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Avoiding the Top 3 Clinical Data Migration Mistakes

Clinical data migration is always a challenge for healthcare organizations. Avoiding these mistakes will assist entities in smoothly and securely transitioning data.

Clinical data migration mistakes to avoid.

Source: Thinkstock

By Elizabeth O'Dowd

- Healthcare organizations are faced with the challenge of clinical data migration, which is a rigorous and often underestimated undertaking, especially when it comes to the cloud.

The consequences of migrating clinical data incorrectly are vast and often crippling. Entities could be left without access to their data after an incorrect migration, but many organizations will not be able to afford the time and cost of correcting the migration. Organizations can also suffer a damaged reputation if data is not migrated correctly.

“The place where organizations find out their data was migrated wrong is when they’re doing acceptance testing of a new application and putting the data in the app,” Informatica Chief Healthcare Strategist Richard Cramer told HITInfrastructure.com in a previous interview. “Competence can be questioned when the data is discovered to be wrong during acceptance testing.”

“When data is discovered to be wrong at the end of the process during acceptance testing, organizations are months away from fixing it simply because of the work required to move the data,” Cramer continued. “Then there’s the problem of figuring out what went wrong.”

Migrating data incorrectly is extremely costly which is why taking a disciplined and knowledgeable approach is necessary to move the data as quickly and securely as possible.

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Here are the top three clinical data migration mistakes organizations need to avoid:

Misunderstanding the data

One of the earliest mistakes healthcare organizations make when beginning the migration process is not fully understanding the data that is being moved.

Healthcare data is complex and follows strict compliance guidelines. Clinical data also often contains different source applications, complex data, and data quality problems. Healthcare data is spread across hundreds of applications in some cases. The data in each application may not be the best quality.

“There is an absolute epidemic in applications and it’s prevalent in healthcare. Businesses will use a field in an application that is completely different than what that field was originally for,” Informatica’s Cramer explained. “When you look at that from a data migration perspective, the first thing that needs to happen is the source needs to be understood and the data in that source may be different than what the label on the field says it is.”

READ MORE: Healthcare Cloud Data Migration Challenges Organizations

Organizations need to address data quality issues before migration begins. Moving data from a legacy EHR application to a new EHR application is one scenario where misunderstood data can damage a migration.

For example, the two EHRs have structural differences and data fields may have different labels. Organizations may have been using a designated data field for something else, causing the data to be loaded into the wrong field upon the migration.

Healthcare organizations need to understand their applications and the quality of the data they have and then they can direct it to the appropriate location.

Not scaling the network

Many organizations hesitate to upgrade their network infrastructure for a data migration because they see it as a one-time event. However, most organizations will face many migrations of various sizes over the years, which makes scaling the network an important step.

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Entities that don’t consider the overperformance needed to support both the migration and everyday workflow can run into serious problems. Decades worth of data can be moving through the network during a migration and the amount of network performance needed to support that amount of data requires increased capacity.

“The ability to just move data in terms of the bandwidth that would be available for a large, heavy movement to the cloud or from the cloud is where things get ugly,” ClearSky Data CEO Ellen Rubin told HITInfrastructure.com.

“An organization has to be willing to invest to upgrade and scale their network. In some ways, it’s a short-term problem. If you have a dataset and you’ve moved it, then you’re done because everything that happens with the data from that point is in the cloud.”

Traditional wireless infrastructure cannot typically handle the stress of a full-scale migration. Organizations need to decide if they will take the steps to upgrade their network for the migration, or use one of the migration tools many of the major cloud vendors provide.

Upgrading the wireless network has many benefits beyond the migration and should be completed first for the overall strength of the IT infrastructure. Upgrading the network can be a large expense, but it needs to be considered before the migration even if it delays the migration for a time.

Underestimating the cloud

Organizations remain distrustful of the cloud although it is rapidly growing in popularity in the healthcare industry. The cloud can be an invaluable tool during a clinical data migration because it’s flexibility and elasticity can save organizations money.

Entities can scale their network during a migration to meet demands, along with supporting everyday workflow. However, organizations cannot fully embrace the cloud if they are not willing to consider hybrid deployments.

“Organizations can no longer rely on the fact that everything will either be on-premise or in the cloud,” Informatica’s Cramer explained. “They need to look at data integration and data migration as a component of that and be completely agnostic toward what is cloud and what is on-premise. Organizations don’t need to care if the source system, the target system or the data migration solution is on-premise or in the cloud.”

Organizations can benefit greatly from standing their data migration solution up in the cloud. The scalability of the cloud allows entities to take advantage of all the tools needed to migrate data correctly and successfully, and to turn it on or off as needed.

“This is where the elasticity of the cloud works out very well,” Cramer added. “The application can be put up on a really powerful platform, it can suck all the data in quickly. Then the platform can be downsized to support everyday operational needs.” 

Healthcare organizations need to understand that they are never really done migrating data. Entities need to be aware of the common mistakes and build a migration strategy that ensures the migration is done correctly the first time.



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