The healthcare industry handles vast amounts of sensitive patient data on a daily basis. From electronic health records to medical images and test results, physicians and medical staff rely on the secure and efficient storage and retrieval of this data to deliver quality care. However, with growing data volumes and strict privacy regulations, healthcare organizations face unique challenges in managing their data storage needs. This article explores some of the key considerations for healthcare data storage and strategies that providers are adopting.
The Growing Volume of Healthcare Data
As medical technology advances, the amount of data generated per patient is exponentially increasing. Where patient files were once limited to paper files, digitized records now include things like high-resolution medical images from CT scans and MRIs, genomic sequencing data, lengthy notes from patient visits, and data from connected medical devices. It's estimated that the average patient record will grow to over 1 million pages by 2020. Additionally, with more healthcare facilities joining electronic health record systems, the overall volume of digital healthcare data is expected to grow at a rate of 48% annually. Storing and managing petabytes worth of patient information presents a significant technical and financial challenge for most healthcare organizations.
Compliance with Strict Privacy Regulations
Healthcare data is considered among the most sensitive types of personal information. As such, providers must abide by stringent privacy laws like HIPAA in the US which regulate the use, access, storage and transmission of protected health information (PHI). Non-compliance can result in heavy penalties. When storing patient data, healthcare organizations must ensure data is kept secure and private at all times through practices like encryption, access controls and activity monitoring. They must also be able to provide proper oversight and respond quickly if a privacy breach occurs. Meeting these regulatory requirements while scaling data storage capabilities is an ongoing effort for healthcare IT teams.
Rise of the Hybrid Cloud
As on-premises storage solutions struggle to keep pace with data growth rates, many providers are moving some or all of their healthcare data to the cloud for improved scalability, mobility and economics. However, migrating sensitive patient records off-site poses security risks that have slowed broader cloud adoption in healthcare. As a compromise, hybrid cloud architectures that combine on-premises and cloud-based infrastructure are gaining prominence. This allows frequently accessed data to remain locally stored and secured while archive data can be cost-effectively housed off-site. It also enables healthcare workers to securely access patient records from anywhere through cloud-based portals and apps.
Leveraging Analytics on Healthcare Data
Besides just storing healthcare files, providers are looking to extract value from their troves of digital patient data through analytics. By gleaning insights from clinical, financial and operational data sources, healthcare organizations aim to improve outcomes, streamline workflows, cut costs and boost revenue. For example, analyzing patient records and diagnostic images can help identify at-risk populations, determine best treatment practices and reduce readmissions rates. Analytics also play a key role in population health management strategies. However, extracting useful analytics requires properly structuring vast amounts of disparate healthcare datasets - another factor driving investment in more sophisticated data management platforms.
Technologies Supporting Healthcare Data Storage
To better manage exploding data volumes while maintaining regulatory compliance and enabling secondary uses of data, healthcare organizations are evaluating new technologies:
- Object storage solutions replace traditional file and block level storage with a more scalable architecture and built-in data governance. This allows petabyte-scale capacity at lower costs.
- Unstructured data platforms provide a single integrated environment for multiple data types like text records, DICOM images, genomic sequences etc. Data can be efficiently stored, accessed and analyzed without moving between siloed systems.
- Artificial intelligence (AI) and machine learning (ML) are being applied to automate tasks like extracting metadata, transcribing clinical notes, and classifying unstructured data. This eases data preparation burdens for analytics.
- Hyperconverged infrastructure (HCI) combines computing, storage, networking and virtualization resources into an on-premises appliance for fast deployment of private clouds. HCI streamlines healthcare datacenter management.
- Software-defined storage decouples storage software from proprietary hardware, enabling elastic scaling, high availability and mobility of data and applications across hybrid IT environments.
Conclusion
As patient data volumes continue to balloon, finding a long-term, cost-effective solution for data storage and management will be crucial for healthcare providers to keep functions running smoothly. Emerging technologies are helping address these challenges by facilitating more scalable, compliant and analytics-ready storage frameworks. By optimizing their data infrastructure strategies, organizations can better support high-quality care delivery while also unlocking new insights from healthcare big data.