Health Care Data Guide – Electronic health record (EHR) systems, IoT devices, AgeTech solutions, and other software used by your healthcare organization collect or store information that is essential for physicians to make informed treatment decisions and for administrators to handle administrative tasks such as invoicing and creating insurance policies. .
Of course, this data must be stored securely and accessible to authorized workers. Sometimes, to achieve this, an organization must go through a healthcare data migration process.
Health Care Data Guide
It can be tempting to dive into implementation as soon as possible. But before that, you need to know how to develop a working healthcare data migration strategy and what to expect along the way.
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The team knows that migrating health data to a cloud or from one system to another should always be a well-planned process. But what best practices should be considered? What pitfalls can we expect? What tools to use? This is exactly what we will explain in this article.
Before we dive deeper into the health data migration process, let’s review what health data actually means. Typically, its definition includes the following:
Understand what health data is needed to plan data migration in the health industry locally, nationally or internationally. It is also essential for medical organizations to know which legal regulations are applicable.
In the United States, for example, the EHR-to-EHR data migration process and related transactions involving protected health information (PHI) must comply with the Health Insurance Portability and Accountability Act (HIPAA) and laws of the state. In Europe, similar actions are protected by the General Data Protection Regulation (GDPR) and the laws of EU member states.
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Now that we’ve covered what health data is, let’s examine the most popular reasons why medical organizations go for data migration.
About 30% of global data is generated by the healthcare sector, and the estimated compound annual growth of 6% puts it at the top of the list of the most data-producing industries by 2025. Considering that the amount of data in worldwide is expected to reach 175 zettabytes (175 trillion gigabytes) in 2025, this figure is quite impressive.
Of course, healthcare organizations must think about how to manage its storage, access and security, so that the collected data can be used and reused. But that’s just one reason for data migration in healthcare. In practice, there are many others, so let’s take a closer look.
The more data that is generated, the more insight the healthcare industry can have. According to the European Commission, innovation in health care is impossible without the proper processing and reuse of data, which gives decision makers a factual basis to improve efficiency and ensure the stability of the health system. However, it is only possible under one condition: if there are secure interoperable cloud data environments at local and global levels and an infrastructure that allows secure data access, transmission and processing. This is why data migration should not be a concern only for providers, but a global healthcare strategy.
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Healthcare data migration is one way to increase the storage capacity of a healthcare organization. With the rapid development of medical technology, existing systems may not have enough space to store all the data generated by the medical institution, to say nothing of the expected increase in volume in the near future. To address ever-increasing business needs, hospitals and clinics may need to migrate their data either to another system or to the cloud.
Accessibility is one of the six main criteria of data quality. The latter is important for the health sector because the decisions of the interested parties are made based on the information they work with and have access to. For example, if doctors do not have access to the entire patient history, there is a greater risk of prescribing a treatment that will cause more harm than good.
This is why many organizations that want to improve data access consider a system upgrade. This process involves moving data to a cloud, a connected network, or a new electronic medical record system that allows interoperability and ensures further use of the information by authorized stakeholders.
Data means nothing if it is not structured and analyzed, but it must be stored somewhere that allows this. Not every data storage solution currently used in healthcare is capable of structuring the collected information and preparing it for further analysis. Analytics is critical to any healthcare organization because it:
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The need for analytics is driving organizations to move to healthcare technology solutions in which analytics algorithms perform automatic data analysis based on selected criteria. In many cases, this process involves migrating data from legacy legacy systems.
Some laws require organizations to retain business documents or patient records for a certain period. For example, under HIPAA rules, business associates and covered entities must retain health information for a minimum of six years from the date it was created or from the time it was last in effect (whichever later life). Consequently, many hospitals and healthcare organizations are moving to cloud storage to avoid clutter and ensure convenient document workflow.
Since regulations cover not only what should be stored, but also how it should be stored, legacy legacy systems may not have a compliant technical foundation. To avoid compliance claims and fines, organizations must switch to compliance solutions and, as a result, migrate data.
For any modern medical organization, it is important to use health technology tools that can bring better results and optimize workflow. Medtech is constantly evolving and offering better solutions in terms of performance or cost, so hospitals may want to change EHR partners, build new ones, or modify their current solutions. All of this includes EHR data migration.
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Data migration during mergers and acquisitions (M&A) is standard practice. M&A processes occur when private or public health care organizations change status, owners, structure, merge into a joint entity, or undergo other changes. Most of them require the movement of digital data from system to system, which covers extracting the data from the source followed by a conversion process (converting the documents to the accepted format) and sending them to the target storage.
Data migration should be done step by step to bring the desired results. Let’s see what stages you should plan when migrating health data.
The data migration process requires creating and following a strategy that will ensure a smooth migration without missing data or system failures. Here are the four stages of a successful data migration.
Not all datasets need to be migrated – some need to stay on the original legacy systems or on internal servers. During the data analysis phase, it is necessary to understand which data should migrate to other platforms and portals, which data should be destroyed and which data is most valuable from a long-term perspective.
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Since health data is usually heterogeneous, you need to structure and classify it before loading it into the new memory. Successful completion of this phase will help you sort the data after the transfer.
Healthcare data migration platforms often only work with specific data formats. Therefore, to ensure an easy transfer, you need to convert the information from the old system to the required format. It is important to ensure that no data is lost during this phase.
When the data is analyzed, filtered, structured and converted, it is ready to be moved to the desired destination. The methods and complexity of data migration will depend on the following criteria:
The choice of medical data migration tools will largely depend on the amount of data to be transferred, its quality, your budget and your strategy. Here are the three most common options.
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When you have a small volume of well-structured data, your internal team can come up with self-written tools (usually, simple code written to execute a few steps). They are the simplest solution for relatively insignificant amounts of data, but the high quality of data transfer is usually not guaranteed. This is why you should always back up data before transferring it with self-written solutions.
If the goal is only to transfer static data, purpose-built software solutions may be an option. Fivetran, IRI NextForm, IBM InfoSphere and Microsoft SQL are the most popular applications on the market for migrating data across environments.
Usually, these solutions are used during M&A where data transfer takes place within the same network and enterprise. They are also the last resort for cases where cloud tools cannot be used due to legal requirements.
Cloud-based data migration solutions are the most advanced option on the market because they allow for the automatic conversion of large volumes of data. AWS Data Migration Service, Google Cloud VMware engine, StarfishETL, Carbonite are cloud solutions that transfer homogeneous and heterogeneous data sets to and from the cloud, provide backup copies and maintain the entire data infrastructure.
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As with on-premise solutions, you should ensure that you are using cloud storage and data migration tools that are HIPAA compliant. Note that cross-state data transfer may be limited or subject to specific policies.
The sensitive nature of medical data and high volumes present a number of health data migration issues. Read more about this tricky side of data migration.
One of the reasons why healthcare organizations still rely on their legacy legacy systems
