more bang for your buck’: in other words, to get the maximum benefit from every dollar spent. Is it possible that big data analytics holds the key to this puzzle?
The potential to analyse massive amounts of data, whether administrative and financial, or clinical, in a short space of time, means that healthcare systems are now able to make decisions about the most effective course of action, supported by evidence. Whether that decision relates to an abnormal pattern of spending, and hence fraud, or the course of treatment that best fits the patient concerned, the potential is there.
The difference now, from many earlier budget optimization initiatives, is that there are no technical issues in balancing patients’ needs against costs. Big data analytics can both optimize budgets and improve patient care. It really is a win-win situation.
To learn more and discuss your big data analytics steps, meet us in Rome during the Analytics Experience Conference. Hope to see you there!