8 Common Challenges Faced During Healthcare Data Migration (and How to Overcome Them)

Healthcare data migration is a process at the top of most priority lists in the industry today—and for good reason. As cloud-based infrastructure takes center stage and demand for seamless healthcare data interoperability grows (from patients and regulatory entities alike), data migration is a must to implement data ecosystems that are modernized, integrated, and agile.

The benefits of successful healthcare data migration are manifold. Modern data systems enable seamless data accessibility from all key stakeholders, which is crucial for delivering high-quality and personalized care. They facilitate advanced data analytics capabilities to provide healthcare professionals with valuable insights that improve clinical outcomes.

They’re also designed to meet today’s stringent and fast-evolving regulatory requirements, enhancing compliance while enabling safeguards for patient data privacy and security.

Perhaps most importantly, they’re necessary to meet the high-level shift toward holistic patient views and 360-degree healthcare delivery. Mayo Clinic President and CEO Gianrico Farrugia summed it up aptly following the 2022 World Economic Forum annual meeting:

“We must move from traditional, linear pipeline-service-model thinking to a platform approach,” he said about addressing healthcare access and quality issues, “which brings together longitudinal medical data, producers and consumers to co-create a new healthcare paradigm that fundamentally changes how we provide healthcare and advance cures.”

Healthcare data migration is a core part of achieving this—but it’s also a complex process that comes with its own set of challenges. In this guide, we’ll explore these challenges in detail and outline the best strategies to mitigate them throughout the migration journey.

Quick Takeaways:

• Healthcare data migration is crucial for achieving ecosystem-wide data interoperability that drives informed decisions and personalized care.
• The migration process comes with challenges like data volume and complexity, downtime and disruptions, data quality assurance, and legacy system decommissioning (among others).
• Working with an expert third-party migration partner and adopting a comprehensive healthcare data management platform (HDMP) significantly reduce risk and enhance migration outcomes.
  
  

Why Do Organizations Migrate Healthcare Data?

The root motivation behind healthcare data migration is the need for complete interoperability in today’s industry landscape. Legacy systems can no longer handle the sheer volume and complexity of data now generated by healthcare organizations. Concurrently, the rise of telehealth and remote patient monitoring (and related technologies like IoT wearables, patient portals, and online pharmacies) demand seamless data exchange across ecosystems.

For this to happen, data must be meticulously maintained so that it’s standardized, accurate, accessible, and secure—an impossible feat with outdated, manual data management systems in place.

Migrating healthcare data to a modern healthcare data management platform (HDMP) centralizes data and automates the many steps that go into managing it long-term. This facilitates key benefits such as:

• Improved Data Accessibility: Modern systems enable faster and secure data access for patients, providers, payers, and other stakeholders, facilitating better decision-making in patient care.
• Enhanced Patient Care: Integration of all data sources provides a comprehensive view of patient health, leading to improved diagnosis and treatment plans.
• Regulatory Compliance: Modernized systems ensure compliance with current data regulations and standards like HIPAA and FHIR.

It’s important to note that none of this is a nice-to-have—without this level of interoperability, healthcare organizations will be unable to stay compliant or operate effectively within their networks. Healthcare data migration is required to keep organizations relevant and in line with patient expectations, regulatory requirements, and operational performance standards.

8 Common Challenges Faced During Healthcare Data Migration

Healthcare data migration challenges are complex to navigate. Without proactive strategies in place to recognize their signs and mitigate their associated risks, organizations can significantly hinder the impact and success of their migration efforts. Important challenges to plan for include:

1. Data Complexity and Volume

Healthcare data is vast and comes from a growing number of sources—patient records, claims reports, IoT wearables, lab reports, population health datasets, research studies, and more. To manage this complexity, start with meticulous planning and data mapping to understand the data relationships and dependencies that exist in your IT ecosystem.

Use data profiling tools to assess data quality and identify anomalies. Implement thorough data cleansing processes to remove duplicates and correct errors. Validate data integrity with continuous checks. Employ technologies like ETL (Extract, Transform, Load) tools and automated data management solutions to streamline these processes and ensure accurate data migration.

2. Interoperability Issues

Healthcare data often resides in disparate systems with varied formats and standards, posing significant integration challenges. Adopt a comprehensive Health Data Management Platform (HDMP) to address these issues and enable the seamless integration of different data sources. Leverage API-driven solutions to ensure continuous synchronization across different systems, break down data silos, and enhance overall interoperability.

3. Downtime and Disruptions

Downtime during migration can disrupt healthcare operations, impacting patient care and administrative processes. Minimize downtime through detailed migration planning, which includes identifying critical systems and scheduling migrations during low-usage periods. Implement a phased migration strategy to gradually transition data without overwhelming systems.

Utilize backup systems to maintain continuity of operations to help to ensure a smooth transition and allow for immediate fallback if issues arise.

4. Data Quality Assurance

Maintaining data quality during migration is essential to prevent inaccuracies that may affect patient care and decision-making. Employ rigorous data profiling, cleansing, and validation procedures to ensure data accuracy and completeness. Establish data governance frameworks to standardize data handling at the highest levels and enforce quality standards across all data generation and access points.

5. Compliance and Security Risks

Migrating healthcare data involves stringent compliance requirements and significant security risks, especially regarding patient privacy. Enhance security and compliance by employing robust encryption methods to protect data during transit and at rest.

Implement strict access control measures to limit data access to authorized personnel only. Conduct regular audits and continuous monitoring to detect and address potential security vulnerabilities. Ensure all processes comply with regulations by integrating compliance checks into the migration workflow.

6.Legacy System Decommissioning

Shutting down legacy systems without losing critical data is a delicate process that requires careful planning. Follow a structured approach for decommissioning, which includes a comprehensive audit of the legacy system to identify all critical data.

Ensure all necessary data is migrated and validated in the new system before decommissioning. Develop a detailed shutdown plan that includes data backup, final validation, and the secure disposal of obsolete systems. This ensures no data loss and a smooth transition to your new system.

7. Resource Allocation and Expertise

Effective data migration requires skilled personnel, which can be challenging to manage within limited budgets and resources. Prioritize critical datasets through strategic planning to allocate resources efficiently. Leverage external expertise by engaging third-party solution providers who bring experience and advanced tools to the migration process.

Invest in training and upskilling internal teams to enhance their capabilities in managing modern data systems, ensuring long-term sustainability and expertise within your organization.

8. Post-Migration Validation and Optimization

Validating your new data system post-migration is crucial to ensure it operates correctly and all data is accurately transferred. Implement comprehensive testing and validation procedures to verify the functionality and data integrity of the new system. Use automated testing tools to perform regression tests and ensure compatibility with existing workflows.

Continuous monitoring and optimization help identify and rectify any post-migration issues, ensuring the new system performs efficiently and securely.

The Takeaway

Navigating healthcare data migration is challenging, but with the right technology tools and strategies, it’s manageable. By anticipating and addressing complexities related to the migration process, healthcare organizations can achieve a seamless transition to modern data systems.

At Gaine, we’ve walked into some of the largest healthcare organizations on the planet and taken the time to tackle a very specific problem space and master it. We’ve poured an immense amount of technical expertise in building a data management platform that is purpose built to support healthcare organizations in modernizing their information systems away from legacy file-based exchanges to more real-time web API or data streaming. The Gaine Coperor™ Health Data Management Platform (HDMP) offers native identity resolution and an out-of-the-box extensible healthcare data model. This allows us to very quickly support concurrent data modernization efforts that are multi-application, multi-phased, and multi-domain – at scale.

Application modernization requires a clearly defined data strategy and a data management platform that can facilitate progressive modernization across your enterprise. The data management platform needs to be purpose-built with healthcare in mind and needs the flexibility to support your specific business needs as it relates to your data.

Talk to a Gaine Health Data Management expert about how Coperor HDMP can help you transform your data strategy.