MediQuant Expands DataArk to Help Health Systems Better Manage Legacy Data
Enhanced platform gives healthcare CIOs greater visibility into data retention, storage costs and compliance risks while preparing legacy information for AI-driven analytics
Healthcare organizations are facing growing pressure to control data storage costs, reduce compliance risks and manage increasingly complex technology environments. MediQuant is expanding its DataArk® platform to help health systems address these challenges through a more comprehensive approach to data lifecycle management.
The next generation of DataArk moves beyond traditional data archiving by giving healthcare organizations greater visibility into the legacy information they retain, including its age, usage and ongoing storage costs. The expanded capabilities are designed to help IT, finance and compliance leaders evaluate whether retained data aligns with organizational policies and determine what should be preserved, where it should reside and when it can be responsibly removed.
As hospitals retire outdated applications and modernize their technology infrastructure, they must continue preserving essential clinical, financial and operational records for patient care, regulatory requirements and audits. However, without a clear understanding of what data they hold and how it is being managed, organizations can struggle to apply retention policies consistently.
The result can be unnecessary storage expenses, increased security exposure and additional operational complexity.
“Not all data is created equal, yet many organizations still store it as if it were,” said Jim Jacobs, president and CEO of MediQuant. He noted that rising storage and software costs, combined with ongoing financial pressures, make it increasingly important for health systems to evaluate whether data is being retained in the right place and at the right cost.
Moving Beyond Traditional Archiving
The expanded DataArk platform brings together several capabilities to help health systems manage legacy information more strategically.
Greater visibility and policy alignment: Organizations gain a centralized view of archived applications and datasets, including their age, usage and cost. This information helps IT, finance and compliance teams assess whether retained data meets established retention requirements.
Continued access to critical information: Clinicians, health information management and revenue cycle teams can securely access archived clinical, financial and operational records without maintaining the outdated applications in which the information was originally stored.
Data prepared for AI and analytics: DataArk structures and indexes archived information, creating opportunities for health systems to use analytics, natural language processing and other AI-enabled tools. Rather than leaving valuable information inaccessible in retired systems, organizations can put retained data to work supporting operational insights and future technology initiatives.
Together, these capabilities support a broader lifecycle strategy that includes application rationalization, system decommissioning, data extraction, migration, archiving and preparation for advanced analytics.
“An archive shouldn’t be the end of the journey. It’s a stop along the way,” said Mike McGuire, senior vice president of product strategy at MediQuant. He said the company’s goal is to help health systems reduce the amount of data they need to store and secure while making retained information more accessible and valuable.
The expanded platform also reflects a broader industry shift toward more proactive data management. During a September executive advisory session hosted by MediQuant and Becker’s Healthcare, health system technology leaders discussed the need to move beyond traditional retention practices and take a closer look at what information organizations should keep, where it belongs and when it can be removed.
For healthcare CIOs, the ability to connect data retention policies with actual storage practices is becoming an important part of managing technology costs, reducing risk and preparing information environments for future AI investments.
To learn more, visit MediQuant or explore its data lifecycle management capabilities.
