Everything Healthcare Leaders Must Know to Build a Data Migration Plan

Why Data Center Migration Is Key for a Competitive Edge

Nearly any healthcare organization seeking to modernize could benefit from data center migration, as it:

1. Drives cost savings.
   Data migration eliminates the need to pay monthly licensing fees for maintaining legacy systems. It also removes extra costs related to keeping legacy systems updated, as well as the productivity losses associated with slower hardware. Research shows that 85% of organizations that retire legacy systems and archive old data experience positive financial results.
2. Supports data accessibility.
   Migrating data from disparate systems to one centralized location means users no longer have to log into multiple systems to access information. In addition, migrations to cloud storage provide secure accessibility from various devices, including mobile devices.
3. Promotes data interoperability.
   Migrating legacy data to a new, interoperable system means healthcare organizations can exchange that data with external entities or incorporate it into technologies within the organization’s own expanding technology stack (e.g., laboratory information systems, telehealth platforms). Without data migration, interoperable exchange is costly and, in some cases, impossible.
4. Increases data security.
   Legacy systems pose a significant cybersecurity risk to healthcare organizations. These antiquated systems were not built with modern security tools and techniques, and they may not even function on modern versions of operating systems. That means they’re not protected with recent security patches that prevent advanced cyberattacks. A cyberbreach can be financially devastating—with the average cost of a healthcare data breach nearly $11 million—and it can greatly harm an organization’s reputation.
5. Allows you to leverage advanced data analytics, automation, and artificial intelligence.
   When historical data is stuck in legacy systems, it’s difficult to use modern analytics tools that help organizations make data-driven decisions. Legacy system migration ensures data from disparate systems is all in one place for easier analysis.

6 Benefits of Data Archiving Before a Migration

Some of the many benefits of archiving cold data before migration include:

1. A Lower Volume of Data to Migrate
   Data migration often becomes more manageable and cost–effective when there’s less to migrate. A structured approach to data archiving drastically reduces the volume of data that needs to be migrated to the new system while simultaneously providing end users with uninterrupted access to cold data.
2. Improved Data Quality and Integrity
   Healthcare data archiving preserves the integrity of data by mitigating the risk of data loss or corruption during migration. If routine data quality checks and validations occur, archiving cold data enhances data quality overall.
3. Optimized System Performance
   If data is archived, your end users won’t need to access both legacy systems and your new system. Archiving solutions can often integrate directly with new systems to provide seamless access through one login.
4. Better Compliance with Regulatory Policies and Data Retention Requirements
   Data archiving helps you meet regulatory requirements regarding data retention and patient privacy even while pursuing a complex migration project. If your cold data is archived, you won’t need to worry about losing access to historical data or accidentally destroying data prematurely.Additionally, healthcare data archiving solutions compliant with the Health Insurance Portability and Accountability Act (HIPAA) protect your organization against potential legal, regulatory, and security issues.
5. Lower Costs
   Archived historical data means your migration efforts only need to target mission-critical data—not all your data. The reduced time and effort lead to substantially lower costs.
6. Better Patient care
   Healthcare data archiving solutions give your teams access to treatment, medication, and prognosis information even in a data migration, ensuring patient safety and quality of care is not put at risk.

6 Clinical Data Management Questions to Inform Your Migration Strategy

Consider these six questions before developing your data migration plan to get your organization off to a good start.

1. Should you do a full or partial system migration?
   You’ll need to determine whether it makes the most sense to migrate all or only a subset of your data. If you do a full migration, you’ll maintain complete access to patient information and historical data and be better able to meet regulatory compliance standards. However, older information may be incomplete or in the wrong format, compromising data integrity and necessitating extra steps in the process. Migrating just some data may be more efficient, especially if you choose to archive the rest.
2. Is a cloud-based or hybrid approach to data migration better?
   While you may feel more familiar with a hybrid approach to clinical data management, today’s cloud services are worth considering for their security, scalability, and affordability. Migrating to the cloud lets you automate the process of converting massive amounts of complex data, and it eliminates the need to pay for expensive in-house hardware.
3. Is it best to work in phases or complete all the work at once?
   There’s no right answer, and what you choose will likely depend on your business needs. While an all-at-once transfer typically involves temporarily taking systems down, the advantage is that it’s a “one and done” procedure. With a phased approach, data migration is completed piecemeal over a longer period of time by running both systems in parallel, thus eliminating downtime.
4. Who should be on the clinical data migration team?
   You’ll need the help of data management professionals who understand how to maintain data integrity, as well as the researchers and clinicians who use the data day to day and understand how and when it needs to be accessed. The clinical data migration team should also include functional experts who know how to validate data, map it correctly, and ensure it transfers accurately.

    

   Finally, the team needs IT professionals skilled in coding and data transfer who can resolve potential technical issues. If your organization is lacking in any of these skill sets, a third-party vendor could help fill the gaps.

5. What needs to be done to improve data quality?
   Performing data cleanup before starting the migration process can combat issues that would otherwise be caused by poor-quality data. Identify records with mistakes, duplications, or unnecessary details and leverage data cleansing tools to address them. It also helps to implement data quality checks, validation rules, and data cleansing workflows at every stage of the migration project.

    

   Inconsistent data formats pose additional challenges to data quality. Converting all data—including images, multi-level patient records, and diagnostics—to a consistent, interoperable structure is also paramount.

6. What data migration risks should you know about?
   Three of the most common risks facing data migration projects include migration of too much or too little data, unplanned system disruptions and downtime, and loss or corruption of data.

    

   The best way to mitigate these risks and others is to create a comprehensive roadmap for migration. Use this roadmap to clearly define your project scope and inform your decisions around things like the solutions you’ll use, transfer methods you’ll follow, and steps you’ll take at each stage of the project.

It’s therefore helpful to account for additional time and to be aware of some of the elements that may cause delays:

1. The volume of data to convert. If you’re in a value-based care arrangement, you may want to convert and migrate several years’ worth of data because you may need historical information to support specific quality measures. However, you also don’t want bad data degrading quality measures, and the more data you convert, the more you run that risk. Finding the right volume of data to convert (and potentially archiving the rest) is a delicate balancing act.
2. Cooperation of your legacy system provider. Your legacy system provider needs to release your data before you retire the system and begin your migration project. If they put up walls—even unintentionally—it can throw off your timeline.
3. Resource constraints in a hosted environment. If you use another healthcare organization’s EMR, you can only move as fast as their resources for ingesting data allow.
4. Delays in pulling data from a source system. If you can’t efficiently extract data from a source system, your entire conversion project may take longer.
5. Internal resource constraints. You must have enough internal resources to assess and validate the data to keep the project progressing in a timely manner.
6. The presence of a single source of truth. Being able to create an enterprise master patient index (EMPI) by correcting duplication errors is crucial. Otherwise, the conversion process may become excessively burdensome and time-consuming.
7. Patient matching. If you can’t easily match patients across systems, the conversion process can get delayed.
8. Scope creep. Failing to monitor the scope of a project can be costly. Additional requests can make the project less straightforward and increase the price and delivery time.

Expert Advice to Heed

As you plan for data conversion and migration, Madelaine Yue, vice president of solutions delivery at Experis Health Solutions, recommends following these best practices:

• Have a strong partner. The right data conversion partner(s) can help you simplify an otherwise complex process. Ask lots of questions to understand what each potential partner brings to the table.
• Keep end-users updated. Let users know what data is being converted or archived and when so they can access the information they need without disruptions.
• Keep going, even when challenges arise. Work with your partners to brainstorm new approaches when you hit a wall.
• Remember the importance of validation. The ultimate goal of data conversion is making sure data is usable. You ensure you’re meeting this goal through validation.

8 Data Security Tips for Protecting Patient Privacy

The following best practices can promote healthcare data security during a data migration and archiving project:

1. Complete a risk assessment before, during, and after migration
   Risk assessments help organizations identify gaps in their cybersecurity posture. Performing a risk assessment before a data migration project sets the stage for strong security during the remainder of the project.However, security issues can occur at any time, which is why it’s important to perform risk assessments during and after the project, too. Risk assessments should analyze physical, technical, and administrative safeguards to test for vulnerabilities in systems, processes, and personnel.
2. Follow strong encryption protocols
   Data encryption—required under HIPAA—converts plain text or data into a coded form inaccessible to anyone without a decryption key.Organizations can leverage encryption not only when data is stored “at rest” in a health information technology system, but also when it’s transmitted between systems (such as during a data migration project). Using SFTPs is one way of keeping data encrypted while it’s being transferred to a new system.

   The best encryption method to use will depend on the type of information being encrypted, the level of protection required, and your existing infrastructure. Whatever you choose, it’s important to ensure appropriate key management and train staff members on encryption protocols and procedures.

3. Implement strict access controls
   Only individuals who need access to patient information to perform their job duties should have that access, regardless of whether a migration is underway. Organizations can keep data secure through role-based access paired with multi-factor authentication.
4. Track data access with compliance monitoring logs
   Compliance monitoring gives organizations insight into who accessed what information, when, and from where. This lets organizations identify anomalies and unusual activity (e.g., access from unexpected locations or large data transfers), allowing quick responses to potential security incidents.
5. Create a backup and recovery plan
   Despite an organization’s best efforts, unexpected issues can occur during a data migration project. Having a backup and recovery plan ensures business continuity. The plan should identify how and when organizations can maintain and access secure, offsite backups of sensitive data, as well as how backup and restore procedures will be tested.
6. Train employees on security best practices
   While employees can be partners in promoting cybersecurity, untrained employees often make mistakes that cause data breaches. Healthcare data security training helps these employees understand threats and vulnerabilities so they can become assets to your security posture instead of liabilities.
7. Work with secure vendors
   Working with contract specialists presents opportunities to put more stringent protections on sensitive patient data. Ask third-party entities how they enforce security and privacy standards and carefully review their policies, procedures, and technical safeguards to make sure they’re capable of keeping your data secure. Those with recognized compliance certifications, such as SOC 2 Type 2, are generally the most trustworthy.
8. Properly manage mobile electronics
   Securing mobile devices with encryption, remote wiping capabilities, and mobile device management solutions can help reduce the chances of hackers gaining access to your system.Isolating connected devices with network segmentation can also help promote healthcare data security by preventing attackers from reaching your main systems if they manage to hack a mobile device.

Before migration, be sure to:

• Discontinue legacy systems for storing and managing data, and transition to a data archiving solution that integrates with your new EHR.
• Create a governance framework that outlines how your organization will collect, retain, use, access, and share data. This framework should detail data-related policies and procedures, roles and responsibilities, and accountability related to data management.
• Train employees on data entry procedures that reduce errors, and enforce data entry best practices.
• Secure your data. Implement strict access controls, perform frequent vulnerability scans, and adopt other comprehensive security measures. Also make sure the data archiving and migration vendors you’re partnering with adhere to strict data security standards.

Implement these strategies during data migration:

• Perform extensive testing to ensure data transfers correctly, without errors or omissions.
• Use secure data transfer protocols that protect data from unauthorized access during migration.
• Clean the data and transform it into a format compatible with the new system. This may require renaming files, reorganizing folder structures, digitizing information, or extracting specific data points.

After data migration is complete:

1. Use third-party data to add context to your datasets. Integrating data from different sources can create a more consistent and unified view of information.
2. Properly integrate and configure all analytics tools to ensure they interpret and process data consistently.
3. Perform ongoing data audits. Regular audits can help you identify and rectify issues before they escalate.
4. Maintain audit trails so you can periodically review who alters data and why.

Some of the key benefits a specialized healthcare data migration vendor brings to the table include:

• Experience with electronic health records (EHR) and other health information systems
• Knowledge of HIPAA and other regulatory requirements, including any related data retention policies
• Expertise in handling data structures and standards for EHR data
• Strong data security and privacy measures
• Scalable solutions that can handle the complexity and volume of healthcare data

Tips for Partnering with a Healthcare-Focused Data Migration Services Provider

All successful partnerships are two-way streets, and a partnership with a data migration services vendor is certainly no exception. Here are some tips for collaborating well with your healthcare data migration services vendor:

1. Clarify expectations at the start of the project. Ensure you and your vendor are on the same page about the purpose and expected outcomes of the data migration project. Encourage the vendor to be clear about what it can and cannot achieve within your given timeframe and budget.
2. Collaborate on the project plan. Work with your data migration vendor to collaboratively establish the objectives, scope, and timeline of your project.
3. Design a strategy together. Convey the core data elements you need access to for care continuity and compliance and ask your data migration vendor to articulate how it will map this data. Align on your approach to moving the data from the old system to the new one using HIPAA-compliant methods that preserve privacy and security. Also identify potential risks (e.g., inconsistent data formats or data quality issues) and work together to decide on mitigation strategies.
4. Discuss legacy data. Your strategy should involve archiving essential legacy data and potentially destroying what you don’t need. A healthcare-focused data migration services provider can offer support for legacy data management.
5. Align on data governance. Agree on data cleansing criteria and quality needs with your vendor before the data migration process begins.
6. Provide the necessary access. Your vendor will need access to all the data you plan to migrate. Prepare an inventory of the data assets and storage systems you need to grant them access to and decide how that access will be given while maintaining security.
7. Communicate consistently. As you receive feedback from end users, pass this information to your data migration services partner so they can hone their strategy. Likewise, your partner should give you regular updates and keep all stakeholders informed of their progress.
8. Thoroughly test data and measure system performance. Validate your data post-migration to ensure the data migration was completed correctly. Also monitor ongoing performance to improve data quality management over time. A trustworthy partner will encourage these checks to ensure you’re satisfied with the project.