Why Healthcare Needs a Better Data Storage Strategy
The possibilities for data-driven healthcare solutions are endless, but as long as your organization lacks a proper data storage strategy, they will remain just that: possibilities.
This past decade has seen many major industries implement data-driven solutions. Amazon has revolutionized retail by building algorithms that predict customers’ purchases; ‘sabermetrics’ has transformed baseball into a data game; and big data has driven advertising to new heights. Unfortunately, similar strategies have yet to influence healthcare at a comparable scale.
So why hasn’t the world of healthcare adopted big data solutions? The issue certainly isn’t a lack of potential. As Forrester Research analyst Kate McCarthy recently asserted, “If we could do even half of [Amazon’s analytics function] in healthcare, it would allow us to reduce bad clinical outcomes, it would allow us to improve quality of care, it would allow us to, essentially, prevent disease manifestation."
In truth, healthcare companies haven’t delivered advanced data solutions because they haven’t invested in data storage infrastructure. With the right storage strategy, healthcare companies could provide 21st century solutions to patients in need.
Big data applications in healthcare aren’t purely theoretical: Explorys offers a cloud-based predictive analytics platform for monitoring disease trends, and other companies are developing similarly ingenious solutions.
Even so, the untapped potential of big data remains enormous. As TechTarget’s Kristen Lee notes, with the right data storage strategy, hospitals “could monitor a prediabetic patient, trend that person's data, and identify patterns in behavior that put them more at risk for moving into the actual category of diabetes.” This could help lower the U.S. population rate for diabetes from a staggering 9.3%.
Similarly, big data expert Bernard Marr writes that such an initiative might have been used to more accurately predict the Zika virus’ spread: “From a technological standpoint, we already have everything we need to leverage big data to quickly and effectively develop vaccines for new viruses such as Zika… Now what we need are platforms and systems to get this data into the hands of those who can develop solutions before a public health emergency develops.”
For these potential breakthroughs to become realities, however, effective data storage strategies must be put into place.
Regardless of whether healthcare providers turn to the cloud or more traditional infrastructure, their approach to data storage should prioritize the ability to incorporate data from multiple sources and in multiple formats. Healthcare analytics (especially functions like disease tracking) rely on such functionality, since data will be compiled from hospitals in different regions of the state, country, or globe.
A healthcare data storage strategy should also allow for easy scaling with capacity planning software from vendors like TeamQuest. The amount of data being analyzed will likely vary depending on certain key factors — skyrocketing during periods of disease outbreak and plateauing during months of relative health — and healthcare companies should vary their spend accordingly.
Finally, organizations throughout the healthcare space must implement effective predictive analytics platforms to utilize the data stored. Otherwise, these advanced storage capabilities will fail to deliver on the end goal: improving quality of care and preventing widespread disease.