A Large Healthcare Services Company
Healthcare Data Management Leader Maintains Critical Operations Through 24/7 Legacy System Support
A large healthcare services company faced mounting challenges with aging master data management systems that processed critical healthcare data for multiple industry partners. Rather than pursuing a costly multi-year replacement project, they partnered with Allata to implement comprehensive 24/7 support services. Through strategic maintenance, process improvements, and targeted AI assistance for data matching, we ensured business continuity while the client developed their long-term modernization strategy.
OVERVIEW
Our comprehensive support approach transformed an unstable legacy environment into a reliable operational foundation. The client successfully maintained their critical healthcare data processing capabilities while avoiding the risks and costs of premature system replacement.
After initial contracting and staffing challenges, our team established consistent 24/7 support coverage using both nearshore and offshore resources. This approach ensured continuous monitoring and rapid response capabilities for weekend processing activities and critical system issues.
The engagement demonstrated how strategic maintenance can extend the lifecycle of mission-critical systems while organizations plan for future modernization. Our approach allowed the client to maintain their position as a key data services provider to hospitals, clinics, and healthcare companies across multiple locations.
- Established 24/7 operational support coverage
- Maintained system stability for core business operations
- Enabled continued service delivery to healthcare partners
THE CHALLENGE
The client operated two primary applications supporting their healthcare data processing business: a Data Management Application to identify, match and reclassify products and studies, and a Master Data Management system for governing shared enterprise data.
Original support teams had been moved to replacement projects as the organization initially attempted to modernize these legacy applications. However, they discovered that replacement solutions would require years to implement, forcing a strategic pivot back to supporting existing systems.
The return to legacy system support revealed significant challenges. Team members had left and required replacement, while vague documentation and manual processes created knowledge gaps. Early contract language also created scope limitations that complicated resource allocation and service delivery.
The Data Management Application presented particular challenges due to its age, insecure protocols, and architectural limitations. The system’s design made routine maintenance difficult and created ongoing security risks that needed immediate attention.
- Legacy applications with poor documentation and manual processes
- Disrupted support teams requiring rebuilding and knowledge transfer
- Security vulnerabilities in aging system architecture
- Scope limitations from initial contract language
OUR SOLUTION
Allata implemented a complete support services model designed to stabilize operations while the client developed their long-term modernization plans. Our approach focused on maintaining business continuity rather than pursuing immediate replacement, recognizing that the existing systems were fundamental pillars of the company’s operations.
To ensure continuous availability for critical healthcare data processing, we established round-the-clock support using both nearshore and offshore team members. This model provided coverage for weekend processing activities and immediate response capabilities for system issues that could impact multiple healthcare partners.
Beyond basic maintenance, we implemented strategic enhancements including CI/CD deployment processes and migration from Octopus deployment tools to Azure DevOps. These improvements increased deployment reliability and reduced manual intervention requirements.
We introduced limited AI capabilities through the existing client matching system to improve data quality and reduce manual effort. The AI component helped identify duplicate entries and similar product names, such as distinguishing between “United States of America” and “USA” or matching variations like “Syringe 3MM” and “3MM syringe.”
- Established comprehensive support framework for critical legacy systems
- Implemented 24/7 coverage using nearshore and offshore team coordination
- Enhanced deployment processes with modern CI/CD practices
- Applied targeted AI assistance for data matching and duplicate detection
- Maintained operational stability while client planned modernization strategy
THE RESULT
Allata’s maintenance approach successfully preserved the client’s ability to serve healthcare partners without interruption. The systems continued processing critical healthcare data that supports hospitals, clinics, and medical device companies across multiple locations, maintaining the client’s position in a competitive market.
After resolving initial staffing and contract challenges, we achieved consistent operational performance. The 24/7 support model ensured rapid response to issues and proactive monitoring of weekend processing activities, significantly reducing system downtime risks.
The engagement proved that strategic maintenance can be more valuable than rushed modernization attempts. While no major replacement solution was delivered, our approach provided the stability needed for the client to properly plan their technological evolution without sacrificing current business operations.
- Maintained uninterrupted service delivery to healthcare industry partners
- Achieved stable operations through 24/7 support coverage
- Enabled strategic planning for future modernization without operational disruption
- Reduced manual effort through targeted AI assistance for data quality management
technology
Our solution leveraged the client’s existing technological investments while adding strategic improvements for enhanced reliability and monitoring capabilities.
- Database Management: SQL Server for core data processing, including SSIS packages
- Cloud Infrastructure: Azure Virtual Machines for application hosting
- Deployment Tools: Azure DevOps (migrated from Octopus Deploy)
- AI Capabilities: Client’s matching system for data matching and duplicate detection
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