Healthcare Data Migration

Healthcare data migration is the process of transferring healthcare data from one system to another. This can include moving data from an electronic health record (EHR) system to a new EHR system or migrating data from one hospital or clinic to another.

  1. What does healthcare data migration mean?
  2. What are the types of healthcare data migration?
  3. Stages of the healthcare data migration process
  4. What are the best practices for healthcare data migration?
  5. Challenges of healthcare data migration
  6. Benefits of healthcare data migration

What does healthcare data migration mean?

Healthcare data migration is the process of transferring health data from one system to another. This includes moving data from one Electronic Health Record (EHR) system to a new EHR system, or migrating data from one hospital or clinic to another. There are several reasons why you might want to migrate your healthcare data. Perhaps your healthcare organization is migrating an EHR system, consolidating clinics and hospitals, or closing a healthcare facility. Perhaps you are complying with new regulations or want to improve your clinical care process. Regardless of the reason, it’s important to carefully plan and effectively execute your healthcare data migration strategy.

What are the types of healthcare data migration?

  1. Storage Migration

As organizations invest in new technology systems, old software is discarded. This process is called storage migration. IT departments move data from one system to the next and digitize physical records. Companies are using this process because of technology change, not because of storage capacity shortages. For large enterprises, it takes time to complete a storage migration. For example, a large global distribution company took 10 years to move data to new systems as part of a storage migration process.

  1. Database Migration

Databases store and organize data under the direction of a database management system. Database migration, therefore, refers to upgrading your current database or moving from an old database to a new provider. Replacing an old database with a new vendor is more difficult than upgrading your current system. It becomes even more difficult when organizations use data migration software to migrate from hierarchical, flat file or network databases. These source/destination systems are outdated, but redesigning and removal of information is expensive, so most organizations continue to use them.

  1. Application Migration

When a company invests in a new software solution, the IT department must move all information into that system. This type of data migration is more popular as companies need to update their software regularly to maintain a competitive advantage. Problems arise when old data systems and new systems operate on different formats and models. In this case, an experienced professional should perform the application migration process.

  1. Data Center Migration

Companies maintain critical applications and information in data centers. Data centers are physical locations, not digital locations, referring to the space in which devices and other IT technologies reside. Organizations can make this type of transition when moving all their digital assets or moving current systems to other parts of their facility. Businesses must be careful when moving equipment, as it is fragile and expensive to replace.

  1. Business Process Migration

When there is a merger between two companies, one or both companies need to transfer information into a new system. Other forms of business process migration include the transfer of information due to a competitive risk or evolving customer demands.

  1. Cloud Migration

Cloud migration is a general business term involving the movement of information from one location to the cloud. Most businesses are migrating their information to the cloud because the cloud offers so much storage space at such a low cost. How long it takes to migrate information to the cloud depends on the amount of potential cloud data and where that data originates. For small datasets, it may take less than an hour, but for large projects, it can take up to a year.

Stages of the healthcare data migration process

  • Rating

The first step is to understand your current position in order to develop a migration strategy. To get the full picture, all electronic and paper patient record systems should be reviewed. Once you have it, you can estimate the records you want to migrate and decide which tools can handle them. At this point and in the next steps, you can choose to engage a technology partner for EHR integration and migration. Qualified technology companies can apply health data migration best practices to strategize and execute the migration.

  • Data Cleanup

There is no point in migrating misformatted or inaccurate data to have it circulating in your system. You must ensure only clean information remains by identifying records with mistakes, duplicates, or unnecessary details.

  • Structuring

Cleaned data is error free but still heterogeneous. Therefore, records should be structured and categorized. This allows them to be better segmented and managed after migration.

  • Data Conversion

Health platforms typically work with specific data formats and have specific requirements. Therefore, to ensure a smooth transition, old records should be converted to the required format. At this point, it is important to ensure that all records have been converted and nothing has been lost.

  • Data Migration

Once your records are structured and formatted, you can move them to the storage you need. It is important to proceed step by step to import all the data. Overall, migration speed depends on data volume, source and final storage locations, system requirements, and data migration tools.

What are the best practices for healthcare data migration?

  1. Plan

This is probably the most important part of any healthcare data migration, make sure you have a plan and stick to it. Having a detailed plan helps ensure the migration goes smoothly and without any major issues.

  1. Testing

It’s important to test your new system thoroughly before going live with it. This includes testing all of your data as well as the new system itself. By testing everything beforehand, you can catch any potential problems and fix them before the transition happens.

  1. Data Backup

This one should go without saying, but always back up your data before starting a healthcare data migration. This way, if something goes wrong during the transition, you’ll have a backup to rely on.

  1. Patience 

The migration process can take some time. So, be patient and give yourself enough time to complete it properly. Rushing through a data migration can lead to mistakes and problems down the road.

Challenges of healthcare data migration

Moving records across an organization have never been easier. However, knowing ahead of time the challenges of migrating healthcare data can help you prepare for these pitfalls and avoid or mitigate risks. So keep these common data migration issues in mind when moving medical records.

Lack of Planning 

One of the most demanding situations surrounding information migration is the dearth of strategic planning, hindering medical practices from reaping benefits in their new system. The method of migrating information in healthcare is complicated. Those responsible for this major decision want a well-thought-out approach plan that is specific to your practice or hospital’s data and information. This plan needs to focus on how the healthcare information migration will benefit the organization, what should be migrated, from which databases or sources, and at what costs. It’s critical to have an approach plan to avoid risking behind-scheduled deliveries and performance. A migration approach plan will help venture navigation and setting up goals, to gain higher results. To ensure success, making plans will encompass the venture timeline, KPIs, technical considerations, and commercial enterprise considerations. This allows those with the critical job of recognizing the utility and protection requirements, to do so effectively.

Creating a healthcare data migration roadmap can be tedious and difficult if you’ve never done it before. But don’t start moving records without careful planning. Lack of planning has many negative consequences, including:

  • Poorly defined scope. Not knowing the amount of information in the organization makes it difficult to know how much time and how many resources the migration will take.
  • Incorrect budget. Not sure if your current budget is sufficient to move the necessary documents, and cover any unexpected expenses that may arise.
  • Incorrect tool selection. It is difficult to choose the best data migration solution without knowing the organization’s data migration needs from the start.
  • Data duplication or modification. Poorly planned data distribution increases the risk of duplication or distortion of information.
  • Regulatory Violation. Failure to analyze applicable legal requirements before transferring a data set leaves it vulnerable to unlawful data processing practices.
  • Cost increase. Correcting data migration inaccuracies later may require additional investment.

Data Interoperability

Since medical records are heterogeneous, interoperability is one of the biggest challenges when migrating medical data. Some tools generate them in generic formats that may be incompatible. Therefore, data interoperability should be ensured when data is moved to more advanced systems and used for analysis and automation.

Data Quality

Data migration in the healthcare industry requires post-migration data quality assurance and an understanding of the data you plan to transform and use. It is important to regularly update patient data and statistics so that we can provide reliable care to patients in need. Database data quality is one of the most important challenges in data migration. If your medical database has data quality issues, migrating the data and just finding the bad data that was moved is a nightmare. The migration and all the hard work, resources, time, planning, and money invested were wasted.

Regulatory Compliance

By neglecting privacy and data compliance, a single data breach can cost healthcare organizations at least $7 million. Data handlers can identify issues and quickly fix data sets before migrating data to healthcare transformations. However, in doing so, you unintentionally commit a data breach.

In addition to the HL7 FHIR and USCDI standards mentioned above, anyone who maintains medical records must comply with HIPAA, the HITECH Act, CCPA, and many other regulations.  Moving to new software always involves a review of regulatory requirements, even if you’re achieving compliance with legacy systems. An organization, therefore, needs to re-evaluate whether new data processing practices comply with the law.

Benefits of healthcare data migration

  • Reduced Costs

Healthcare organizations can avoid capital expenditures to replace legacy infrastructure equipment by migrating IT platforms and services to the cloud. The cloud provider completely takes care of hardware and software updates and ensures applications are supported by up-to-date infrastructure, reducing costs and time spent on them. Outsourcing maintenance services to the cloud allows providers to save money on in-house IT staff.

  • Easier Access to Data

Cloud-based patient medical and billing data are far more accessible to authorized users than data stored locally, enabling interoperability and collaboration among clinicians in different locations. As healthcare systems expand to new physical locations, cloud migration brings convenient means to securely access data and applications from any devices such as mobile phones, laptops, or wearable devices.

  • Improved Backup and Disaster Recovery

Remote cloud deployments can be used to back up hospital data and systems in an outage or cyberattack event.

  • Greater Storage Capacity

Cloud computing improves scalability and flexibility for businesses; providers with limited on-premises data centers can scale their data storage capacity as needed in the cloud. It enables an enterprise to scale and adopt powerful computing capabilities. Organizations can alter resources on-demand during demand spikes and run workloads closer to where customers are. They can also deploy and remove applications easily.