Data Migration in Healthcare: Challenges and Best Practices

There are only a handful of industries where data security and privacy are as mission-critical as they are in healthcare, which happens to be one of the most tightly governed sectors. However, the ever-growing amount of data being stored and processed by healthcare organizations begins to outstrip the existing infrastructure at some point, making data migration a necessity.

Migrating data from one system to another is one of the most complex projects that can be undertaken in healthcare. This post will help you determine the medical data migration approach that suits your medical business goals and priorities. 

What is healthcare data migration?

Healthcare data migration is the process of transferring healthcare data from one eHealth environment to another. It’s usually a necessary step if you choose to abandon your legacy system and move on to one that has a greater capacity to securely store patient-related medical data.

In this way, you’ll manage to improve data storage and integrity, increasing your trustworthiness as a medical institution. On top of that, a well-conducted data transfer enables you to significantly improve patient care, contributing to more precise diagnosing.

Check out this video for a quick intro to healthcare data migration:

Key takeaways

• Healthcare data migration involves the transfer of healthcare data from one environment to another.

• Changing data formats, the growing need for data connectivity, and the increasing complexity of data are the most common drivers of data migration in healthcare.

• The volume and complexity of data, interoperability between different systems, and resource constraints pose challenges for healthcare data migration projects.

Healthcare data migration in numbers

• RBC Capital Markets claims that the healthcare sector generates 30 percent of the global data volume.

• According to a 2023 HIMSS Analytics Report, 78 percent of healthcare organizations have either completed or are in the process of migrating their data to the cloud.

• A 2021 survey by KLAS Research reported that 82 percent of healthcare facilities observed improved patient care after migrating medical data to a centralized platform.

• A 2022 study published in the Journal of Medical Systems found that medical data migration can improve operational efficiency by up to 25 percent.

Reasons for healthcare data migration

Why exactly do medical establishments choose to conduct data migration? Below are the five main reasons for data migration:

Adoption of cloud storage

The most common reason for medical data migration is the inability of the current software system to handle the increasing volume and complexity of stored data.

The healthcare sector deals with large amounts of data, which usually require significant investments in infrastructure, hardware, and server maintenance. That’s why cloud storage is now gaining popularity. Cloud data storage solutions allow for quick and cost-effective scaling of storage infrastructure without reliance on physical servers and with predictable spending. 

Additionally, the majority of cloud-storage service vendors provide solid data backup options, making your healthcare data migration less risky and facilitating an additional layer of security for patient data. 

Data consolidation

Usually, a lot of healthcare service providers have more than one eHealth platform. Consequently, each type of software contains drastically different data types that somehow have to be gathered within unified data storage. The medical data migration process engages a wide range of useful tools and algorithms that make it possible such as:

• Data encryption algorithms,
• Data correctness validation algorithms,
• Machine Learning (ML) algorithms,
• Mapping algorithms.

Electronic Health Record (EHR) updating

Unfortunately, your EHR software can become outdated, prompting the need to modernize it or switch to new software. By choosing to conduct EHR data migration, you are taking a step toward enhancing the quality and accuracy of medical services. Then, you'll need to consider how to transfer data without any issues and ensure carefully planned data management. Here are the key ways proper data migration can help during the adoption of new EHR:

Smooth new feature implementation: A newly upgraded EHR will most likely include new features and interface variations. Data migration ensures that new features are effectively utilized in all patient data.

Optimized eHealth environment: EHRs are supposed to work tightly with other software systems within your digital health environment, including Laboratory Information Systems, Remote Patient Monitoring Software, and telemedicine applications. Proper data migration enables seamless data exchange, bringing about a wholesome treatment journey for your patients.

Challenges of healthcare data migration

There are a number of common challenges medical enterprises encounter during healthcare data migration:

Data volume and complexity

Healthcare data often comes in large volumes and a wide diversity of formats, which may make it challenging to migrate effectively at once. Additionally, medical data like images, multi-level patient records, and diagnostics are quite complex to operate, adding another layer of difficulty to the migration process.

Solution: To overcome issues associated with increased data complexity and volume, start off with a thorough assessment of the current data landscape. Then, leverage data cleansing tools to get rid of inaccurate or damaged data and establish unified data standards.

Interoperability failures

As the amount of data increases, ensuring its seamless flow within other medical software solutions becomes more complicated. If you’ve lost track of formats, data types, and standards, you may experience difficulties during data mapping and migration.

Solution: To avoid problems with data interoperability, strictly follow unified standards like HL7 and FHIR and ensure seamless data flow across different digital healthcare systems.

Regulatory compliance and security

Keeping up with medical industry laws and regulations appears to be the most significant challenge for many healthcare providers. In addition to the industry-specific legislation, there are also ever-evolving privacy laws one needs to keep tabs on. 

Solution: Make sure to conduct in-depth research on all healthcare regulations that can be applied in your location and strictly follow them during your healthcare data transfer.

System disruptions

Given the challenges of migrating huge volumes of healthcare data, a total collapse of the system may not be excluded from the list of potential risks. This could result in downtime and have a potential negative impact on patient care, causing treatment delays and compromising overall patient safety.

Solution: The best way to mitigate these risks involves carefully planning and implementing data migration strategies in incremental stages. Furthermore, scheduling healthcare data migration during off-peak hours can help reduce the impact on medical services.

Resource constraints

Healthcare data migration projects require highly qualified and experienced experts, which may be quite challenging to find initially. Lack of sufficient numbers of well-qualified technical experts can result in poor execution and delay the completion of healthcare data migration initiatives.

Solution: To address this issue, invest more time and resources into training programs to upskill existing staff members. Another option is to outsource particular tasks and data migration project scopes to a third-party vendor with strong technical expertise, experience, and a deep understanding of the eHealth domain. Additionally, you may want to explore relevant tools that can assist you in implementing a more organized approach to data migration with limited resources.

Healthcare data migration best practices

So, what do you need to prioritize to ensure properly executed data migration in healthcare? Here is a short 6-step list for a sound medical data migration flow:

1. Define why you need medical data migration

Understanding your specific migration needs, identifying requirements, and setting goals will help transform an undefined migration strategy into a precise plan. Healthcare businesses undertake such an initiative to

• Reorganize data and improve consistency,
• Enhance data integrity,
• Ensure scalability for future data volume growth,
• Bolster data security.

2. Conduct an audit of the data ecosystem

An auditing of your current data environment may provide you with a 360-degree view of the current data storage picture, enabling you to prevent potential major risks like significant loss of data. Here is what you should check out primarily:

• Common and repetitive data patterns, types, formats, and data sources,
• Common data inaccuracies and inconsistencies,
• Data protocols and standards,
• Transmitted data complexity and volume,
• Essential health regulations to comply with,
• Financial planning and assessment.

3. Use data visualization

Medical data visualization is a very popular trend in the healthcare industry. This approach provides medical providers with deeper insight as they work with patient data and plays a crucial role in healthcare data migration. This technology helps translate complex data into easy-to-understand graphics and charts, making them easier to manage and understand.

Moreover, data visualization tools can help detect data inconsistencies and anomalies, enabling you to set data cleansing targets and take corrective measures to ensure wholesome data integrity.

4. Choose the right medical data migration tools

There is a wide range of tools in the market that can be used for data migration in healthcare. To find the most suitable instruments for your use case, start by making a list of the qualities you should seek in medical data migration tools:

• Ability to support your data standards (FHIR, HL7, etc.),
• High interoperability bandwidth,
• Ease of use within your existing tech infrastructure,
• Vast customization options to meet your unique requirements,
• Scalability for your current migration needs.

5. Ensure regulatory compliance

Healthcare services providers encompass a wide range of industry regulations. HIPAA (Health Insurance Portability and Accountability Act) is the most common regulation your medical software solution has to meet (if in the US) to be reliable in terms of protecting patient-related medical information. However, in addition to HIPAA compliance for software development, data migration in healthcare is also sensitive to a lot of international medical security standards, including:

• eHealth Action Plan, GDPR (in Europe),
• PIPEDA, PHIPA (in Canada),
• Data Protection Act 2018 (in the UK),
• Australian Digital Health Agency Standards (in Australia).

The set of essential regulations may differ depending on your location, so make sure to conduct thorough research before starting the data transferring process.

6. Safeguard medical data

Complying with medical regulations requires robust data security, which, in turn, helps mitigate risks, including data leaks, data disruptions, and invalid data. Here are basic data security measures you can utilize:

• Medical data encryption,
• Role-based access controls,
• Data retention and residency,
• PHI (Protected Health Information).

7. Keep track of migration

Usually, medical data migration requires a systematic approach to transferring the data from a source system to a destination system. That’s why you’ll need to plan the medical data migration as well as monitor its flow. Additionally, a sound plan also helps you identify the potential risks involved and establish robust error-handling processes. 

This strategy enables you to detect errors, record details, and apply off-the-shelf issue resolution algorithms promptly. You can automatically resume the medical data migration process after the resolution of the main issue thanks to advanced error-handling capabilities.

A well-executed data migration process consists of many stages. To simplify this task, you can utilize tools such as:

• Splunk - for medical data migration troubleshooting

• Dynatrace - for end-to-end monitoring of the infrastructure

• SolarWinds - for tracking database state and performance during migration.

Healthcare data migration content to consume

• Video – Migrating Clinical Data in Various Formats to a Clinical Data Management System

• Podcast – The Good, Bad, Ugly, and Even Uglier of Healthcare Data Migration; Will Erskine, PBT Australia

• Article – Seamless & Secure Medical Data Migration

Conclusion

The increasing pace of digital transformation has made data migration inevitable for healthcare organizations. However, medical data migration projects can pose a significant challenge due to the complexity of the data landscape in such organizations and the rules and regulations at play. Adopting a systematic approach to medical data migration, leveraging specialized data migration tools, prioritizing data security and compliance, and following the rules and regulation go a long way toward successfully migrating data.

A relatively new technique that caters to the specific needs of healthcare organizations is data virtualization, which facilitates the creation of a single view of truth from different data sources. It establishes a semantic layer over distributed data sources, enabling users to access data via SQL, REST, or GraphQL. This capability makes data virtualization ideal for healthcare organizations striving to break down data silos and form a single view of truth from their scattered data.

Data virtualization eliminates the need for copying or moving data, simplifying data management for healthcare organizations where huge amounts of data need to be migrated. It minimizes the risk of data loss and reduces data storage requirements. Thanks to the absence of complex and brittle data pipelines for moving data, data virtualization removes the need for large data teams and brings about cost savings.

Peaka leverages data virtualization to combine data from a wide range of databases, data warehouses, SaaS tools, and APIs. Its zero-ETL approach allows users to access and query data wherever it resides without any maintenance or data teams involved.

Book a free demo and discover how Peaka can simplify your data migration project!