Any high-performance electronic medical records system needs access to organized, secure, and accurate data. Healthcare practices and businesses have seen huge demand for scalable, reliable data storage solutions that integrate with records automation processes and expedite the way practitioners and other medical staff access patient information.
One of the many post-pandemic impacts has been that healthcare providers have needed to shift how they communicate and deliver care to their patients, with automation in healthcare and HCC risk adjustment technology tools being a significant and sustained transition. In this guide, we’ll discuss the three primary data storage options–exploring the pros and cons of each–as an insight into how data storage solutions can provide cost savings to healthcare facilities while making records easier to access.
Healthcare providers use varied pieces of data to ensure the care, procedures, medications, and recommendations they make to their patients are tailored to their needs. Practice managers, owners, and senior executives also rely on data to produce accurate billing or claim information and ensure they fully comply with HIPAA regulations. This data could include:
The nature of each aspect of healthcare data means it must be secure, confidential, or anonymized while being filtered, categorized, and stored in a way that is immediately available.
We mentioned three core alternatives medical companies may choose when deciding the best way to manage their data storage requirements. These include keeping data on-site through a localized data center, using a cloud-based solution, or implementing hybrid data storage combining several data management services.
Storing data on-site has benefits, giving the practice or organization complete oversight about how data is managed and who has access to specific data types. Hospitals, clinics, and facilities can also use various technologies, such as private cloud storage, for security.
The challenge may be that implementing a custom localized data storage center requires significant investment in hardware and resources, with ongoing expenditures linked to maintaining a server space with a regulated environment and sufficient servicing and updates to remain fit for purpose. It can also be tricky to scale on-site data centers, when a facility may need to revisit its data management approach if it reaches capacity.
The next option is to use a cloud-based data storage strategy, with providers offering low-cost storage space at a fraction of the outlay of designing and setting up a private data center. Medical service providers pay for the data storage volumes they need, and scaling is easy if patient numbers, the services offered, or the magnitude of data used in automated healthcare management increases.
While cloud-based storage has advantages in terms of remote connectivity and off-site accessibility, there are risks–particularly when considering the strict requirements around data protection and ensuring all confidential healthcare data is under rigorous control. Public cloud-based storage is often considered unsuitable for healthcare businesses due to potential issues such as lost data, connectivity downtime, and hacking, putting patient data in an exposed position.
A third and final solution involves a mixture of the options we’ve looked at, combining on-site servers and cloud-based storage to manage data inflows and outflows while integrating other software or applications that provide on-demand access to authorized system users. Storing data on-site offers the assurance that data is protected and compliant with HIPAA data protection regulations while delivering the scalability of cloud storage as a cost-effective middle ground that requires fewer resources and computing power than a standalone data server center.
Setting up failure response strategies, regular data backups, and routine maintenance provides a safeguard against system downtime or data losses. However, medical service providers are advised to ensure that their hybrid data control networks are thoroughly tested before rollout to verify that solutions provide the right level of data capacity and interoperability with data-reliant systems.
