Cloud computing is rapidly advancing healthcare on three important fronts.
First, according to Mathew Soltis, vice president of cloud solutions at GDIT, is how it improves healthcare research. The cloud enables the aggregation and sharing of data in a given research area, accelerating the visualization and analysis of data, and therefore the development of remedies.
“The NIH is a good example of data sharing here around COVID. They have a common platform, where researchers can come together and share data in a common standard, a common infrastructure, ”Soltis said on Federal News Network Cloud Exchange. Previously swapping hard drives or snail-like downloads just delayed things, he said. Now, cloud deployments “speed up search results.”
The second area of cloud-induced improvement, Soltis said, is how it facilitates compliance with a myriad of healthcare requirements, such as privacy under HIPAA. Basic cybersecurity also improves under a well-designed cloud implementation, he added.
“What we are seeing now is that many cloud providers and service providers have raised the standards,” Soltis said. “So if you want to use data or access a cloud infrastructure, it is now HIPAA compliant or can support your HIPAA results. It advances the cyber posture of a lot of customers.
Third, how the cloud enables new ways of delivering healthcare remotely and thus improves outcomes. For example, cloud-hosted data linked to electronic health records makes it easy to interoperate and access EHRs from anywhere, Soltis said.
Leveraging cloud computing comes with challenges, Soltis pointed out. A central question is how to manage and govern the large amounts of data that characterize health information.
“When we talk to federal customers, over 40% of them experience data migration issues,” Soltis said. Beyond any technical challenge are questions of data ownership, who will use the data, who in sharing arrangements pays the costs of the cloud and who is responsible for backups.
Key, Soltis said, “has an official role to own, manage, charter, chaperone and govern data.” Namely, the data controller.
But the CDO organization needs to partner with other stakeholders. When the CDO “sits at the same level as the technology and the mission owner and the application owner, it works best,” Soltis said.
On the technical side, questions arise about how to design an architecture for data lakes, dealing with mixed structured and unstructured data, and the most economical ways to prioritize storage configuration.
“If that infrastructure is in place with your architecture, then you can perform higher level activities such as machine learning, artificial intelligence and data visualization,” Soltis said.
Success depends on putting these elements in place, he said, but additional strategies can provide shortcuts for health agencies.
For example, look at how practitioners in other fields have done it.
“Sometimes in parallel industries things like high performance computing, anomaly detection, image recognition – there may be other agencies or organizations that do that,” Soltis said. “Some of the intergovernmental communities have really succeeded here, looking at these use cases, where you can apply this technology and this solution to health data.”
The specific strategy adopted by major organizations, he added, sees data as the primary focus and moves data to the cloud first, before applications.
Entrepreneurs can help you too. Soltis said that GDIT’s secure, cloud-native data reference architecture applies in many circumstances. He cited the Indian Health Service, which is modernizing its EHR system to integrate the cloud.