Data plays an increasingly crucial role in all aspects of healthcare. Source: Shutterstock

Data is now vital in healthcare — but how’s it being managed?

One of the key takeaways from the ongoing Covid-19 global outbreak is the importance of leveraging the data available.

At a time where different healthcare agencies across the world have to make sure that all actions are regulated, aligned and synchronized in efforts to contain the virus spread, data becomes just that much more instrumental.

Having data that is accessible, of quality, and most importantly secure has helped agencies around the world receive updates, communicate information and pool intelligence to help with ongoing research.

As a result, patients have been recovering at a higher rate, precaution measures can be thoroughly structured to prevent infection and improved healthcare services can be provided.

Such practice is not new, by the way. The industry has long been relying on data — mostly collected by electronic medical records (EMR) —  to gain in-depth insights on patients’ health conditions and even predict future medical possibilities.

Now, with advances like artificial intelligence, machine learning, and the Internet of Things, data can be pooled from various different sources to create a more integrated information network system.

As these information networks grow and transcend boundaries, new challenges and concerns emerge, stemming from the fact that the digital paradigm is ever-evolving. The industry needs to identify current issues, risks, and threats, that will not only hinder revolution and progress but also endangers the safety of patients and corrupts historical data.

For starters, healthcare data is growing in tremendous volumes across the globe, which poses the question: how to best manage and process such a heavy mass of data? As the volume grows, the distribution of data also increases. Is there a way to locate and extract all this data at will?

Not to mention, as data gets more distributed, different compliant requirements and security policies follow. Attending to different requirements is time-consuming. With new workloads on the horizon and limited IT infrastructure, does the industry have the right solutions at hand to withstand the management of increased data inflow?

Next, the industry must also think about intensifying cyber threats and cyberattacks that may come with this growth of data. By now, it’s clear that data is highly valuable — which is why it comes at the cost of cybersecurity. Just last year, New Jersey’s Hackensack Meridian Health suffered a ransomware attack that threatened the primary clinical systems on its network.

Before that, 11 threats were found in medical software by the US cybersecurity researchers who highlighted that not only can data be stolen and compromised, it can also be manipulated.

In these scenarios, the first thing that the industry needs to pay attention to is security measures. Data — regardless of age and size — must be protected. Blockchain is easily positioning itself as a key solution to ensuring data is encrypted and hard to manipulate.

Combining the solution with on-cloud cybersecurity features can profoundly elevate data protection levels. Coupled with artificial intelligence capabilities, the system can be trained to monitor all changes that occur within the storage and computing environments, and activate defense systems when necessary.

Agility is also another important component in augmenting the security and longevity of data. Automated security solutions can help support an agile approach to cybersecurity where protection can be regulated automatically with every change in each data application environment. Machine learning can also be used to ward off possible breaches within and beyond the network perimeter.

Using relevant historical data of network activity can help the machine learning better predict risks and threats before they happen. The key is to create a security first information network environment that follows basic standards of regulation that can be applied worldwide. When it comes to healthcare data, an automated and integrated approach to data protection is key.